satya final project

Customer Focus of Wireless Telecom Companies in India

A PROJECT REPORT SUBMITTED IN PARTIAL FULFILLMENT OF THE

REQUIREMENT FOR THE AWARD OF THE DEGREE OF

MASTER OF BUSINESS ADMINISTRATION

2008-10

BY

Satya Narayan Behera (Regd.No. 08482)

SCHOOL OF BUSINESS MANAGEMENT, ACCOUNTING & FINANCE

SRI SATHYA SAI UNIVERSITY

(Established under Section 3 of the UGC Act, 1956)

Accredited by NAAC at A++ level

PRASANTHI NILAYAM

2008-2010

(DECEMBER 2009)

OFFERING AT THY

divine LOTUS

FEET...

SCHOOL OF BUSINESS MANAGEMENT, ACCOUNTING AND FINANCE

CERTIFICATE & DECLARATION

This project entitled “Customer Focus of Wireless Telecom Companies in India”

is an original work done by me under the supervision of Prof. Ramaier Sriram,

School of Business Management, Accounting & Finance, Sri Sathya Sai

University, Prasanthi Nilayam, in partial fulfillment of the requirements for the

award of the degree of Master of Business Administration of this University, and

has not formed the basis for the award of any degree, diploma or any other such

title by this or any other university.

Prof. Ramaier Sriram Satya Narayan Behera

(Project Guide) (Regd. No. 08482)

Place: Prasanthi Nilayam A. Sudhir Bhaskar

(Prof. and Dean)

Date:

SRI SATHYA SAI UNIVERSITY

(Established Under Section 3 of the UGC Act 1956

Accredited by NAAC at A++ Level)

ACKNOWLEDGEMENTS

First and foremost, I would like to express my heartfelt gratitude to my

beloved Master, Bhagawan Sri Sathya Sai Baba, with whose grace and

blessings alone this project has been successful.

I wish to thank my parents and my sisters for their continuous concern

and prayers which enabled me to complete this endeavour.

I sincerely thank my guide Dr Ramaier Sriram for his constant guidance,

encouragement and support.

I would like to express my sincere thanks to Shri Renju Reghuveeran, Shri

Piyush Shrivastava, Shri Prakash Chittaranjan and the Library staff

members for extending to me all the resources necessary to complete

this project.

I would like to convey my gratitude to the members of Hostel Computer

Center and Sai Images Department for their help and support.

I also thank all my classmates and roommates for their kind cooperation

and encouragement in helping me to complete this project.

I cannot possibly name all those who have helped me in the completion

of this work. But, I will be failing in my duty if I do not express my

gratitude to those noble souls who have directly or indirectly provided

the necessary help to complete this project.

Satya Narayan Behera

Page i

Table of Contents

1 INTRODUCTION .......................................................................................................... 1

1.1 Overview of wireless telecom industry .................................................................... 1

1.2 Statement of the problem ......................................................................................... 4

1.3 Nature of study ......................................................................................................... 4

1.4 Objective of study .................................................................................................... 4

1.5 Scope of study .......................................................................................................... 5

1.6 Limitations of study .................................................................................................. 5

1.7 Scheme of chapterisation .......................................................................................... 5

2 LITERATURE REVIEW ............................................................................................... 7

2.1 Customer focus ......................................................................................................... 7

2.2 Characteristics of customer-focused organizations .................................................. 7

2.3 Customer satisfaction ............................................................................................... 8

2.4 Customer satisfaction tests ....................................................................................... 9

2.5 TRAI‘s quality of service initiative ........................................................................ 10

2.6 Need of the hour: Customer Relationship Management ........................................ 11

3 THEORETICAL BACKGROUND .............................................................................. 15

3.1 SWOT Analysis (Strengths, Weaknesses, Opportunities, Threats) ....................... 15

3.1.1 External environment (opportunity and threat) analysis ................................. 15

3.1.2 Internal environment (strengths/weaknesses) analysis ................................... 16

3.2 Oneway ANOVA Test ........................................................................................... 16

3.3 Factor analysis ........................................................................................................ 17

3.4 Multivariate regression analysis ............................................................................. 18

4 METHODOLOGY AND DESIGN OF STUDY .......................................................... 20

Page ii

4.1 Research design for the study ................................................................................. 20

4.2 Data collection ........................................................................................................ 21

4.3 Survey construction ................................................................................................ 21

4.3.1 Sampling plan ................................................................................................. 21

4.3.2 Questionnaire design ....................................................................................... 21

4.3.3 Scale construction ........................................................................................... 23

4.4 Tools used for the study ......................................................................................... 23

4.5 Treatment of data .................................................................................................... 24

4.5.1 Weighted satisfaction scores ........................................................................... 24

5 ANALYSIS AND FINDINGS ...................................................................................... 26

5.1 Questionnaire analysis ............................................................................................ 26

5.1.1 Demographic profile of respondents ............................................................... 26

5.1.2 Oneway ANOVA on survey data operator-wise ............................................. 32

5.1.3 Oneway ANOVA on TRAI data operator-wise .............................................. 35

5.1.4 Overall customer satisfaction scores from survey .......................................... 37

5.2 Airtel – A case analysis .......................................................................................... 38

5.2.1 Airtel: profile ................................................................................................... 38

5.2.2 Partners ............................................................................................................ 39

5.2.3 Swot analysis ................................................................................................... 39

5.2.4 Top competitors .............................................................................................. 44

5.2.5 Customer focussed strategies of Airtel ........................................................... 44

5.2.6 Airtel quantitative data analysis ...................................................................... 46

5.2.7 Airtel qualitative data analysis ........................................................................ 88

5.2.8 Overall Findings of customer‘s perception of Airtel‘s services: .................... 95

6 RECOMMENDATIONS ............................................................................................ 101

Page iii

6.1.1 Recommendations/Suggestions based on study of CRM for the present

situation of Bharti Airtel ............................................................................................. 101

7 CONCLUSIONS ......................................................................................................... 106

7.1 Conclusion ............................................................................................................ 106

8 APPENDIX ................................................................................................................. 107

8.1 Questionnaire ........................................................................................................ 107

8.2 Tables ................................................................................................................... 123

9 BIBLIOGRAPHY AND REFERENCES ................................................................... 150

Page iv

List of Tables

Table 1: Summary of age profile of respondents for the survey ........................................... 26

Table 2: Summary of gender profile of respondents for the survey ..................................... 27

Table 3: Summary of occupation profile of respondents for the survey ............................... 28

Table 4: Summary of operator profile of respondents for the survey ................................... 29

Table 5: Summary of Area profile of respondents for the survey......................................... 30

Table 6: Summary of User type profile of respondents for the survey ................................. 30

Table 7: Summary of Technology type profile of respondents for the survey ..................... 31

Table 8: Test of homogeneity of variances ........................................................................... 32

Table 9: Oneway ANOVA test results .................................................................................. 33

Table 10: Test of homogeneity of variances ......................................................................... 36

Table 11: ANOVA results ..................................................................................................... 36

Table 12: Airtel‘s strategic partners ...................................................................................... 39

Table 13: SWOT analysis of Airtel ....................................................................................... 40

Table 14: Descriptives of oneway ANOVA test ................................................................... 57

Table 15: Test of Homogeneity of Variances ....................................................................... 58

Table 16: Oneway ANOVA test results ................................................................................ 58

Table 17: Games-Howell test for post-hoc analysis segment-wise ...................................... 59

Table 18: Tukey‘s test for homogeneous grouping of means ............................................... 60

Table 19: Descriptives of oneway ANOVA test between telecom regions .......................... 62

Table 20: Test of Homogeneity of Variances ....................................................................... 62

Table 21: Oneway ANOVA test results between telecom regions ....................................... 63

Table 22: Games-Howell test for post-hoc analysis for telecom regions ............................. 63

Table 23: Tukey‘s test for grouping of homogeneous means of telecom regions ................ 64

Table 24: One sample Statistics ............................................................................................ 69

Page v

Table 25: One sample T test on overall quality satisfaction scores between survey data and

TRAI data .............................................................................................................................. 70

Table 26: Descriptive statistics for regression analysis of Airtel postpaid customers .......... 75

Table 27: Regression model for Airtel postpaid customers .................................................. 76

Table 28: Oneway ANOVA test on Airtel postpaid customers ............................................ 76

Table 29: Regression model components for Airtel postpaid customers .............................. 77

Table 30: Descriptive statistics for regression analysis of Airtel prepaid customers ........... 83

Table 31: Regression model for Airtel prepaid customers ................................................... 84

Table 32: Oneway ANOVA test on Airtel prepaid customers .............................................. 84

Table 33: Regression model components for Airtel prepaid customers ............................... 85

Table 34: Factors affecting the postpaid and prepaid Airtel customers ................................ 88

Table 35: Crosstabulation of time frame of acquisition of service and time taken to activate

service for Airtel respondents ............................................................................................... 89

Table 36: Descriptives of Oneway ANOVA test between operators from survey ............. 123

Table 37: Games-Howell test for post-hoc analysis ........................................................... 123

Table 38: Tukey‘s test for homogeneous grouping of means ............................................. 125

Table 39: Descriptives of ANOVA TRAI operator-wise ................................................... 125

Table 40: Tukey's test for ANOVA TRAI operator-wise ................................................... 126

Table 41: Comparison of satisfaction scores of TRAI survey, survey and TRAI benchmark

............................................................................................................................................. 127

Table 42: TRAI data on customer satisfaction with provision of service ........................... 129

Table 43: TRAI data on customer satisfaction with postpaid billing performance ............ 130

Table 44: TRAI data on customer satisfaction with prepaid billing performance .............. 130

Table 45: TRAI data on customer satisfaction with help services ...................................... 131

Table 46: TRAI data on customer satisfaction with network performance, reliability and

availability ........................................................................................................................... 132

Page vi

Table 47: TRAI data on customer satisfaction with maintainability .................................. 133

Table 48: TRAI data on customer satisfaction with offered supplementary services......... 133

Table 49: TRAI data on customer satisfaction with overall quality of service ................... 134

Table 50: Comparison of satisfaction scores of TRAI survey, survey and TRAI benchmark

for Airtel .............................................................................................................................. 135

Table 51: Descriptive statistics of factor analysis of Airtel postpaid customers ................ 137

Table 52: Communalities of factor analysis of Airtel postpaid customers ......................... 138

Table 53: Factor analysis of Airtel postpaid customers ...................................................... 139

Table 54: Descriptive statistics for factor analysis of Airtel prepaid cusotmers ................ 141

Table 55: Rotated Component Matrix for factor analysis for Airtel postpaid customers ... 142

Table 56: Correlations between the factors selected for regression analysis for Airtel

postpaid customers .............................................................................................................. 143

Table 57: Communalities of factor analysis of Airtel prepaid customers ........................... 144

Table 58: Factor analysis of Airtel prepaid customers ....................................................... 145

Table 59: Rotated Component Matrix for factor analysis for Airtel prepaid customers .... 146


prepaid customers ............................................................................................................... 148

Page vii

Table of Figures

Figure 5-1: Age profile of respondents for the survey .......................................................... 26

Figure 5-2: Occupation profile of respondents for the survey .............................................. 27

Figure 5-3: Operator profile of respondents for the survey .................................................. 28

Figure 5-4: Area profile of respondents for the survey ......................................................... 29

Figure 5-5: User type profile of respondents for the survey ................................................. 30

Figure 5-6: Technology type profile of respondents for the survey ..................................... 31

Figure 5-7: Plot of overall quality satisfaction means versus telecom operator ................... 34

Figure 5-8: Plot of Operator vs overall satisfaction .............................................................. 37

Figure 5-9: Plot of TRAI data on customer satisfaction with provision of service .............. 47

Figure 5-10: Plot of TRAI data on customer satisfaction with postpaid billing performance

............................................................................................................................................... 48

Figure 5-11: Plot of TRAI data on customer satisfaction with prepaid billing performance 49

Figure 5-12: Plot of TRAI data on customer satisfaction with help services ....................... 50

Figure 5-13: Plot of TRAI data on customer satisfaction with network performance,

reliability and availability ..................................................................................................... 51

Figure 5-14: Plot of TRAI data on customer satisfaction with maintainability .................... 52

Figure 5-15: Plot of TRAI data on customer satisfaction with offered supplementary

services .................................................................................................................................. 53

Figure 5-16: Plot of TRAI data on customer satisfaction with overall quality of service .... 54

Figure 5-17: Plot of TRAI data on customer satisfaction with overall quality of service .... 54

Figure 5-18: Plot of overall quality satisfaction means versus telecom segments ................ 60

Figure 5-19: Plot of telecom regions versus the overall satisfaction score means ............... 65

Figure 5-20: Age profile of Airtel respondents ..................................................................... 66

Figure 5-21: Gender profile of Airtel respondents ................................................................ 66

Figure 5-22: Occupation profile of Airtel respondents ......................................................... 67

Page viii

Figure 5-23: Area profile of Aitel respondents ..................................................................... 67

Figure 5-24: User type profile of Airtel respondents ............................................................ 68

Figure 5-25: Plot of Factors extracted versus the eigen values for Airtel postpaid customers

............................................................................................................................................... 71

Figure 5-26: Customer satisfaction model for Airtel postpaid customers ............................ 78

Figure 5-27: Plot of overall quality satisfaction score means with frequency for Airtel

postpaid customers ................................................................................................................ 79

Figure 5-28: Plot of observed overall quality satisfaction score means with expected values

for Airtel postpaid customers ................................................................................................ 79

Figure 5-29: Plot of Factors extracted versus the eigen values for Airtel prepaid customers

............................................................................................................................................... 80

Figure 5-30: Customer satisfaction model for Airtel prepaid customers .............................. 86

Figure 5-31: Plot of overall quality satisfaction score means with frequency for Airtel

prepaid customers ................................................................................................................. 87


for Airtel prepaid customers ................................................................................................. 87

Figure 5-33: Pie chart for time frame of acquisition of service by Airtel respondents ......... 89

Figure 5-34: Pie chart for time taken to activate service for Airtel respondents .................. 89

Figure 5-35: Pie chart for issues related with prepaid charges for Airtel respondents ......... 90

Figure 5-36: Pie chart for issues related with accuracy of postpaid bills for Airtel

respondents ............................................................................................................................ 91

Figure 5-37: Pie chart for issues related with clarity of postpaid bills for Airtel respondents

............................................................................................................................................... 91

Figure 5-38: Pie chart for reasons for not querying customer care for Airtel respondents ... 92

Figure 5-39: Pie chart for usage of value added services for Airtel respondents ................. 93

Figure 5-40: Pie chart for reasons for not using value added services for Airtel respondents

............................................................................................................................................... 93

Page ix

Figure 5-41: Pie chart for usage of types of value added services for Airtel respondents .... 94

Figure 5-42: Pie chart for knowledge about reception of subscription of service details for

Airtel respondents ................................................................................................................. 94

Page x

ABSTRACT

The purpose of this study is to analyse the customer focus of wireless

telecom industry in India. In the competitive and regulated

environment, telecom service providers have to focus on improving

customer satisfaction levels so as to be characterized as customer

focussed. Thus they will be able to provide superior service quality

resulting in higher satisfaction levels leading to the retaining of loyal

customers and achievement of organizational goals.

The study conducted a survey among wireless telecom service users

to establish the satisfaction levels among the customer. The study

also used factor analysis and multivariate regression analysis to find

the factors affecting the Indian telecom user’s customer satisfaction.

It also used TRAI survey reports to find the satisfaction levels over

the years and validate the survey results.

It has been found from the study that the customers of wireless

telecom services are not satisfied with customer care services and

value added services. This shows that the perceived performance is

not matching the expectations of customers. Therefore the study

concludes that wireless services overall satisfaction can be improved

by improving the internal processes by using solutions based on CRM

and analytics.

Chapter 1

Introduction

INTRODUCTION

Customer focus of wireless telecom companies in India Page 1

1 INTRODUCTION

1.1 Overview of wireless telecom industry

In the 21st century most organizations are trying to become more customer focussed. The

new breed of customer is very well informed. These customers are swapping passive roles

for much deeper involvement. ―Consumers‖ are becoming ―producers,‖ often creating

entertainment and advertising content for their peers, while demanding flexibility and

responsiveness from companies with whom they choose to do business. Therefore a lot of

importance is given by organizations, to the relationship they have with their customers.

This phenomenon is also observed in Indian organizations.

According to Reserve Bank of India‘s annual report 2008-09[21]

the Indian services sector

has not only exhibited minimum growth of 9 per cent in the recent five years, but its share

in aggregate GDP has also increased to about 64.5 per cent. The current global economic

crisis being unprecedented in the recent history in terms of the magnitude of the impact as

well as the duration, the past resilience of the services sector could be tested in future.

While services sector‘s share in GDP improved marginally from 63.0 per cent in 2007-08 to

64.5 per cent during 2008-09, its relative contribution to GDP growth rate increased

significantly from 74.1 per cent to 88.2 per cent during the same period.

According to Mani[19]

Communications is the fastest growing sector in India‘s economy.

No other sector of the economy has clocked such a rate of growth. The sector accounts for

about 4 per cent of GDP and the recent high rate of growth has contributed to about 11 per

cent of the growth in overall GDP of the country. Consequently, it is generally opined that a

revolution of sorts is taking place in the Indian telecom industry. One of the dimensions of

this growth taking place in the Indian telecom industry is the dominance of wireless

technology. The Indian telecom sector is now heavily dominated by wireless technologies,

which include cellular mobile and fixed wireless technologies. In fact, almost the entire

increase in the availability of telephones has been contributed by wireless technologies. The

ratio of wireless to wireline services is now almost five which is the highest in the history

of telecom industry in India. In fact what is interesting is that since 2005, the wireline

services have started falling in terms of sales. A number of factors explain this decrease in

INTRODUCTION


the popularity of fixed telephones, which has now become a worldwide trend. This heavy

reliance of wireless technologies, while extremely positive from the availability point of

view, has some implications for the diffusion of other services in the country.

Total Wireless Subscribers in the country stand at 391.76 million[27]

. This results in a

percentage growth of 12.93% during the quarter. Out of this the Urban Wireless

Subscribers are 282.05 Million (72%) and Rural Wireless Subscribers 109.71 Million

(28%); the GSM Subscribers are 297.26 Million (75.88%) and CDMA Subscribers 94.50

Million (24.12%). This leads us to make the following observation that rate of growth in

mobile subscriber base has been substantially high.

Some of the characteristics exhibited by the wireless telecom industry in India are the

following:

The cost of ownership of mobile services is very low. Therefore the customer base

of wireless telecom services is increasing at such a fast pace.

The need for connection and communication with others helps in fulfilling

emotional needs.

The use of communication services is shared by all households, compared only by

services like utilities, banking and other financial services.

On top of this wireless telecom services also create and enhance a lot of

individualism leading to attraction of these services.

The wireless telecom sector is dynamic and experiencing explosive growth. It is having a

lot of opportunities as well as facing a lot of threats. Mobile number portability, where a

subscriber would be able to shift from one operator to another without changing his/her

number, is such a disruptive threat. Therefore the telecom operators foreseeing the future

where they will have to compete on brand value and service offerings have to tighten their

belts as the switching costs for customers will dramatically lower.

Another interesting development has been the advent of mobile virtual network operators

(MVNO). These companies buy airtime and SIM cards in bulk from telecom operators and

sell them under their own brand. It is expected that the virtual operators will help shore up

INTRODUCTION


the fallen Average Revenue Per User‘s (ARPU) from Rs 450 in 2000 to about Rs 200

today. They will help the new telecom licensees to acquire customers faster, as well as

established licensees in better utilisation of resources for netting higher revenues.

In this dynamic and regulated environment, telecom service providers have a very

important goal in acquiring new customers and retaining loyal customers. They also have to

do this in a fast manner, as the market is growing at such a scorching pace that every month

world records are being created in adding new subscribers. While this has helped in

increasing the tele-density of the country, consequently helping people network and

communicate much faster, cheaper and effectively, whether the quality of service provided

has improved, or at least remained at a desired level is questionable. When more

subscribers are added on a daily basis, there should be capacity to enable services with the

desired level of quality.

In this context, marketing philosophy is fundamentally based upon the satisfaction of

customer needs and achievement of organisational goals. Essentially, it has always been an

inclusive aspect of the marketing orientation that there should be customer care and

satisfaction in order to meet customer needs.

Therefore the question is, to what degree telecom service providers are customer oriented to

meet customer‘s satisfaction needs. For this we need to find out the present degree of

customer satisfaction for telecom service providers. According to Telecom Regulatory

Authority of India (TRAI) survey reports on customer perception of service provided27]

, the

overall satisfaction scores of all the telecom service providers in all the telecom circles

remain below the acceptable benchmark of TRAI. This clearly brings out the fact that the

service providers are yet to achieve the desired level of quality for providing customer

satisfaction. But there has been very little research in collating the survey reports and seeing

a holistic picture for a service provider over a period of time. There is also sparse literature

available to find factors affecting the Indian telecom customer‘s satisfaction. Based on

these findings, the Indian telecom customer‘s requirements could be established.

Many researchers have found the effective application of Customer Relationship

Management (CRM) in the telecom sector in helping to get a complete view of the

INTRODUCTION


customer. This complete view serves the service provider in providing excellent customer

service to the exact needs of the customer. The use of CRM will also help in personalizing

the service for the customer. The use of CRM in this way helps in satisfying the customer‘s

need of identity and personalized service contributing to satisfaction. Hence satisfied and

loyal customers will prove the service provider to be customer focused.

1.2 Statement of the problem

There is a wide gap between the customer satisfaction from Quality of Service (QoS)

provided by telecom service providers according to TRAI benchmarks and customer‘s

voice.

1.3 Nature of study

The project studies the nature of wireless telecom industry and determines the customer

orientation of the industry. It determines the extent of satisfaction or dissatisfaction with

service quality of telecom service providers. The project also studies the underlying factors

of Indian customer‘s satisfaction leading to insights which help in improving customers‘

perception of service quality delivered.

1.4 Objective of study

1. To study wireless telecom industry‘s customer focus initiatives from their public

documents and conduct SWOT analysis.

2. To analyze the customer satisfaction provided by the wireless telecom industry by

analyzing primary and secondary data. To find factors which affect customer

satisfaction and find the relationships between overall customer satisfaction and the

factors affecting it.

3. To suggest solutions based on CRM and analytics which can help enhance the

customer focus of wireless telecom industry.

INTRODUCTION


1.5 Scope of study

1. Analyse wireless telecom industry‘s public documents towards customer focus

initiatives.

2. Conduct survey on customer satisfaction from wireless telecom services.

3. Use of secondary information sources including TRAI Reports on telecom industry.

4. Evaluating solutions provided by CRM and analytics for wireless telecom industry.

1.6 Limitations of study

1. The generalizability of the results should not be overstated. One reason may be this is

based on reported than actual behaviour.

2. The telecom service provider‘s customer oriented initiatives are based on their public

documents only.

3. The study is based on TRAI‘s construct of QoS and therefore other constructs which

might affect customer satisfaction have not been taken into consideration.

In view of the above, this study cannot be considered to be exhaustive in nature, but can be

used as a prelude for further research.

1.7 Scheme of chapterisation

CHAPTER 1: INTRODUCTION: This chapter gives a brief Introduction about the study

along with the Nature, Objective and limitations of the study.

CHAPTER 2: LITERATURE REVIEW: This chapter briefly summarizes the definitions

of key terms, importance and effect of customer focus and customer satisfaction on the

fortunes of telecom service providers and factors which influence customer satisfaction

CHAPTER 3: THEORETICAL BACKGROUND: This chapter covers various

theoretical and conceptual aspects related with customer focus and customer satisfaction.

INTRODUCTION


CHAPTER 4: METHODOLOGY AND DESIGN OF STUDY: This chapter includes the

methodology adopted for carrying out the survey and the discussion on the treatment of

data.

CHAPTER 5: ANALYSIS AND FINDINGS: This chapter analyses the data gathered and

finds insights about the customer satisfaction levels in the country.

CHAPTER 6: SUMMARY AND CONCLUSIONS: This chapter summarizes all the

previous chapters and provides conclusion to the study.

Chapter 2

Literature

Review

LITERATURE REVIEW


2 LITERATURE REVIEW

The literature review section presents a comprehensive summary of the relevant knowledge

present in the area of customer focus of telecom service providers.

2.1 Customer focus

We have analysed the common and widely accepted definitions of customer focus and

present a comprehensive definition for customer focus:

It is an organizational orientation [3]

towards providing excellent customer service [5]

and

Satisfy needs of potential and actual customers[3]

.

Follow customer specifications [12]

.

Greatly value customer relationships [5]

.

Involve customers in product development and service development [5]

.

Build trust and maintain integrity and strategic partnerships with customers [5]

.

Structure the company so every tier supports the person providing the service to the

customer [5]

.

Move beyond the notions of customer satisfaction and loyalty and encourage

customers to be advocates for a product or service [5]

.

Treat colleagues like customers by building obliging, responsive and respectful

relationships [5]

.

2.2 Characteristics of customer-focused organizations

Through the analysis of literature, we have found the following characteristics which a

customer focussed company should possess.

They always interact with customers and seek feedback from them. They analyse

feedback and use the relevant information to change their internal processes and

respond swiftly [18]

.

LITERATURE REVIEW


They take customer care seriously by providing toll-free number and help desks so

that they get valuable immediate feedback. They try to help fix problems within an

acceptable timeframe [18]

.

They value customer satisfaction metrics and results on par with financial metrics

[18].

Through the review of literature, we have been able to understand that for a telecom service

provider to be customer focussed, it has to be able to satisfy the needs of its potential and

actual customers by providing excellent customer service. To satisfy the needs of

customers, the service provider has to constantly monitor and receive feedback from

customers. Using customer satisfaction results, the service provider receives feedback about

its services and consequently feeds the information to its process to improve service quality

and satisfy customers.

Therefore the need for critical review of customer satisfaction has to be there so as to

understand how a telecom service provider can satisfy its customers.

2.3 Customer satisfaction

Through the analysis of current literature on customer satisfaction we arrive at the

following definition of customer satisfaction.

Customer satisfaction is defined as a person‘s feelings of pleasure or disappointment

resulting from the comparison of a product/service‘s perceived performance in relation with

his or her expectation [2]

.

Hence for telecom service providers to achieve customer satisfaction, researchers

recommend the following action:

Mobile carriers must focus on service quality and offer customer-oriented services

to heighten customer satisfaction [13]

.

Customer satisfaction can be improved by the use of improving service quality and

perceived value [16]

.

LITERATURE REVIEW


Mobile service providers must change either customer perception or service quality

to improve customer satisfaction [9]

.

Acceptance and satisfaction of value added services is heavily influenced on quality

of service experienced by the user [14]

.

Therefore telecom service providers should look to improve service quality. Researchers

have empirically found out the factors affecting service quality so that service providers can

act decisively. Call quality, value-added services, and customer support were among the

important factors having significant impact on service quality.

The improvement in service quality by making an impact on improving the factors affecting

service quality will lead to improvement in customer satisfaction levels. This will provide

lots of benefits. A high customer satisfaction level heightens customer loyalty and prevents

customer churn, lowers customers‘ price sensitivity, reduces the costs of failed marketing

and of new customer creation, reduces operating costs due to customer number increases,

improves the effectiveness of advertising, and enhances business reputation [1]

.

Researchers give another way of improving customer satisfaction, which is by keeping a tab

on the early warning signals for the degree of customer retention. There are two factors

which provide us such early warning signals. They are the customer assessment about the

prices charged being good and fair (compared against competitors), and, the customer

perception of the functional benefit of mobile communications services [11]

.

2.4 Customer satisfaction tests

From present understanding of customer satisfaction we can infer that the telecom operators

have to look at customer satisfaction as a metric to provide the perception of the functional

benefits being enjoyed by the customer. This will give the telecom operators an indication

of what the customer is thinking about them.

This leads us to arrive at user perceptions as a means of improving customer satisfaction.

User perceptions are psychological constructs that must be measured indirectly using

psychological instruments [14]

. There are two major approaches for the measurement of

LITERATURE REVIEW


quality of service from the user‘s point of view: opinion polls and customer satisfaction

surveys. Customer satisfaction tests are suggested to be closely related to usability testing.

Usability testing is defined as techniques to collect empirical data while observing

representative end users using the product itself [22]

. The main difference between usability

testing and customer satisfaction tests is the focus. Customer satisfactions tests analyze the

quality of service as a whole.

2.5 TRAI’s quality of service initiative

In the Indian telecom sector context, the telecom regulator TRAI has come up with

regulation named, ―Regulation on Quality of Service of Basic and Cellular Mobile

Telephone Services, 2005‖ [26]

to lay-down the standards of quality of service to be

provided by the service providers. The regulation also states about the regular testing of

QoS performance and assessment of customer satisfaction with QoS. Hence TRAI regularly

undertakes customer satisfaction tests for the industry. This provides valuable information

to service providers about customer perception of QoS delivered. According to TRAI [26]

,

Quality of service is the main indicator of the performance of a telephone network and of

the degree to which the network conforms to the stipulated norms. The subscriber‘s

perception of the QoS is determined by a number of performance factors. The purpose of

laying down Quality of Service Parameters is to:

1. Create conditions for consumer satisfaction by making known the quality of service

which the service provider is required to provide and the user has a right to expect.

2. Measure the Quality of Service provided by the Service Providers from time to time

and to compare them with the norms so as to assess the level of performance.

3. Generally protect the interests of consumers of telecommunication services.

Therefore we have been able to arrive at the need for customer satisfaction test to be

customer focussed. Hence the service providers should be able to continuously monitor

customer satisfaction levels, satisfy the customers and be customer focussed. But to retain

these satisfied customers, service providers have to make these customers loyal by building

LITERATURE REVIEW


longer and stronger relationships. By building relationships with customers, service

provider takes the level of trust and commitment between them a notch higher. The service

provider will be able to build a switching barrier which is above monetary benefits and

consists of emotional benefits. Researchers have shown that CRM is used for building

relationships and improving switching barrier. Switching barrier is the hurdle which

customers would have to jump to switch to a different service provider. The factors

significantly affecting the switching barrier appeared to be switching costs such as loss cost,

move-in cost and interpersonal relationships. Hence mobile carriers must develop a three-

pronged strategy of developing customer reward programs that compensate customers,

increasing the cost of switching and developing and carrying out relationship-oriented

marketing to enhance interpersonal relationship with customers[13]

.

2.6 Need of the hour: Customer Relationship Management

From the review of literature, we have been able to arrive at the following definition for

CRM.

It consists of the processes a company uses to track and organize its contacts with its

current and prospective customers. Hence it is not just about technology but about strategy

and process [7]

.

Researchers say that CRM gives the complete information and provides a holistic view of

the customer. Some of the views suggested by researchers are:

CRM is an attitude that needs to pervade the company, but it needs a solid

foundation of knowledge of customers [29]

.

With the help of enterprise applications like CRM the telecom service providers are

now able to obtain complete customer information. They are now able to have a

unified view of the customer so that all the interactions of different departments and

services of the company with the customer are at the dashboard [4]

.

Therefore the value provided by CRM is:

http://en.wikipedia.org/wiki/Customer

LITERATURE REVIEW


The knowledge about customers and their interactions with the company facilitates

better business decisions and encourages customer loyalty and retention [29]

.

Telecom service providers have been able to streamline their business processes to

reduce variability, improve of quality of service and hence lead to positive financial

results for the company. Through the use of better technology companies can handle

more in less time, be more accurate, and hence lead to more quality services for the

customer [4]

.

In this way the company can provide more value to the customer, more satisfaction

thereby increasing customer loyalty leading to retention and revenues [4]

.

Online CRM provide online billing, online repair, ordering of routers and private

branch exchanges, provide access to consultants online. This has helped the

customers in faster access to bills, faster resolution of bills, easier access to services

and provisions. This ultimately leads to richer customer interaction and higher

customer satisfaction [28]

.

Analytical CRM solutions can perform precise market segmentation, trending and

modelling, customer analysis and reporting using centralized customer data from

disparate sources. By doing this telecom service providers will be able to understand

what products are helping to retain the customers and which ones are experiencing a

loss of customers [6]

.

Hence we can see the value provided by CRM in satisfying customers and building a

relationship with them. But literature also has failures stories about the implementation of

solutions related with CRM.

Literature says that most telecom companies haven‘t been able to understand what CRM

stands for. Most of them have thought of it as a technological solution and not as a change

in business processes. So they have not been able to focus on getting their CRM strategy

right [17]

. According to analysts most CRM initiatives have disappointed telecom companies

because they are too focused on management and have done little to improve the customer

relationship experience. Because of the detoured focus on management, carriers don't

integrate CRM with all touch-points in the customer lifecycle, miss out key opportunities to

analyze and improve on the customer experience, and overlook the importance of sharing

customer data across departments and even back-office application silos. As a result, there

LITERATURE REVIEW


is little synergy across departments, resulting in skyrocketing costs while process gaps

remain the norm. Some of the other problems are the integration with the legacy systems

and other technical barriers, the gap between the CRM application software solution and

functionality, the need for vendors to increase the functionality critical for carriers and offer

a more valuable solution.

Therefore telecom service providers should learn from the successes and failures of other

industries and follow a set of guidelines for successful implementation. Some of the things

which they should do are:

1. They have to collect and integrate data to create a single comprehensive view of the

customer across all the services. They have to design systems that allow them to

take information about customer data, profitability, customer usage, likes and

dislikes, and using that information to extend the customer‘s relationship with the

organisation.

2. They have to focus the majority of their efforts on servicing their most profitable

customers. It is the issue of spending the right amount of money in order to market

the right bundle to the right customers.

3. They have to provide a virtual branch office on the web even though all the

customers are not yet willing to move all their transactions to the internet. So they

should promote the web services at every touch point to remind the customer about

self-service. They also have to make the websites more user-friendly for faster

adoption.

4. They can rethink their expectations out of CRM and slowly rollout CRM strategy in

a phased manner to discourage huge investments and consequently high

expectations of results.

5. They have to basically change their mindset in the way they interact with the

customer. They have to move from a relationship driven by price to a bonded

relationship based on a combination of factors, including trust, reciprocity, loyalty,

concern etc.

LITERATURE REVIEW


Hence summarizing the literature review section, we started with looking into the

characteristics of customer focused organizations and the need for them to improve

customer satisfaction. In the Indian telecom context, the assessment of customer

satisfaction is done by the regulator, TRAI. But the telecom service providers cannot retain

satisfied customers only through improving service quality. They need to change the

perception of these customers and build strong relationships. Research shows that CRM is

an effective strategy to improve service quality, satisfy customers and build long-term

relationships.

Chapter 3

Theoretical

background

THEORETICAL BACKGROUND


3 THEORETICAL BACKGROUND

The theoretical background discusses about the theory of analytical tools used for

explaining the concept of customer focus and customer satisfaction, which have been used

in analysis and findings of the study.

3.1 SWOT Analysis (Strengths, Weaknesses, Opportunities, Threats)

According to Kotler et al. [15]

, the overall evaluation of a company‘s strengths, weaknesses,

opportunities, and threats is called SWOT analysis. It involves monitoring the external and

internal business environment. They have divided the analysis into the following two parts.

SWOT analysis has been used in the study to discuss the strengths and weakness of a

telecom service provider in its ability to compete in the telecom sector and in providing

QoS contributing to overall satisfaction for customers.

3.1.1 External environment (opportunity and threat) analysis

A business unit has to monitor the key macro environment forces like demographic,

cultural, technological forces etc and significant microenvironment actors like customers,

competitors, suppliers etc. that affect its ability to earn Profits. The business should set up a

marketing intelligence system to track trends and important developments. For each event

or development management needs to identify the associated opportunities and threats.

An opportunity is an area of buyer need and interest in which there is a high probability that

a company can profitably satisfy that need. There are three main sources of market

opportunities. The first is to supply something that is in short supply, the second to supply

an existing product or service in a new or superior way, the third source often leads to a

totally new product or service.

An environmental threat is a challenge posed by an unfavourable trend or development that

would lead, in the absence of defensive marketing action to lower sales or profit. Threats

should be classified according to seriousness and probability of occurrence.



3.1.2 Internal environment (strengths/weaknesses) analysis

Each business needs to evaluate its internal strengths and weaknesses. This does not mean

that the business needs to correct all its weaknesses nor should it harp about the strengths it

possesses. The business has to consider about limiting itself to those opportunities where it

possesses strengths or whether it should consider opportunities where it might have to

develop certain strengths.

Stalk et al. [24]

suggest that winning companies are those that have achieved superior in-

company capabilities. Although each department may possess specific core competencies

the challenge for the business is to develop superior competitive capability in managing

company's key processes.

Thus we arrive at the need and use of SWOT analysis for the business. It provides us with a

competitive analysis of the business. We also have to look at other analysis techniques used

for study.

3.2 Oneway ANOVA Test

Oneway ANOVA test helps us in comparing the satisfaction levels between different

groups, thus contributing in proving whether satisfaction levels are similar or homogeneous

across the groups.

According to Joaquim P. Marques de Sá [20]

, ANOVA or analysis of variance is the test of

hypothesis that three or more means are the same or not. It produces an F-statistic that

compares the amount of systematic variance in the data to the amount of unsystematic

variance in the data. It is done by producing a one-way analysis of variance for a

quantitative dependent variable by a single factor (independent) variable. This technique is

an extension of the two-sample t test.

The assumptions made are each group is an independent random sample from a normal

population. Analysis of variance is robust to departures from normality, although the data

should be symmetric. The groups should come from populations with equal variances. To

test this assumption, we use Levene's homogeneity-of-variance test.



In addition to determining the differences existing among the means, we can also know

which means differ. Post hoc range tests and pair wise multiple comparisons can determine

which means differ. Range tests identify homogeneous subsets of means that are not

different from each other. Pair wise multiple comparisons test the difference between each

pair of means and yield a matrix where asterisks indicate significantly different group

means at an alpha level of 0.05.

Tukey‘s test uses the Studentized range statistic to make all of the pair wise comparisons

between groups. It provides a homogeneous set of means which are significantly not

different. Games-Howell test is a pair wise comparison test that is sometimes liberal. This

test is appropriate when the variances are unequal.

Thus using Oneway ANOVA we will be able test for the equality of satisfaction scores

given by different populations. It will help us finding if the population characteristic of

satisfaction is similar across the country.

3.3 Factor analysis

The study uses factor analysis to reduce the number of variables affecting overall

satisfaction into factors which can explain the underlying behaviour of overall satisfaction.

According to SPSS also known as Statistical Package for Social Sciences [23]

, Factor

analysis attempts to identify underlying variables, or factors, and that explain the pattern of

correlations within a set of observed variables. Factor analysis is often used in data

reduction to identify a small number of factors that explain most of the variance that is

observed in a much larger number of manifest variables. Factor analysis can also be used to

generate hypotheses regarding causal mechanisms or to screen variables for subsequent

analysis (for example, to identify co-linearity prior to performing a linear regression

analysis).

The assumptions made are that the data should have a bivariate normal distribution for each

pair of variables, and observations should be independent. The factor analysis model

specifies that variables are determined by common factors (the factors estimated by the

model) and unique factors (which do not overlap between observed variables); the



computed estimates are based on the assumption that all unique factors are uncorrelated

with each other and with the common factors.

The method used is Principal Components Analysis. It is a factor extraction method used to

form uncorrelated linear combinations of the observed variables. The first component has

maximum variance. Successive components explain progressively smaller portions of the

variance and are all uncorrelated with each other. Principal components analysis is used to

obtain the initial factor solution.

Scree plot is the plot of the variance that is associated with each factor. This plot is used to

determine how many factors should be kept. Typically the plot shows a distinct break

between the steep slope of the large factors and the gradual trailing of the rest (the scree).

Varimax Method is an orthogonal rotation method that minimizes the number of variables

that have high loadings on each factor. This method simplifies the interpretation of the

factors.

Thus using factor analysis we will able to find the underlying factors behind the satisfaction

of customers from telecom services. Using these factors we can be able to build a model for

satisfaction from telecom services.

3.4 Multivariate regression analysis

Multivariate regression analysis has been used in the study to find the relationship between

factors affecting overall satisfaction and the overall satisfaction level.

According to Field [10]

, Linear Regression estimates the coefficients of the linear equation,

involving one or more independent variables that best predict the value of the dependent

variable.

The assumptions for using this analysis are that for each value of the independent variable,

the distribution of the dependent variable must be normal. The variance of the distribution

of the dependent variable should be constant for all values of the independent variable. The

relationship between the dependent variable and each independent variable should be linear,

and all observations should be independent.



The R squared change value is produced by adding or deleting an independent variable. If

the R2 change associated with a variable is large, that means that the variable is a good

predictor of the dependent variable.

Thus using regression analysis we will able to build the customer satisfaction model based

on the factors found earlier.

Chapter 4

METHODOLOGY AND

DESIGN OF STUDY

METHODOLOGY AND DESIGN OF STUDY


4 METHODOLOGY AND DESIGN OF STUDY

4.1 Research design for the study

This study is an attempt to understand the customer focus orientation of telecom operators

towards the retail customer by finding out their customer service initiatives and the end

consumer‘s perception about the service quality offered. The study is basically exploratory

in nature. The objective of exploratory research is to explore or search through a problem or

the situation to provide insights and understanding.

The study uses the survey reports from TRAI on customer perception of service. The TRAI

data describes customer satisfaction across providers and the nation. The study is also

conducting a survey among customers to find out the satisfaction levels from the services of

the telecom companies, and if it matches with the findings of the survey reports of TRAI.

CRM solutions and analytics will be used for enhancing customer focus of telecom

companies by enabling them to provide better customer service and overall experience.

The data consists of quantitative as well as qualitative data. Survey has been used as a

research instrument for the study. Many researchers state that quantitative research based

on survey is an appropriate research method because it provides economy of design by

being able to reach out to a larger population and allows rapid turnaround in data collection.

Survey requires standardized information from or about the subjects being studied.

(Subjects might be individuals, groups, organisations, projects or systems). It helps in

generating information that can be projected to the whole population using a representative

sample.

The data collected will be used in the form of statistical information, for the calculation of

satisfaction scores of customers. The data collected from the Quality of Service (QoS)

survey reports by TRAI will also be used to identify the causes of success or failure of

customer focus initiatives of telecom companies.

The step wise design adopted for the study is described in the following sections.



4.2 Data collection

Structured online questionnaire will be web-hosted and made available to all the

respondents in the country. The questionnaire consists of different factors of service quality

of telecom services, established by TRAI. The questions asked mainly elicit satisfaction of

customers with the present services offered to them.

The major sources of secondary data are the TRAI‘s QoS survey reports, various journals,

government reports and policies, research articles, newspaper reports and the internet. The

two approaches of using primary data and secondary data helped in getting a clear

understanding of the situation.

4.3 Survey construction

4.3.1 Sampling plan

The sample plan for the study involves the following decisions to be taken. The researcher

has used non probability convenience and snowball sampling as sampling method. This is

due to the time and cost constraints involved with the study. The survey will be web-hosted

and made available for all to respond. It has been spread through word of mouth. The

respondents represented various parts of the country to present the perceptions of customers

from all parts of the country.

4.3.2 Questionnaire design

The questionnaire is designed to find out from the customers about their perception of the

service quality provided by the telecom operators. It is based on the TRAI‘s QoS survey

questionnaire. The questions consist of a combination of open and closed end questions.

The type of closed ended questions used are scaled, multiple choice and yes/no questions.

The questionnaire was divided into the following parts:

Personal information

In this part general information about the respondents is collected like:



Name of the respondent, Age of the respondent, Gender, Occupation, Telecom operator,

Area (Metropolitan/Rural/Semi-urban/Urban), User type (Prepaid/Postpaid), Technology

type (GSM/CDMA)

Service provision

It consists of questions regarding the point of sale experience of customers regarding the

services provided by the telecom operators.

Prepaid billing

It consists of questions regarding the perception of customers about the pricing of services

by the telecom operators.

Postpaid billing

It consists of questions regarding the perception of customers about the different aspects of

bills and the bill-related complaint resolution process.

Customer care

It consists of questions regarding the customer services provided by the telecom operators,

the general complaint resolution process and the problem solving ability of customer

representatives.

Network performance

It consists of questions regarding the network performance, reliability, availability and

maintainability of the network of the telecom operators.

Value added services

It consists of questions regarding the value added services provided by the telecom

operators.

Overall customer satisfaction



It has questions to gauge the overall satisfaction of customers from the telecom services.

General information

It has general questions regarding different statutory services to be provided by the telecom

operators under the regulations of the industry.

4.3.3 Scale construction

For scaled questions used in the questionnaire, the non-comparative scaling technique of

Likert scale consisting of a 5 point satisfaction scale is used.

The 5 point scale is used to avoid the following problems:

An even number of points may force a commitment, while odd number of points

permits respondents to adopt a neutral position.

―Floor‖ or ―ceiling‖ effect is avoided. In this phenomenon, subjects tend to choose

responses that cluster at either the top or bottom of any scale. As a result of this

clustering, the instrument may not capture a significant amount of the true

variability in opinion among respondents.

The scale is observed for reliability, generalizability, and validity. To validate the scale, the

scale must properly represent the psychological construct of the customer which has been

captured in the range of ‗very satisfying‘ to ‗very dissatisfying‘, so as to draw accurate

theoretical conclusions using such instruments. For reliability, the scale being modified

from TRAI‘s QoS survey validates that the responses can be consistent in giving same kind

of results. To be able to generalize the responses across the population, the secondary data

from TRAI‘s QoS survey has been used to show that customer satisfaction across the

country is fairly homogeneous in nature.

4.4 Tools used for the study

Online web hosting is used as the tool for administering the questionnaire to the various

respondents. The web site used was http://www.surveygizmo.com.

http://en.wikipedia.org/wiki/Reliability_%28psychometric%29

http://en.wikipedia.org/wiki/Validity_%28psychometric%29



4.5 Treatment of data

The raw data collected from questionnaires is suitably tabulated to make statistical

inference. The data is analysed using:

Microsoft Excel, and

SPSS ( Statistical Package for Social Sciences)

From the responses, suitable information is extracted, analyzed, tabulated and illustrated

using factor analysis, regression analysis and other tools. Various tables and graph obtained

by using Microsoft Excel and SPSS have been used for drawing inferences and make

suggestions thereupon.

The satisfaction scores have been represented in the following way based on the

methodology followed by the surveys conducted by TRAI:-

4.5.1 Weighted satisfaction scores

Overall weighted satisfaction score is ascertained using the following formula(s):

Mean score = A/N

Where:

A = (No of subscribers who have given a rating of very satisfied X 5 + No of subscribers

who have given a rating of satisfied X 4 + No of subscribers who have given a rating of

neutral X 3+ No of subscribers who have given a rating of dissatisfied X 2+ No of

subscribers who have given a rating of very dissatisfied X 1)

N=Total sample size achieved

Overall weighted satisfaction score = {(Mean score-1)/4} X100

Thus, if all customers are very satisfied, the operator can get a score of 100%. On the other

hand, if all the customers are very dissatisfied, the operator gets a score of 0%. Thus, the



scale has been calibrated to range between 0% and 100%. The satisfaction benchmarks

have been compared against weighted satisfaction scores.

Chapter 5

ANALYSIS AND

FINDINGS

ANALYSIS AND FINDINGS


5 ANALYSIS AND FINDINGS

5.1 Questionnaire analysis

The survey population consists of mobile/cell phone users. The questionnaire has been

attempted by 196 respondents of which 109 responses were complete and deemed usable.

5.1.1 Demographic profile of respondents

1. Age: the table and graph clearly depict that the majority of the respondents were in the

age group of 0-35 years. Therefore majority of sample population was young.

Figure ‎5-1: Age profile of respondents for the survey

Table 1: Summary of age profile of respondents for the survey

Summary

Value Count Percent %

0-25 years 62 57%

25-35 years 43 39%

35-50 years 3 3%

50 years and above 1 1%



2. Gender: the majority of respondents were male clearly depicted by the pie chart and

table.

Figure ‎5-2: Gender profile of respondents for the survey

Table 2: Summary of gender profile of respondents for the survey

Summary


Male 81 74%

Female 28 26%

3. Occupation: most of the respondents were employed (57%) or student (41%). This

represents the dominant customer base for the wireless telecom services.

Figure ‎5-2: Occupation profile of respondents for the survey



Table 3: Summary of occupation profile of respondents for the survey

Summary


Employed 62 57%

Student 45 41%

Self employed (Business owner) 2 2%

4. Operator: 41% of the respondents were subscribers of Airtel while 30% were using

Vodafone. The other important operators whose subscribers responded for the survey are:

BSNL (7%), Reliance Communications (6%), Tata Teleservices (6%), Idea Cellular (3%)

and others (7%). This is clearly depicted in the pie-chart as well as the table.

Figure ‎5-3: Operator profile of respondents for the survey



Table 4: Summary of operator profile of respondents for the survey

Summary


Bharti airtel 45 41%

Vodafone 33 30%

BSNL 8 7%

Reliance communications 6 6%

Tata tele-services 6 6%

Idea 3 3%

MTNL 2 2%

Reliance telecom 2 2%

Aircel 1 1%

Others (Specify) 2 2%

Spice 1 1%

5. Area: 64% of the respondents belonged to the metropolitan area, while 19% belonged to

urban area. On the other hand, only 11% belonged to semi-urban area and 6% belonged to

rural area.

Figure ‎5-4: Area profile of respondents for the survey



Table 5: Summary of Area profile of respondents for the survey

Summary


Metropolitan 70 64%

Urban 21 19%

Semi-urban 12 11%

Rural 6 6%

6. User type: the majority of the respondents were prepaid (60%), while postpaid

respondents consisted of 40% of the sample.

Figure ‎5-5: User type profile of respondents for the survey

Table 6: Summary of User type profile of respondents for the survey

Summary


Prepaid 65 60%

Postpaid 44 40%



7. Technology type: the majority of the respondents were using the GSM phones (85%) of

telecom operators highlighting the popularity as well as market share of GSM technology

compared to CDMA technology.

Figure ‎5-6: Technology type profile of respondents for the survey

Table 7: Summary of Technology type profile of respondents for the survey

Summary


GSM 92 85%

CDMA 16 15%

We are analysing the survey and TRAI data by first looking at the overall satisfaction levels

of the customers found from the survey. To find the overall satisfaction levels we need to

see if customers across the telecom operators have similar satisfaction levels. Than we can

use the satisfaction levels of all the operators and find the average satisfaction levels which

can be projected for the population. Therefore to be able to do this, we need to test the

satisfaction levels between the operators. We use oneway ANOVA test to find out whether

the overall satisfaction scores are significantly not different.



5.1.2 Oneway ANOVA on survey data operator-wise

We conduct one way ANOVA for testing whether there is significant difference between

the means of overall quality for different operators from the survey data. Therefore for the

purpose of doing the analysis the selected operators (with sample size in brackets) are

Bharti Airtel (43), Vodafone (33), BSNL (8), Reliance Communications (6), Tata

Teleservices (6), Others (10). These operators have been coded for the purpose of analysis

as ‗Bharti Airtel = 1‘, ‗Vodafone = 2‘, ‗BSNL = 3‘, ‗Reliance Communications = 4‘, ‗Tata

Teleservices = 5‘, ‗Others = 7‘. Therefore we are testing a hypothesis that the group means

for overall quality are significantly equal.

H0: The group means of Bharti Airtel, Vodafone, BSNL, Reliance Communications, Tata

Teleservices and Others are equal.

H1: The group means of Bharti Airtel, Vodafone, BSNL, Reliance Communications, Tata

Teleservices and Others are not equal.

The descriptives of the ANOVA test illustrate the sample size, mean, standard deviation

and standard error of the circles as a group (refer to Table-35 in Appendix).

Levene‘s test is used to find whether the variances between the groups are significantly

different or not. Significance of 0.018 is lesser than 0.05 signifying that at 5% level of

significance, Levene‘s test is significant. Therefore we can say that the variances are

significantly different.

Table 8: Test of homogeneity of variances

OVLQUAL

Levene Statistic df1 df2 Sig.

2.873 5 100 .018

The ANOVA summary table is divided into between group effects and within group effects.

The sum of squares represents the variances from between the group and within the group.

The degrees of freedom is shown in the next column. The mean square present in the next



column is found by dividing the sum of squares by the degrees of freedom. The mean

square represents the average amount of variance present between the groups and within the

groups. The F ratio tells us whether the group means are same or different. Here the value

of 0.844 signifies that there is higher variation within the group means than between the

group means. But the observed significance value of 0.521 is very high compared to the

cut-off of less than 0.05. Hence at 5% significance level we have to accept the null

hypothesis. Therefore we conclude that we have no statistical evidence to reject the null

hypothesis that the group means of Bharti Airtel, Vodafone, BSNL, Reliance

Communications, Tata Teleservices and Others are equal.

Table 9: Oneway ANOVA test results

OVLQUAL

Sum of Squares df Mean Square F Sig.

Between Groups 4.791 5 .958 .844 .521

Within Groups 113.473 100 1.135

Total 118.264 105

Post-hoc analysis helps us in finding whether there are significant differences between the

means. Since the ANOVA proves that there is no significant difference, we do post hoc

range tests and pairwise multiple comparisons to determine which means if any differ. The

Range test like Tukey‘s identifies homogeneous subsets of means that are not different

from each other. Pairwise multiple comparisons test like Games-Howell gives us the

difference between each pair of means and yield a matrix where asterisks indicate

significantly different group means at an alpha level of 0.05.

Games-Howell test shows that at 5% (.05) significance level, shown by the significance

column, the difference between the group means is not significant. Hence we can conclude

them to be similar (refer to Table-36 in Appendix).



Tukey‘s test has identified homogeneous subset of means that are not different from each

other having all the groups present in the same set signifying that the group means are fairly

homogeneous(refer to Table-37 in Appendix).

Here we plot the group means of Bharti Airtel (1), Vodafone (2), BSNL (3), Reliance

Communications (4), Tata Teleservices (5), Others (7) against the aggregate mean scores

for overall quality. This shows that the satisfaction is lower for Reliance Communications

(4) customers after taking into account the variable sample sizes for each operator.

Figure ‎5-7: Plot of overall quality satisfaction means versus telecom operator

Therefore we can conclude that customer satisfaction for all the operators for overall

quality is significantly not different. Therefore we can compile to see a holistic picture of

customer satisfaction across the country. We have compiled this data and compared it with

the TRAI survey data.

But to validate the findings of the survey we need to be able to compare the satisfaction

levels shown by the sample with that of other surveys. Here we use TRAI survey‘s on

assessment of quality of service. TRAI has done comprehensive surveys in each of the

telecom circles in India. Therefore, the satisfaction levels expressed in TRAI surveys can be

considered to be valid for the whole of the country. Now if we want to compare with TRAI



data, we have to compile an average of all the operators to see a satisfaction score

representing India. Therefore we need to test whether the satisfaction level for customers

across the operators is similar. Only then can we group them together. So we conduct a

oneway ANOVA test on TRAI data operator-wise to see whether the overall satisfaction

scores are significantly not different.

5.1.3 Oneway ANOVA on TRAI data operator-wise

We conduct one way ANOVA for testing whether there is significant difference between

the means of overall quality for different operators from the TRAI data. Therefore for the

purpose of doing the analysis the selected operators (with number of circles of operation in

brackets) are Aircel(9), Bharti Airtel (22), BSNL (22), Idea (10), Reliance Communications

(22), Tata Teleservices (19), Vodafone (19), Others (5). These operators have been coded

for the purpose of analysis as ‗Aircel = 1‘, ‗Bharti Airtel = 2‘, ‗BSNL = 3‘, ‗Idea = 4‘,

‗Reliance Communications = 5‘, ‗Tata Teleservices = 6‘, ‗Vodafone = 7‘, ‗Others = 8‘.

Therefore we are testing a hypothesis that the group means for overall quality are

significantly equal.

H0: The group means of Aircel, Bharti Airtel, BSNL, Idea, Reliance Communications, Tata

Teleservices, Vodafone and Others are equal.

H1: The group means of Aircel, Bharti Airtel, BSNL, Idea, Reliance Communications, Tata

Teleservices, Vodafone and Others are not equal.

The descriptives of the ANOVA test illustrate the sample size, mean, standard deviation

and standard error of the circles as a group (refer to Table-38 in Appendix).


different or not. Significance of 0.017 is lesser than 0.05 signifying that at 5% level of

significance, Levene‘s test is significant. Therefore we can say that the variances are




Table 10: Test of homogeneity of variances


2.565 7 117 .017











hypothesis that the group means of Aircel, Bharti Airtel, BSNL, Idea, Reliance

Communications, Tata Teleservices, Vodafone and Others are equal.

Table 11: ANOVA results

ANOVA

OVLQUAL

Sum of Squares Df Mean Square F Sig.

Between Groups .182 7 .026 .417 .890

Within Groups 7.282 117 .062

Total 7.464 124



homogeneous(refer to Table-39 in Appendix).

Here we plot the group means of Aircel (1), Bharti Airtel (2), BSNL (3), Idea (4), Reliance

Communications (5), Tata Teleservices (6), Vodafone (7) and Others (8) against the



aggregate mean scores for overall quality. This shows that the satisfaction is lower for

BSNL (3), Idea (4) and Reliance Communications (5) customers after taking into account

the variable sample sizes for each operator.

Figure ‎5-8: Plot of Operator vs overall satisfaction

5.1.4 Overall customer satisfaction scores from survey

After the testing the survey data and TRAI data across the operators, we can conclude that

they are significantly not different across the operators. Therefore we can compare these

two data sets to see the similarities and dissimilarities (Refer to Table-40 in Appendix).

The satisfaction scores are comparable except for billing, customer care and value added

services categories. In these categories the satisfaction scores from the survey are

comparatively lower than that of the TRAI data. Hence based on this analysis we are

describing the case of Airtel. We have taken the case of Airtel, the leading telecom service

provider for analysing the research objectives. The reasons for using Airtel as a case, is

because it is at the forefront of providing customer focussed solutions. The survey data is

also sufficiently available for Airtel.



5.2 Airtel – A case analysis

5.2.1 Airtel: profile

Bharti Airtel is one of the leading providers of telecom service providers in India. The

company offers mobile, wireline, broadband and DTH services. The company primarily

operates in India and is headquartered in New Delhi. The company recorded revenues of

INR 373,520.8 million during the financial year ending March 2009 showing an increase of

38.3% over the previous year. Its net profits where INR 78,589.5 million for the same time

period, showing an increase of 22.9% over the previous year.

Bharti Airtel has three major business divisions: mobile services, telemedia services and

enterprise services division.

The company's mobile services division offers mobile services using GSM technology in all

the major telecom circles of India. It operates under the ‗Airtel‘ brand, and offers prepaid,

postpaid, roaming and value-added services through its sales and distribution channel. It

had over 93 million customers in the wireless segment of the market, thus capturing 24% of

the wireless segment of the overall telecom market in India.

The telemedia services division offers fixed line and broadband services through digital

subscriber line (DSL), direct to home (DTH) TV and IPTV services.

The enterprise services group, including enterprise services carriers and enterprise services

corporate segments, offers a portfolio of services to carrier and large enterprise customers,

respectively.

Bharti Airtel‘s other operations include passive infrastructure services. Bharti Infratel, a

subsidiary of the company, provides passive infrastructure services on a non-discriminatory

basis to all telecom operators in India. Bharti Infratel deploys, owns and manages passive

infrastructure in 11 circles of India. Bharti Infratel also holds 42% share in Indus Towers, a

joint venture between Bharti Infratel, Vodafone and Idea Cellular.

We are focussing on the mobile services division of Airtel in this study, as it is the biggest

segment contributing almost 80% to total revenues of the company. It is also the division



which can make maximum impact on people‘s lives as they are having above 90 million

subscribers.

5.2.2 Partners

According to their official website, the major partners of Bharti Airtel are:

Table 12:‎Airtel’s‎strategic‎partners

Network

Equipment

Network Equipment Nokia Siemens, Ericsson, Huawei

Telemedia & Long

Distance Services

Nokia Siemens, Wipro, Cisco, Alcatel

Lucent, ECI, Tellabs

Information Technology IBM

Call Centre Operations IBM Daksh, Hinduja TMT,

Teleperformance,

Mphasis, Firstsource & Aegis

Equity Partner {Strategic} Singtel

5.2.3 Swot analysis

According to Datamonitor [8]

, Bharti Airtel being in a highly competitive telecom industry

is still the leading provider of telecom services in India. Integrated operations and strategic

partnerships provide a competitive advantage to the company as it allows the company to

control the quality of services delivery and brand offerings. However, increasing

competition in the Indian telecom market could affect its market share in coming years.



Table 13: SWOT analysis of Airtel

Strengths Weaknesses

Integrated operations

Strong brand value

Significant strategic partnerships

Sales and pre-sales

Network performance

VAS

Relatively weak corporate house

Billing

Customer care

Opportunities Threats

Low penetration rates

New services

Expanding presence

Increasing competition

Regulations

Decreasing ARPU

Strengths

Integrated operations: the company is an integrated player by having presence in the

infrastructure, wholesale services, enterprise and customer services etc. areas of the

telecom market. Being an integrated player, the company enjoys the synergies

existing between the different services helping the company in diversifying their

product portfolio and to control the quality of service delivery. For example, the

company launched triple play services with ‗Airtel digital TV interactive‘ providing



telephone, broadband and TV on a single line. The company is also able to benefit

from its presence in all the 23 telecom circles of India by leveraging on its brand

value of providing reliable connectivity all over India.

Strong brand value: the company has a strong brand value, established over a period

of many years. It is evident from the numerous awards and accolades received by it

in recent years. It was ranked second behind LIC as the most trusted brand in the

country, by the Economic Times. It intends to be the Most Admired Brand in India

by 2010. Along with being a trusted and admired brand, they also intend to become

the most Innovative brand in the country, delivering the most exciting and creative

services in all domains.

Significant strategic partnerships: the company has strategic alliances with various

leading industry players. It has a long standing strategic alliance with SingTel,

which has enabled it to further enhance and expand telecommunications network in

India. Its equipment partners include Ericsson, Nokia Siemens and Huawei. Its

technology partners include IBM which has been working closely with the company

to transform IT systems, key business processes and establishing an enterprise

integration platform. Its telephone services and long distance networks equipment

partners include Siemens, Cisco, Wipro and Tellabs, among others. It is also

associated with Nortel, IBM Daksh, Mphasis, Firstsource, Teleperformance, Aegis

and HTMT for providing application servers and interactive applications to enhance

digital lifestyle for its customers. It also works with On Mobile, Comviva, Yahoo,

Google and Cellbrum to provide unique customer experience through dedicated call

center operations. It also has a strategic partnership with Infosys to provide a suite

of products, including devices, experience in the areas of CRBT (caller ring back

tone), Music on Demand, Email services and other Airtel Live applications. It also

has a joint venture with Alcatel Lucent for managed services for its broadband and

fixed line/ telephone services. Strategic partnerships enhance the company‘s ability

to introduce new services and compete effectively.

Sales and pre-sales: they have a strong sales and pre-sales focus. This is evident the

customer satisfaction surveys done by other agencies like voice and data. They have



established thousands of Airtel service outlets which add to the visibility of the

brand.

Network performance: Airtel has also got high customer satisfaction ratings for

network performance. This is evident from its push to have maximum network

towers. The idea of outsourcing the network operations to world-class leaders who

are experienced in managing networks has also helped Airtel in professional

management of the networks.

Value Added Services: Airtel has been at the forefront of providing value added

services and customer satisfaction levels over the years found by voice and data

conform these.

Weaknesses

Relatively weak corporate house: the promoter Bharti Enterprises, has a relatively

weak corporate house image compared to its major competitors. Despite having a

strong brand value for Airtel brand, Bharti Enterprises as a corporate house is

relatively weak compared to its major competitors like Tata Group (Tata

Teleservices), Aditya Birla Group (Idea Cellular) and Anil Dhirubhai Ambani

Group (Reliance Communications). Bharti Enterprise is not a conglomerate.

Companies being part of a conglomerate group would have synergies in various

aspects, including relationship with various agencies, well established distribution

network, cooperation between different units and brand recognition. While, weak

corporate image did not have a negative effect on the company, relatively weak

corporate image could result in competitive disadvantage for the company.

Billing: Airtel hasn‘t been rated well for billing services by customers over the years

found by voice and data.

Customer service: customers are also not happy with the satisfaction from customer

service provided. Voice and data surveys show low ratings for customer satisfaction

from customer service. Therefore we can consider these as weakness upon which

Airtel needs to work.

Opportunities



Low penetration rates: The Indian telecom market is one of the less penetrated

markets in the world having telecom penetration rate of 37% at the end of 2008,

wireless penetration rate of 33.7% and broadband penetration of 0.54%. The low

penetration rates signify potential for growth in coming years. The factors of

increasing urbanization, rising income levels, untapped rural markets and a large

young population is expected to support the growth of the telecom market further.

Airtel being the leading player is in an enviable position to take the market to its

next level of growth.

New services: the company has been introducing various new services in recent

times. In October 2008, it launched direct-to-home (DTH) TV services, digital TV,

in India. In January 2009, it introduced triple play service by launching Airtel digital

TV interactive, an internet protocol (IP) TV service combined with telephone and

broadband. The company‘s new services will allow it to diversify its offerings and

allow it to tap the growth potential of the market.

Expanding presence: the company has been expanding its presence outside India in

recent times. Airtel entered the Sri Lankan market for telecom services in January

2009. The company‘s experience in the Indian market and low cost business model

allowed it to enter Sri Lankan market. Additionally, the company launched the

virtual calling card service in the UK, Singapore and Canada, and calling rate of 1

cent per minute in the US on its online calling card service. The company‘s

expanding presence would diversify its operations and enhance its brand image.

Threats

Increasing competition: The competition in the Indian telecom market is increasing

in recent time owing to expansion of existing players and entry of new players. In

recent times, the market has experienced launch of services in new circles by

existing players and migration to GSM technology by CDMA players. International

players such as Vodafone and NTT DOCOMO also made a direct entry into the

market. NTT DOCOMO entered the market as TATA DOCOMO through an

alliance with Tata Teleservices, a CDMA service provider. Additionally, Tata



Teleservices also launched Virgin Mobile services targeting young generation

through a brand franchise agreement with Virgin Group. Increasing competition

could affect the company‘s market share in coming years.

Regulations: The telecom regulations being handled by the Department of

Telecommunication (DoT) and TRAI are ever increasing in their scope. In recent

times, there have been significant modifications and additions to regulations. The

regulatory changes could affect the company‘s revenues, and may require it to make

changes in organization to adapt to new regulations.

Decreasing ARPU: The telecom service charges in India have been decreasing in

recent times. Despite having one of the world‘s lowest tariffs for local and long

distance calls, the telecom services charges in India continue to fall due to

competitive pressures. As a result, average revenue per user (ARPU) of various

players in India has been decreasing. Although, revenues of telecom players in India

have been growing in recent year due to new customer additions, inability to attract

new customers and retain existing customers would affect the company‘s revenues

and profitability.

5.2.4 Top competitors

The following companies are the major competitors of Bharti Airtel Limited.

Vodafone Group PLC.

Bharat Sanchar Nigam Limited.

Videsh Sanchar Nigam Limited.

Aircel Limited.

Idea Cellular Ltd.

NTT DoCoMo, Inc.

Reliance Communications Ltd.

Tata Communications Limited.

Tata Teleservices (Maharashtra) Limited.

5.2.5 Customer focussed strategies of Airtel

After specifying the strengths, weaknesses, opportunities and threats for Bharti Airtel, we

focus on the specific customer-oriented strategies implemented by them in the recent past.



The customer focussed strategies will give us an idea of where Airtel stands in terms of its

ability to service the customer. The customer focussed strategies of Airtel are:

Rural India focus: The partnerships with IFFCO and Nokia, has led to a huge

transformational impact in rural India with enhanced agricultural productivity and

quality of life. Through the joint venture with IFFCO (IFFCO Kisan Sanchar Ltd.),

they have kicked off a unique initiative to harness the power of telecom to add value

to the farm sector. It provides information on key elements like weather, farming

techniques and commodity rates to the farmers to enhance their productivity.

Another initiative has been the creation of Airtel Service Centres. They already have

around 18,000 of these up and running in villages, enabling them to cater to 400

different languages and dialects. This concept has led to local people serving the

rural customers instead of town and city people.

M-commerce domain: M-commerce is the area of mobile commerce where the

mobile devices are used for conducting transactions. It has developed a solution

called m-Cheque along with partners, where special SIM card is used for financial

transactions replacing the credit card or hard currency. Some of the areas where

Airtel wants to focus are:

o Financial Inclusion: they want to unlock the market of the unbanked people

consisting of 80-85% of population by making the mobile phone act as their

ATM.

o Domestic money-transfer market: they want to offer alternative ways of

money transfer in the domestic market through the use of the mobiles which

have percolated in the market.

o International money transfer: they are planning to work with financial

institutions to speed up the money transfer process and adding value to the

offering by making it pervasive through their 1.2 million retail outlets.

Local city search: it has partnered with Asklaila, India‘s first local information

service, to provide up-to-date information about metro cities, free of cost, from the



extensive city information database for Delhi, Mumbai, Chennai, Hyderabad,

Kolkata and Bangalore.

Enhanced customer experience for platinum customers: it is providing enhanced

customer experience for top-end platinum customers by partnering with IBM Daksh

through process and technology innovation like regional language customer service

etc.

Superior service quality and customer experience: with the mobile services business

contributing 81% to the consolidated revenues of the company. Its prime focus is on

ensuring customer satisfaction through network quality; superior customer service

and continuous innovation in value added services that would help expand its

mobile subscriber base and drive up volumes. Their customer empowerment

strategy has already proved a key differentiator. At the heart of this strategy lies

robust processes that enable customers to change their bill plans or start and stop

services at will, reducing the need for intermediation.

From the customer focussed strategies, we can infer that Airtel is continuously looking for

avenues to improve the overall experience for its customers. But we need empirical

evidence to prove this to be so. Therefore the study uses quantitative and qualitative data

from customer satisfaction surveys done by TRAI as well as survey instrument to find the

customer perception of service quality delivered by Airtel. This data can be used to analyse

whether Airtel has been succeeding in providing superior customer service. Therefore we

first analyse quantitative data to arrive at findings.

5.2.6 Airtel quantitative data analysis

5.2.6.1 TRAI data analysis for Airtel

The telecom regulator TRAI has, under the regulation of ‗Regulation on Quality of Service

of Basic and Cellular Mobile Telephone Services, 2005‘ conducting annually audits and

surveys in all the telecom circles with the help of independent agencies. The surveys have

been conducted regarding the customer perception of the Quality of Service of all the

operators present in a given telecom circle. The results of these surveys provide satisfaction



scores for the sample under various parameters of Quality of service. They are Service

provision, network performance, reliability and availability, maintainability, help services,

billing, supplementary services and overall satisfaction. The following graphs present the

satisfaction scores for the various parameters mentioned above, for telecom operator Airtel,

in all the telecom circles it has presence in, for the years 2001, 2003, 2006, 2007 and 2008-

09.

5.2.6.1.1 Customer satisfaction with the provision of service

Figure ‎5-9: Plot of TRAI data on customer satisfaction with provision of service

From the table (refer to Table-41 in Appendix) we can make out that the customer

satisfaction with provision of service over the time period has decreased comparatively.

This might be for two reasons. Either it might be due to the learning curve of customers,

who have greater expectations or due to lower service quality level of Airtel. The data also

shows that telecom circles like Bihar, Himachal Pradesh (HP), North East (NE) show

drastic decrease in provision of service quality or otherwise pre-sales service. This may be

because the operator might be focusing on the major circles belonging to Metros, Type ‗A‘

and Type ‗B‘ circles which might be having higher ARPU‘s and hence higher revenue

potential. The graphical representation of the same data is given above.

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

CUSTOMER SATISFACTION

TELECOM CIRCLES

CUSTOMER SATISFACTION WITH PROVISION OF SERVICE

TRAI BENCHMARK

2001-02

2003-04

2006

2007

2008-09



5.2.6.1.2 Customer satisfaction with the postpaid billing performance

Figure ‎5-10: Plot of TRAI data on customer satisfaction with postpaid billing

performance

For customer satisfaction from postpaid billing performance, when we see the table (refer to

Table-42 in Appendix) we can find that the satisfaction is far lower recently even though

the TRAI benchmark also is low. The circles of Assam, North east (NE) and HP show very

low satisfaction scores. This shows the lacunae in providing customer service in those

circles. Another observation which can be made is the gradual lowering of satisfaction

scores in most circles from 2006 to 2008. The graphical representation of the data has been

shown below.

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%


TELECOM CIRCLES

CUSTOMER SATISFACTION WITH POSTPAID BILLING PERFORMANCE

TRAI BENCHMARK

2001-02

2003-04

2006

2007

2008-09



5.2.6.1.3 Customer satisfaction with the prepaid billing performance

Figure ‎5-11: Plot of TRAI data on customer satisfaction with prepaid billing

performance

The next table (refer to Table-43 in Appendix) specifies about the prepaid billing

performance across the circles, but a distinct point which can be noted down is that the

customer satisfaction across the states has remained significantly similar while across time

it has gone down drastically. For the year 2006 customer satisfaction levels where in the

range of 90-100% except for two circles. In 2007 the satisfaction levels came down to 80-

90%. And in 2008-09 the satisfaction levels hover in the range of 60-80%. This might

indicate growing customer expectations regarding accuracy of prepaid charges as telecom

operators are always improving in providing this service.

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%


TELECOM CIRCLES

CUSTOMER SATISFACTION WITH PREPAID BILLING PERFORMANCE

TRAI BENCHMARK

2001-02

2003-04

2006

2007

2008-09



5.2.6.1.4 Customer satisfaction with help services

Figure ‎5-12: Plot of TRAI data on customer satisfaction with help services

In case of customer satisfaction with help services (refer to Table-44 in Appendix) or

popularly known as customer care services, we can see a different trend compared to the

previous results. The customer satisfaction levels have remained stagnant over the years

from 2006 to 2008-09. They were at historically low levels from 2006, and still haven‘t

improved until 2008-09 according to customers. Therefore Airtel has a big task in trying to

improve the customer perception of the help services provided by them.

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%


TELECOM CIRCLES

CUSTOMER SATISFACTION WITH HELP SERVICES

TRAI BENCHMARK

2001-02

2003-04

2006

2007

2008-09



5.2.6.1.5 Customer satisfaction with network performance, reliability and availability

Figure ‎5-13: Plot of TRAI data on customer satisfaction with network performance,

reliability and availability

In case of customer satisfaction with network performance, reliability and availability we

can see from the table (refer to Table-45 in Appendix) and the graph as well that the

customer satisfaction level across time period is fairly similar. But the satisfaction levels

show wide disparity across the circles, which have remained so over the years. Circles like

Bihar, Gujarat, Kolkata, Tamil Nadu and West Bengal show customer satisfaction levels

below the TRAI benchmark consistently. Therefore Airtel can go through the TRAI audit

reports on the network performance of its towers to see if the problem is a reality or is the

problem only in the minds of customers. If the problem is first one, than Airtel can look at

improving network performance, while if the problem is the second one, than Airtel can try

to communicate specifically for these sectors about its good network performance.

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%


TELECOM CIRCLES

CUSTOMER SATISFACTION WITH NETWORK PERFORMANCE

TRAI BENCHMARK

2001-02

2003-04

2006

2007

2008-09



5.2.6.1.6 Customer satisfaction with maintainability

Figure ‎5-14: Plot of TRAI data on customer satisfaction with maintainability

Customer satisfaction with maintainability shows that satisfaction levels have remained

pretty stagnant over the years with high satisfaction levels in only some of the circles (refer

to Table-46 in Appendix). But a point to note is the drastic fall in customer ratings given to

Airtel for maintainability from 2006 to 2008-09 in the circles of Bihar (96% to 65%),

Gujarat (88% to 67%), Himachal Pradesh (100% to 66.4%) and Tamil Nadu (100% to

74%). Another point is the very low ratings in the UP West circle consistently over the

period of 4 years. Airtel should seriously take a look at those numbers and design it‘s

strategy.

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%


TELECOM CIRCLES

CUSTOMER SATISFACTION WITH MAINTAINABILITY

TRAI BENCHMARK

2001-02

2003-04

2006

2007

2008-09



5.2.6.1.7 Customer satisfaction with offered supplementary services

Figure ‎5-15: Plot of TRAI data on customer satisfaction with offered supplementary

services

Customer satisfaction with offered supplementary services or popularly known as value

added services shows that the satisfaction levels have come down over the period of 4 years

in all the circles signifying the higher expectations of customers (refer to Table-47 in

Appendix). The only circle showing a problem for Airtel is Himachal Pradesh (HP). They

should take a note of this.

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%


TELECOM CIRCLES

CUSTOMER SATISFACTION WITH OFFERED SUPPLEMENTARY SERVICES

TRAI BENCHMARK

2001-02

2003-04

2006

2007

2008-09



5.2.6.1.8 Customer satisfaction with overall quality of service

Figure ‎5-16: Plot of TRAI data on customer satisfaction with overall quality of service

Figure ‎5-17: Plot of TRAI data on customer satisfaction with overall quality of service

Customer satisfaction with overall quality of service (QoS) provided by Airtel shows

similarities between time periods (refer to Table-48 in Appendix). That is the ratings given

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%


TELECOM CIRCLES

CUSTOMER SATISFACTION WITH OVERALL QUALITY

TRAI BENCHMARK

2001-02

2003

2006

2007

2008-09

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

2001-02 2003 2006 2007 2008-09


YEAR

CUSTOMER SATISFACTION WITH OVERALL QUALITY

OVERALL CSAC SCORE

TRAI BENCHMARK



by customers have remained similar for circles relative to other circles over the time period.

But there are wide differences in terms of ratings given across circles. And the ratings show

a downward trend over the years. Therefore Airtel has to improve overall performance of

its services across the circles, while also giving special attention to circles like Bihar,

Himachal Pradesh, Kolkata, Maharashtra, Mumbai and West Bengal where the ratings

lower relatively.

Through the critical analysis of TRAI survey data of customer satisfaction across the

telecom circles where Airtel has a presence, helps us in considering in detail the problems

associated with service quality related to different factors and different telecom circles. It

gives Airtel the rationale to make specific improvements in specific sectors of service

quality and in specific circles of India to improve overall satisfaction for its customers, as

well as brand image in the minds of its stakeholders.

5.2.6.2 Summarized findings of analysis of TRAI data for Airtel

Pre-sales service quality in Bihar, Himachal Pradesh, North East has gone down

drastically.

Postpaid service quality in Assam, North east and Himachal Pradesh is very low

among customers.

Prepaid service quality has remained stagnant relatively between circles, but the

satisfaction as a whole has come down over the years‘ according to customer‘s

perceptions.

Customer service quality has remained stagnant across the years as well as across

the circles.

Network performance quality in Bihar, Gujarat, Kolkata, Tamil Nadu and West

Bengal has remained below TRAI benchmark consistently over the years. While in

other circles like Andhra Pradesh, Chennai, Karnataka, Kerala, Orissa, Punjab and

Uttar Pradesh (East) network performance quality has remained high consistently.

Maintainability quality has come down in Bihar (96% to 65%), Gujarat (88% to

67%), Himachal Pradesh (100% to 66.4%) and Tamil Nadu (100% to 74%) from

2006 to 2008-09. It has remained low in UP West circle consistently over the period

of 4 years.

Value added services quality has come down across the circles from 2006 to 2008-

09.



Overall quality of service according to customers has come down from 81.83% in

2001 to 70.43%in 2008-09, a change of 11.4% points over 8 years.

Airtel should give special attention to Bihar, Himachal Pradesh, Kolkata,

Maharashtra, Mumbai and West Bengal circles to improve their overall quality

satisfaction scores.

Now to find out specific causes for the problems identified earlier we have conducted a

primary online survey across 196 respondents out of which 109 have responded completely.

The objective of the survey is to find out underlying causes and factors behind the

downward trend of customer satisfaction levels. Out of the 109 respondents, 43 respondents

were Airtel customers. Now, to generalize the findings of the underlying causes for all the

Airtel customers across India, we have to first find out whether the overall satisfaction from

Airtel services is significantly similar across all the telecom circles according to TRAI data.

That is, we have to prove statistically that there is no significant difference between the

overall quality scores given as an aggregate for a circle with that of the other circles where

Airtel has a presence. If we are able to prove the overall quality scores being fairly similar

across the circles, it will imply that the overall quality of services (QoS) provided by Airtel

is perceived to be similar by Airtel customers across India. To prove the above statement

we will conduct Oneway ANOVA test in SPSS on the overall quality satisfaction scores

given by the Airtel customers according to TRAI data. The One-Way ANOVA procedure

produces a one-way analysis of variance for a quantitative dependent variable by a single

factor (independent) variable. Analysis of variance is used to test the hypothesis that several

means are equal.

5.2.6.3 Oneway ANOVA on TRAI data segment-wise

To perform the Oneway ANOVA test the telecom circles have to be divided into

meaningful groups or clusters. Therefore the telecom circles were divided into categories to

find whether there was any significant difference between the overall quality mean scores

of these categories. They were divided according to the classification given by the TRAI.

TRAI has divided the circles based on the income levels of the circles. Therefore the

metropolitan cities are categorized under the type ‗METRO‘ circles. High income states

like Andhra Pradesh, Gujarat and Tamil Nadu are categorized under type ‗A‘ circles.

Middle income states like Kerala, Rajasthan and Haryana have been categorized under type

‗B‘ circles. Low income states like Assam, Bihar, Orissa have been categorized under type



‗C‘ circles. Now these 4 types of circles have been grouped and been coded for conducting

the test. ‗METRO‘ circle consisting of metropolitan cities have coded ‗1‘. In the same way

Type ‗A‘, Type ‗B‘, Type ‗C‘ circles have been coded ‗2‘, ‘3‘, ‗4‘ respectively. Now these

circles coded as numbers 1-4 were named as CODE_I variable. Now these circles coded as

numbers 1-4 were compared with those circles mean aggregate scores for overall quality for

the year 2008-09 named as FOUR_POINT. Therefore we are testing a hypothesis that the

group means are significantly equal.

H0: The group means of METRO, A, B, C circles are equal.

H1: The group means of METRO, A, B, C circles are not equal.

The descriptives of the ANOVA test illustrate the mean, standard deviation and standard

error of the circles as a group.

Table 14: Descriptives of oneway ANOVA test

N Mean Std. Deviation Std. Error

95% Confidence Interval for

Mean

Minimum Maximum Lower Bound Upper Bound

1.00 4 3.1158 .22789 .11394 2.7531 3.4784 2.92 3.43

2.00 5 3.0760 .18542 .08292 2.8458 3.3062 2.86 3.25

3.00 8 3.0754 .14916 .05274 2.9507 3.2001 2.83 3.24

4.00 6 3.1915 .40611 .16579 2.7653 3.6177 2.67 3.90

Total 23 3.1128 .24577 .05125 3.0065 3.2191 2.67 3.90


different or not. Significance of 0.423 is higher than 0.05 signifying that at 5% level of

significance, Levene‘s test is not significant. Therefore we can say that the variances are not

significantly different. Hence we have not violated ANOVA‘s assumption of variances not

being significantly different.



Table 15: Test of Homogeneity of Variances


.980 3 19 .423











hypothesis that the group means of METRO, A, B, C circles are equal.

Table 16: Oneway ANOVA test results


Between Groups .055 3 .018 .274 .843

Within Groups 1.274 19 .067

Total 1.329 22










Table 17: Games-Howell test for post-hoc analysis segment-wise

(I)

CODE_I

(J)

CODE_I

Mean Difference

(I-J) Std. Error Sig.

95% Confidence Interval

Lower Bound Upper Bound

1.00 2.00 .03975 .14092 .991 -.4535 .5330

3.00 .04040 .12556 .987 -.4514 .5322

4.00 -.07575 .20117 .981 -.7218 .5703

2.00 1.00 -.03975 .14092 .991 -.5330 .4535

3.00 .00065 .09827 1.000 -.3221 .3234

4.00 -.11550 .18537 .922 -.7236 .4926

3.00 1.00 -.04040 .12556 .987 -.5322 .4514

2.00 -.00065 .09827 1.000 -.3234 .3221

4.00 -.11615 .17398 .906 -.7178 .4855

4.00 1.00 .07575 .20117 .981 -.5703 .7218

2.00 .11550 .18537 .922 -.4926 .7236

3.00 .11615 .17398 .906 -.4855 .7178


column, the difference between the group means is not significant. Hence we can conclude

them to be similar.



Table 18:‎Tukey’s‎test‎for homogeneous grouping of means

CODE_I N

Subset for alpha = 0.05

1

Tukey HSDa,,b

3.00 8 3.0754

2.00 5 3.0760

1.00 4 3.1158

4.00 6 3.1915

Sig. .881

Means for groups in homogeneous subsets are displayed.

a. Uses Harmonic Mean Sample Size = 5.393.

b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not

guaranteed.



homogeneous.

Figure ‎5-18: Plot of overall quality satisfaction means versus telecom segments



Here we plot the group means of METRO (1.00), A (2.00), B (3.00), C (4.00) circles

against the aggregate mean scores for overall quality in 2008-09. This shows that the

satisfaction is higher in type C circles is compared to other circles significantly.

Hence we are able to conclude that the overall satisfaction from Airtel telecom services

across the country is not significantly different.

5.2.6.4 Oneway ANOVA on TRAI data region-wise

We also conduct oneway ANOVA for testing whether there is significant difference

between the means of overall quality for circles region-wise for the year 2008-09. Therefore

for the purpose of doing the analysis region-wise, the circles have been divided into four

distinct regions. They are North, East, South and West. Those circles which are present in

the northern region of the country according to the Indian political map have been classified

under north category. In the same way the circles have been classified under east, south and

west categories respectively. These categories have been coded for the purpose of analysis

as ‗north = 1‘, ‗east = 2‘, ‗south = 3‘, ‗west = 4‘.These coded regions were named under the

variable called CODE_II, and were compared with the aggregated overall satisfaction

means for these regions for the year 2008-09 named as FOR_POINT. Therefore we are

testing a hypothesis that the group means are significantly equal.

H0: The group means of North, East, South and West circles are equal.

H1: The group means of North, East, South and West circles are not equal.

The descriptives of the ANOVA test illustrate the mean, standard deviation and standard

error of the circles as a group.



Table 19: Descriptives of oneway ANOVA test between telecom regions



Mean


1.00 8 3.1878 .33600 .11879 2.9068 3.4687 2.67 3.90

2.00 6 3.0700 .15531 .06340 2.9070 3.2330 2.86 3.28

3.00 5 3.2346 .11961 .05349 3.0860 3.3831 3.11 3.43

4.00 4 2.8750 .03873 .01936 2.8134 2.9366 2.83 2.92

Total 23 3.1128 .24577 .05125 3.0065 3.2191 2.67 3.90


different or not. Significance of 0.453 is higher than 0.05 signifying that at 5% level of

significance, Levene‘s test is not significant. Therefore we can say that the variances are not

significantly different. Hence we have not violated ANOVA‘s assumption of variances not

being significantly different.

Table 20: Test of Homogeneity of Variances


.915 3 19 .453







of 2.320 signifies that there is higher variation between the group means than within the






hypothesis that the group means of North, East, South and West circles are equal.

Table 21: Oneway ANOVA test results between telecom regions


Between Groups .356 3 .119 2.320 .108

Within Groups .973 19 .051

Total 1.329 22








Table 22: Games-Howell test for post-hoc analysis for telecom regions

(I)

CODE_I

I

(J)

CODE_I

I

Mean Difference




1.00 2.00 .11775 .13465 .818 -.2915 .5270

3.00 -.04681 .13028 .983 -.4497 .3560

4.00 .31275 .12036 .123 -.0805 .7060

2.00 1.00 -.11775 .13465 .818 -.5270 .2915

3.00 -.16456 .08295 .262 -.4237 .0946

4.00 .19500 .06629 .094 -.0358 .4258

3.00 1.00 .04681 .13028 .983 -.3560 .4497

2.00 .16456 .08295 .262 -.0946 .4237



4.00 .35956* .05689 .006 .1497 .5694

4.00 1.00 -.31275 .12036 .123 -.7060 .0805

2.00 -.19500 .06629 .094 -.4258 .0358

3.00 -.35956* .05689 .006 -.5694 -.1497

*. The mean difference is significant at the 0.05 level.


column, the difference between the group means is not significant, except for between 3

and 4 denoting the South and West regions (Significance value of 0.006) . Hence we can

conclude them to be similar, except the relationship between the south and west regions

where the means for overall quality are significantly different.

Table 23:‎Tukey’s‎test‎for‎grouping‎of‎homogeneous‎means‎of‎telecom‎regions

CODE_I

I N

Subset for alpha

= 0.05

1

Tukey HSDa,,b

4.00 4 2.8750

2.00 6 3.0700

1.00 8 3.1878

3.00 5 3.2346

Sig. .075



b. The group sizes are unequal. The harmonic mean of

the group sizes is used. Type I error levels are not

guaranteed.





homogeneous.

Here we plot the group means of North (1.00), East (2.00), South (3.00), West (4.00) circles

against the aggregate mean scores for overall quality in 2008-09. This shows that the

satisfaction is lower in western region compared to other regions significantly.

Figure ‎5-19: Plot of telecom regions versus the overall satisfaction score means

Hence through test based on differentiation of circles according to their income levels and

the regions they belong to, we conclude that overall satisfaction from Airtel telecom

services is significantly not different across the country.

5.2.6.5 Results of survey data

After concluding that the satisfaction from telecom services to be homogeneous, we

compare the satisfaction scores of the survey data with that of the TRAI data consolidated

for the country.



5.2.6.5.1 Demographics of Airtel customers’ participation in the survey:

The demographic characteristics of the Airtel customers‘ who participated in the survey are:

1. Age

Figure ‎5-20: Age profile of Airtel respondents

2. Gender

Figure ‎5-21: Gender profile of Airtel respondents

0-25 years51%

25-35 years47%

50 years and above

2%

Male72%

Female28%



3. Occupation

Figure ‎5-22: Occupation profile of Airtel respondents

4. Area

Figure ‎5-23: Area profile of Aitel respondents

Student35%

Employed63%

Self employed (Business owner)

2%

Metropolitan77%

Urban7%

Semi-urban11%

Rural5%



5. User type

Figure ‎5-24: User type profile of Airtel respondents

We have shown the results of the compounding of the satisfaction scores for all the various

parameters being measured under the Quality of Service (QoS) for Airtel services given by

the formula discussed in the methodology. This has been compounded with the aggregated

TRAI results for the year 2008-09 across all the circles (refer to Table-49 in Appendix).

This result gives us insights into specific areas for Airtel to concentrate on:

They should concentrate on improving their customer care services and value

added services.

In customer services, they should specifically try to improve their processes of ease

of access of the customer representatives for the customers.

They should also try to improve the time to respond to query process, problem

solving ability of the customer representatives and the time to resolve complaint

processes.

In value added services and other supplementary services they should specifically

look at the VAS charges for providing value for the customers.

Prepaid49%Postpaid

51%



Some of the problems recognized by Airtel customers are satisfaction with

reactivation of accounts, prepaid accuracy charges, postpaid billing complaint

resolution process and network complaint resolution process.

5.2.6.6 Hypothesis testing on TRAI data and survey data

After establishing that the aggregate satisfaction scores given for overall quality by

customers for Airtel across all telecom circles for 2008-09, to be fairly homogeneous

statistically, we have to test the hypothesis whether the weighted mean for overall quality

from the survey is significantly different from the weighted mean of overall quality given

for all the circles from the TRAI data.

H0: The means of overall quality from survey and TRAI data (2008-09) are equal.

H1: The means of overall quality from survey and TRAI data (2008-09) are not equal.

To test the hypothesis a One Sample T-Test was done on the data. The means of all circles

for overall quality was compared with the observed survey mean for overall quality of 3.88

out of 5. The statistics of the means of all the circles is given below.

Table 24: One sample Statistics

N Mean Std. Deviation Std. Error Mean

SCORES 22 3.8164 .33454 .07132

The results of the test show a significance value of 0.382 which leads us to accept the null

hypothesis at 5% (0.05) significance level. Therefore we accept the null hypothesis that the

means of overall quality from survey and TRAI data (2008-09) are equal.



Table 25: One sample T test on overall quality satisfaction scores between survey data

and TRAI data

One-Sample Test

Test Value = 3.88

t df Sig. (2-tailed) Mean Difference

95% Confidence Interval of the

Difference

Lower Upper

SCORES -.892 21 .382 -.06364 -.2120 .0847

Therefore from this test we are able to statistically prove that the sample mean for overall

quality from the survey and sample mean for overall quality for all the circles from TRAI

data for 2008-09 are significantly not different. So we can conclude that the sample mean of

survey data for overall quality can be a representative for the Airtel‘s customer population

in India.

5.2.6.7 Factor and multivariate regression analysis on survey data

We have been able to compare sample mean on overall quality from survey data with that

of the TRAI data. Therefore we have been able to establish that the sample mean for overall

quality is statistically equal to that of the means for overall quality for all the telecom

circles. Therefore the answers and values found from the survey can be generalized for the

Airtel customers‘ population of India. Now we did a factor analysis of the satisfaction

scores given to all aspects of Quality of Service (QoS) by Airtel customers. Factor analysis

is useful when we measure several variables, then the correlation between each pair of

variables can exist. The existence of clusters of large correlation coefficients between

subsets of variables suggests that the variables could be measuring aspects of the same

underlying dimension. These underlying dimensions are known as factors (or latent

variables).

Now we have done the Factor analysis for postpaid and prepaid customers separately due to

the influence of the user type on usage characteristics. Another reason for doing this is the



use of prepaid and postpaid billing sections in the questionnaire. Since these sections were

mutually exclusive for postpaid and prepaid customers, there were significant blank

answers in the section of postpaid billing for prepaid customers and vice versa.

5.2.6.7.1 Factor analysis of Airtel postpaid customers

The correlation between the variables as a whole is not positive. Therefore the KMO test of

sampling adequacy and Bartlett‘s test of sphericity have not been given. The communalities

show the proportion of common variance within a sample. Therefore we can say that

extraction column tells us the amount of variance which is shared by other variables as well

(refer to Table-50 for Descriptive Statistics and Table-51 for Communalities in Appendix).

Now the factor extraction method identifies the factors. The criterion to select factors is

based on values having Eigen values above 1. Therefore we are extracting the 7 factors

which are having eigen value of greater than 1 which explain 83.64% of variance observed

among the variables (refer to Table-52 in Appendix).

The scree plot gives the eigen values of each of the factors. From the graph we can make

which factors contribute to the variance the most. The first five contribute the most to

variance exhibited by the variables.

Figure ‎5-25: Plot of Factors extracted versus the eigen values for Airtel postpaid

customers



Now the Rotated Component matrix (refer to Table-54 in Appendix) gives us final

variables present under each of the factors and which are highly uncorrelated between the

factors but highly correlated within each factor. Those variables which have very high

values compared to others (above 0.6) for each factor are used to explain the factors.

Based on the table we describe each factor below. They are:

1. Factor 1: These variables represent the network and billing requirements of the

customers. So if customers have rated these variables closely, than the process of

satisfaction from these services might be similar for Airtel. So this factor can be

named as ‗Network and billing requirements or critical requirements‘.

Availability of network signal in locality.

Ability to make or receive calls easily.

Availability of network signal when on the move.

Clarity of the bills in terms of transparency and understandability.

Ability to make or receive calls/SMS during peak hours.

Accuracy of the postpaid bills.

2. Factor 2: This factor consists of variables related to value added services (VAS) and

customization of offers. Therefore postpaid customers might perceive customization

to be an important requirement for them. Therefore we can name this factor as

‗VAS and Customization requirements‘.

Value added services can be customized for usage requirements.

Present process of resolving customer complaints.

Quality of the value added services provided.

Tariff plan can be customized for usage requirements.

3. Factor 3: This factor consists of variables related to the aspect of postpaid billing.

Therefore we can name this factor as ‗Billing and payment requirements‘.

Payment process for the bills.

Bill payment options can be customized for usage requirements.

Timely delivery of the bills.




4. Factor 4: This factor consists of variables related to customer service. Therefore we

can name this factor as ‗Customer service requirements‘.

Time taken by the customer care to resolve complaint.

Problem solving ability of the customer care executive(s).

5. Factor 5: This factor consists of variables related to areas with which customers are

generally dissatisfied, giving rise to higher overall dissatisfaction (See table ‗results

of survey data‘). Therefore we can name this factor as ‗Satisfaction requirements‘.

Process of resolution of billing complaints.

Charges of value added services.

6. Factor 6: This factor consists of variables related to areas with which customers are

generally satisfied, giving rise to higher overall satisfaction (See table ‗results of

survey data‘). Therefore we can name this factor as ‗Delight requirements‘.

Time taken to respond to call by a customer care executive.

Voice quality.

7. Factor 7: This factor consists of variables which don‘t seem to be related. Therefore

this factor can be named as ‗Network and pre-sales requirements or extra

requirements‘.

Complete process of acquiring the mobile phone connection.

Ability of the service provider to resolve problems related with the network signal.

Therefore based on factor analysis the factors which affect Airtel‘s postpaid customers‘

perception of service quality are the following:

Network and billing requirements

VAS and Customization requirements

Billing and payment requirements



Customer service requirements

Satisfaction requirements

Delight requirements

Network and pre-sales requirements

5.2.6.8 Multivariate regression analysis of Airtel postpaid customers

After finding the factors which affect Airtel's postpaid customers we try to build a model to

see how much each of the factors affect the value of overall quality. In this way we will be

able to build a relationship model between the different factors affecting quality of service

based on the perceptions of the end customers. To build the model, we use multivariate

regression analysis on the survey data of Airtel postpaid customers. We have taken the

factors determined in the previous step and found a factor score by taking the mean of the

scores of the variables coming under those factors. These factors scores have been

compared with scores given for overall quality by the Airtel postpaid customers. These

factors are CRITICAL, CUSTOMIZATION, BILLING, CUSTOMER SERVICE,

SATISFACTION, DELIGHT, EXTRA. Descriptive statistics tells us about the mean,

standard deviation and sample size of the variables for the test.



Table 26: Descriptive statistics for regression analysis of Airtel postpaid customers

Mean Std. Deviation N

OVERALL_QUALITY 3.8095 .51177 21

CRITICAL 3.7000 .85460 21

CUSTOMIZATION 3.6229 .75909 21

BILLING 3.8452 .90649 21

CUST_SERVICE 3.3810 .65009 21

SATISFACTION 2.8095 .81358 21

DELIGHT 3.7381 .62488 21

EXTRA 3.7857 .64365 21

The correlation between the variables is shown in the table (refer to Table-55 in Appendix).

The table shows that there are significant positive and negative correlations between the

variables.

The regression model summary table tells us about the value of R2, which is 0.647. The R

square value tells us that 64.7% of the variance in overall quality can be explained by the

regression model consisting of the factors. The adjusted R square gives us some idea of

how well the model generalises for the population.



Table 27: Regression model for Airtel postpaid customers

Model R

R

Square

Adjusted R

Square

Std. Error

of the

Estimate

Change Statistics

Durbin-

Watson

R Square

Change

F

Change df1 df2

Sig. F

Change

1 .804a .647 .457 .37721 .647 3.402 7 13 .027 2.584

a. Predictors: (Constant), EXTRA, SATISFACTION, DELIGHT, BILLING, CUSTOMIZATION, CUST_SERVICE,

CRITICAL

b. Dependent Variable: OVERALL_QUALITY

The ANOVA table gives the value of F-statistic which is 3.402. The value being greater

than one implies that the variance in overall quality explained by the regression model is

greater than the variance explained by residual values. The significance of 0.027 is highly

significant making it very unlikely for the F-statistic to have happened by chance.

Table 28: Oneway ANOVA test on Airtel postpaid customers

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 3.388 7 .484 3.402 .027a

Residual 1.850 13 .142

Total 5.238 20

a. Predictors: (Constant), EXTRA, SATISFACTION, DELIGHT, BILLING, CUSTOMIZATION,

CUST_SERVICE, CRITICAL


Here we have the coefficients for the factors in the equation explaining overall quality. The

regression equation is as follows:



Overall Quality = 1.739 + 0.032 (Network and billing) + 0.269 (VAS and Customization) +

0.208 (Billing) + 0.293 (Customer service) – 0.082 (Satisfaction) – 0.234 (Delight) + 0.076

(Network and pre-sales)

Table 29: Regression model components for Airtel postpaid customers

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

95.0% Confidence

Interval for B Correlations

B

Std.

Error Beta

Lower

Bound

Upper

Bound

Zero-

order Partial Part

1 (Constant) 1.739 .872 1.995 .068 -.145 3.623

CRITICAL .032 .148 .054 .218 .831 -.287 .352 .457 .060 .036

CUSTOMIZATION .269 .139 .400 1.933 .075 -.032 .571 .632 .472 .319

BILLING .208 .115 .369 1.815 .093 -.040 .457 .580 .450 .299

CUST_SERVICE .293 .191 .372 1.530 .150 -.121 .707 .379 .391 .252

SATISFACTION -.082 .126 -.131 -.654 .525 -.355 .190 .089 -.178 -.108

DELIGHT -.234 .150 -.285 -

1.558

.143 -.557 .090 -.007 -.397 -.257

EXTRA .076 .162 .095 .470 .646 -.273 .425 .249 .129 .077

a. Dependent Variable: OVERALL_QUALITY



Customer satisfaction model developed from regression analysis for Airtel postpaid

customers:

Figure ‎5-26: Customer satisfaction model for Airtel postpaid customers

Network and billing

requirements (0.032)

VAS and

Customization


Billing requirements

(0.208)

Customer service


Satisfaction


Network and pre-

sales requirements

(0.076)

CUSTOMER

SATISFACTION

Delight requirements

(0.234)



Now we have two graphs to show that the data chosen for the regression model follows

normal distribution.

Figure ‎5-27: Plot of overall quality satisfaction score means with frequency for Airtel

postpaid customers


for Airtel postpaid customers



5.2.6.9 Factor analysis of Airtel’s prepaid customers:

The correlation between the variables as a whole is not positive. Therefore the KMO test of

sampling adequacy and Bartlett‘s test of sphericity have not been given. The communalities

show the proportion of common variance within a sample. Therefore we can say that

extraction column tells us the amount of variance which is shared by other variables as well

(refer to Table-53 for Descriptive statistics and Table-56 for Communalities in Appendix).

Now the factor extraction method identifies the factors. The criterion to select factors is

based on values having Eigen values above 1. Therefore we are extracting the 5 factors

which are having eigen value of greater than 1 which explain 78.14% of variance observed

among the variables (refer to Table-57 in Appendix).

The scree plot gives the eigen values of each of the factors.

Figure ‎5-29: Plot of Factors extracted versus the eigen values for Airtel prepaid

customers

Now the Rotated Component matrix gives us final variables present under each of the

factors and which are highly uncorrelated between the factors but highly correlated within



each factor. Those variables which have very high values compared to others (above 0.6)

for each factor are used to explain the factors (refer to Table-59 in Appendix).

Based on the table we describe each factor below. They are:

1. Factor 1: This factor consists of variables which are related to customer service

aspects of Quality of Service (QoS). Therefore this factor can be named as

‗Customer care requirements‘.

Time taken by the customer care to resolve complaint.

Time taken to respond to call by customer care executive.

Present process of resolving customer complaints.

Problem solving ability of the customer care executive(s).

Ease of access of call centre/customer care/online website.

2. Factor 2: this factor consists of variables which are related to the ability to make

calls and SMS. Therefore this factor can be named as ‗Call/SMS ability

requirements‘.

Ability to make or receive calls/SMS during peak hours.

Time taken for reactivation.

Availability of network signal when on the move.

Ability to make or receive SMS.

3. Factor 3: this factor consists of variables which are related to the aspects of prepaid

billing. Therefore this factor can be named as ‗Prepaid billing requirements‘.

Overall quality of your mobile service.

Accuracy of the charges, i.e. amount deducted on every usage.




4. Factor 4: this factor consists of variables related to the aspects of value-added

services and other supplementary services. Therefore this factor can be named as

‗VAS requirements‘.

Charges of value added services.

Quality of the value added services provided.

Value added services can be customized for usage requirements.

5. Factor 5: this factor consists of variables related to the aspects of network

performance. Therefore this factor can be named as ‗Network performance

requirements‘.

Ability of the service provider to resolve problems related with the network signal.

Therefore based on factor analysis the factors which affect Airtel‘s postpaid customers‘

perception of service quality are the following:

Customer care requirements

Call/SMS ability requirements

Prepaid billing requirements

VAS requirements

Network performance requirements

These factors help in finding out the latent variables which affect the choices made by the

postpaid and prepaid users while assessing the Quality of service provided by the Airtel.

5.2.6.10 Multivariate Regression analysis of Airtel’s prepaid customers

After finding the factors which affect Airtel's prepaid customers we try to build a model to

see how much each of the factors affect the value of overall quality. In this way we will be



able to build a relationship model between the different factors affecting quality of service

based on the perceptions of the end customers. To build the model, we use multivariate

regression analysis on the survey data of Airtel prepaid customers. We have taken the

factors determined in the previous step and found a factor score by taking the mean of the

scores of the variables coming under those factors. These factors scores have been

compared with scores given for overall quality by the Airtel postpaid customers. These

factors are CUSTOMER CARE, CALL/SMS ABILITY, PREPAID BILLING, VAS,

NETWORK PERFORMANCE. Descriptive statistics tells us about the mean, standard

deviation and sample size of the variables for the test.

Table 30: Descriptive statistics for regression analysis of Airtel prepaid customers

Descriptive Statistics

Mean Std. Deviation N

OVERALL_QUALITY 4.0000 .57735 19

CUST_CARE 3.0842 1.26854 19

CALL_SMS_ABILITY 3.9842 .58997 19

BILLING 3.7368 .77043 19

VAS 3.1895 1.35109 19

NETWORK_PERF 3.0000 1.45297 19

The correlation between the variables is shown in this table. The table shows that there are

significant positive and negative correlations between the variables (refer to Table-60 in

Appendix).

The regression model summary table tells us about the value of R2, which is 0.744. The R

square value tells us that 74.4% of the variance in overall quality can be explained by the

regression model consisting of the factors. The adjusted R square gives us some idea of

how well the model generalises for the population.



Table 31: Regression model for Airtel prepaid customers

Model Summaryb

Model R

R

Square

Adjusted R

Square

Std. Error

of the

Estimate

Change Statistics

Durbin-

Watson

R Square

Change

F

Change df1 df2

Sig. F

Change

1 .862a .744 .645 .34380 .744 7.553 5 13 .002 1.526

a. Predictors: (Constant), NETWORK_PERF, VAS, CALL_SMS_ABILITY, CUST_CARE, BILLING


The ANOVA table gives the value of F-statistic which is 7.553. The value being greater

than one implies that the variance in overall quality explained by the regression model is

greater than the variance explained by residual values. The significance of 0.002 is highly

significant making it very unlikely for the F-statistic to have happened by chance.

Table 32: Oneway ANOVA test on Airtel prepaid customers

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 4.463 5 .893 7.553 .002a

Residual 1.537 13 .118

Total 6.000 18

a. Predictors: (Constant), NETWORK_PERF, VAS, CALL_SMS_ABILITY, CUST_CARE, BILLING


Here we have the coefficients for the factors in the equation explaining overall quality. The

regression equation is as follows:



Overall Quality = 0.95 - 0.096 (Customer Care) + 0.478 (Call/SMS ability) + 0.394

(Billing) + 0.022 (VAS) – 0.034 (Network Performance)

Table 33: Regression model components for Airtel prepaid customers

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

95.0% Confidence

Interval for B Correlations

B

Std.

Error Beta

Lower

Bound

Upper

Bound

Zero-

order Partial Part

1 (Constant) .950 .710 1.338 .204 -.584 2.484

CUST_CARE -.096 .071 -.212 -

1.358

.198 -.250 .057 -.023 -.353 -.191

CALL_SMS_ABILITY .478 .161 .489 2.960 .011 .129 .827 .652 .635 .416

BILLING .394 .123 .526 3.195 .007 .128 .661 .749 .663 .448

VAS .022 .063 .052 .355 .728 -.113 .158 .071 .098 .050

NETWORK_PERF -.034 .062 -.085 -.548 .593 -.167 .099 -.265 -.150 -.077

a. Dependent Variable: OVERALL_QUALITY



Customer satisfaction model developed from regression analysis for Airtel prepaid

customers:

Figure ‎5-30: Customer satisfaction model for Airtel prepaid customers

Customer care


Call/SMS ability


Billing requirements

(0.208)

VAS requirements

(0.293)

Network

performance


CUSTOMER

SATISFACTION



Now we have two graphs to show that the data chosen for the regression model follows

normal distribution.

Figure ‎5-31: Plot of overall quality satisfaction score means with frequency for Airtel

prepaid customers

Figure ‎5-32: Plot of observed overall quality satisfaction score means with expected

values for Airtel prepaid customers



Therefore we can now see the factors for both the prepaid and postpaid customers compare

them to see if there are significantly different factors affecting the overall satisfaction for

both postpaid and prepaid customers.

Table 34: Factors affecting the postpaid and prepaid Airtel customers

POSTPAID FACTORS PREPAID FACTORS

Call/SMS ability Customer service

Billing VAS and Customization

VAS Billing

Network performance Network and pre-sales experience

Customer service Network and billing

Satisfaction

Delight

We can see that most of the factors rank similarly between the two groups. Therefore we

can see that the overall satisfaction which, postpaid and prepaid customers get from

different aspects of mobile services are quite similar.

5.2.7 Airtel qualitative data analysis

After doing the quantitative analysis, we have arrived at frameworks for customer

satisfaction model for Airtel prepaid and postpaid users. Now we analyse some of the

qualitative aspects of the data to find out insights about the expectations, and behavioural

characteristics of Airtel‘s customers. Therefore we analyse the responses given to the

following questions present in the questionnaire by Airtel customers.

5.2.7.1 Service provision

Q. 8) When did you apply for your latest mobile phone connection?



Figure ‎5-33: Pie chart for time frame of acquisition of service by Airtel respondents

Q. 9) How much time was taken to activate the connection after you applied and completed

the formalities?

Figure ‎5-34: Pie chart for time taken to activate service for Airtel respondents

Table 35: Crosstabulation of time frame of acquisition of service and time taken to

activate service for Airtel respondents

Crosstabulation Time taken for activation

1 day 2-3 days 4-7 days Don't remember total

Applied for mobile service

Less than 6 months 6 0 0 0 6

6-12 months 1 3 1 0 5

Greater than 12 months 14 7 3 0 24

Don't remember 1 0 0 7 8

total 22 10 4 7

Less than 6 months

14%

6-12 months12%

Greater than 12 months/Don't

remember74%

1 day51%2-3 days

23%

4-7 days10%

Don't remember

16%



When we analyse the pie charts and the table above, we see that may be the process used by

Airtel to activate accounts has improved as can be seen in the reduction of time taken for

activation from older users to newer users.

5.2.7.2 Prepaid billing

Q. 13) If you had issues or complaints with prepaid charges deducted, please specify the

reasons for your dissatisfaction?

Figure ‎5-35: Pie chart for issues related with prepaid charges for Airtel respondents

Percentage of sample with issues: 85.71%

This shows that Airtel prepaid customers are not happy with the billing process. There are

many instances where we see that the customers have problems with the balance of money

being deducted from their accounts. This might be due to the inherent nature of prepaid

model that the upper hand in the transaction is with the operator.

5.2.7.3 Postpaid billing

Q. 16) If you had issues or complaints with accuracy of bills, please specify the reasons for

your dissatisfaction?

Charges for calls/services

not made/used34%

Charges not as per plan subscribed

22%

Tariff plan changed

without notice22%

Charged for value-added services not requested

22%



Figure ‎5-36: Pie chart for issues related with accuracy of postpaid bills for Airtel

respondents


Here we can see that the Airtel postpaid customers are more happy with the billing process.

This might be due to the nature of postpaid model, where the customer has the power to pay

the bills only after clarification of such issues.

Q. 26) If you had issues or complaints with the clarity of bills, please specify the reasons?

Figure ‎5-37: Pie chart for issues related with clarity of postpaid bills for Airtel

respondents

Charged for value-added services not requested

34%

Charges for calls/services

not made/used33%

Tariff plan changed without consent

22%

Charges not as per plan

subscribed11%

Payment only at the designated

centers50%

Payment through

internet not available

33%

Payment only during office

hours17%




While Airtel has gone for a revamp, and the present bills are very comprehensive, the

customers‘ are saying that they are still having problems. This might lead us to infer that

Airtel might have to look for newer manner for presenting the bills.

5.2.7.4 Customer care

Q.28) If no, can you specify the reasons for not making a query or filing a complaint with

the customer care service in the last one year?

Figure ‎5-38: Pie chart for reasons for not querying customer care for Airtel

respondents

Percentage of sample having no/small complaints: 64%

This is a very important finding that almost 64% of the sample hasn‘t felt the need to call

up the customer care services. This can lead us to infer that Airtel has been proactive in

providing customer services and minimising dissatisfaction.

5.2.7.5 Value added services

Q. 42) Do you use value added services like roaming, ring tone, GPRS, e-mail, voice mail

or any other such services?

There were small

complaints/Nothing to

complain about73%

The complaint process is too

tedious18%

I don't know the complaint

process9%



Figure ‎5-39: Pie chart for usage of value added services for Airtel respondents

Percentage of sample using value added services: 58.14%

Q. 43) If you don‘t use value added services, please specify the reasons?

Figure ‎5-40: Pie chart for reasons for not using value added services for Airtel

respondents

Percentage of sample who never felt the need for VAS: 70%

This is also an important finding that almost 70% of the sample, who don‘t use value added

services, don‘t feel the need for using value added services. While the operators are bullish

about VAS being the driver of ARPU‘s (average revenue per user) in the future, here is an

insight where the customer doesn‘t need VAS itself. Therefore Airtel has an important

customer segment to tap for growth.

Q. 44) If yes, please specify those value added services which you use most?

Yes61%

No39%

I never felt the need for

it70%

I knew, but the service

charges were not

affordable15%

I knew, but it was very

complicated to try10%

I was never informed by the service provider

5%



Figure ‎5-41: Pie chart for usage of types of value added services for Airtel respondents

This pie chart shows that roaming is still the most important supplementary service required

by customers. Even though they might be using other value added services, for the

customer segment as a whole, roaming is still the most important VAS. Therefore, if Airtel

is able to differentiate it‘s roaming services rather than just pricing it competitively, it will

be able to gain strategic advantage.

Q. 51) Have you been informed in writing, at the time of subscription of service or within a

week of activation of service, the complete details of your tariff plan?

Figure ‎5-42: Pie chart for knowledge about reception of subscription of service details

for Airtel respondents

roaming46%

GPRS/email26%

caller tunes17%

others11%

Yes45%

No55%



This is an important area where Airtel can gain goodwill of customer as well as delight the

customer. If Airtel is able to provide the details of the account plan to the customers after

they subscribe, the customers would get a perception of the operator caring for them.

Some of the other important findings are:

Most customers who call to customer care call regarding value added services, tariff

plan and billing charges.

Suggestions from customers regarding improving the customer complaint resolution

process are mostly towards empowering the customer care executives in solving the

customer‘s problem.

The most important criterion for overall quality of Airtel services is Ability to make

Calls/SMS and the network performance. On this criterion most customers are

satisfied with Airtel‘s services.

The second most important criterion for overall quality of Airtel services is tariff

and billing related aspects. Here there are mixed views among customers.

The third most important criterion for overall quality of Airtel services is the

customer services provided. However an important thing to note is the unnecessary

campaigns which Airtel runs a lot through calls and SMS. It should do target

campaigning more strategically with using Business analytics.

There is still not much awareness (only 21%) about the Do Not Call (DNC) registry

among customers. And those who have registered for DNC still keep receiving

(over 71%) the unwanted calls/SMS. This gives an important insight where Airtel

can focus to provide customer satisfaction. As these can lead to high rate of

customer dissatisfaction leading to higher churn.

5.2.8 Overall Findings of customer’s perception of Airtel’s services:

Finally we summarize overall findings of the data analysis done for Airtel. These findings

give us insights as to where Airtel can improve upon so as improve the Quality of Services



leading to higher satisfaction for customers and in the process making Airtel truly customer

focussed.

Pre-sales service quality in Bihar, Himachal Pradesh, North East has gone down

drastically.

Postpaid service quality in Assam, North east and Himachal Pradesh is very low

among customers.

Prepaid service quality has remained stagnant relatively between circles, but the

satisfaction as a whole has come down over the years‘ according to customer‘s

perceptions.

Customer service quality has remained stagnant across the years as well as across

the circles.

Network performance quality in Bihar, Gujarat, Kolkata, Tamil Nadu and West

Bengal has remained below TRAI benchmark consistently over the years. While in

other circles like Andhra Pradesh, Chennai, Karnataka, Kerala, Orissa, Punjab and

Uttar Pradesh (East) network performance quality has remained high consistently.

Maintainability quality has come down in Bihar (96% to 65%), Gujarat (88% to

67%), Himachal Pradesh (100% to 66.4%) and Tamil Nadu (100% to 74%) from

2006 to 2008-09. It has remained low in UP West circle consistently over the period

of 4 years.

Value added services quality has come down across the circles from 2006 to 2008-

09.

Overall quality of service according to customers has come down from 81.83% in

2001 to 70.43%in 2008-09, a change of 11.4% points over 8 years.

Airtel should give special attention to Bihar, Himachal Pradesh, Kolkata,

Maharashtra, Mumbai and West Bengal circles to improve their overall quality

satisfaction scores.



Overall satisfaction from Airtel telecom services across the country is not


Customer care services and value added services scores from the survey were low

for Airtel services.

In customer services, they should specifically try to improve their processes of ease

of access of the customer representatives for the customers.

They should also try to improve the time to respond to query process, problem

solving ability of the customer representatives and the time to resolve complaint

processes.



Some of the problems recognized by Airtel customers are satisfaction with

reactivation of accounts, prepaid accuracy charges, postpaid billing complaint

resolution process and network complaint resolution process.

The means of overall quality from survey and TRAI data (2008-09) are significantly

not different.

The factors which affect Airtel‘s postpaid customers‘ perception of service quality

are the following:

o Network and billing requirements

o VAS and Customization requirements

o Billing and payment requirements

o Customer service requirements

o Satisfaction requirements

o Delight requirements

o Network and pre-sales requirements



Multivariate regression model for explaining customer satisfaction for Airtel‘s

postpaid customer:

Overall Quality = 1.739 + 0.032 (Critical) + 0.269 (Customization) + 0.208 (Billing)

+ 0.293 (Customer service) – 0.082 (Satisfaction) – 0.234 (Delight) + 0.076 (Extra)

The factors which affect Airtel‘s prepaid customers‘ perception of service quality

are the following:

o Customer care requirements

o Call/SMS ability requirements

o Prepaid billing requirements

o VAS requirements

o Network performance requirements

Multivariate regression model for explaining customer satisfaction for Airtel‘s

prepaid customer:

Overall Quality = 0.95 - 0.096 (Customer Care) + 0.478 (Call/SMS ability) + 0.394

(Billing) + 0.022 (VAS) – 0.034 (Network Performance)

According to the survey, the process used by Airtel to activate accounts has

improved.

Airtel prepaid customers are not happy with the billing process. There are many

instances where we see that the customers have problems with the balance of money

being deducted from their accounts. This might be due to the inherent nature of

prepaid model, where the upper hand in the transaction is with the operator.

Airtel postpaid customers are more happy with the billing process. This might be

due to the nature of postpaid model, where the customer has the power to pay the

bills only after clarification of such issues.



While Airtel has gone for a revamp, and the present bills are very comprehensive,

the customers‘ are saying that they are still having problems. This might lead us to

infer that Airtel might have to look for newer manner for presenting the bills.

Almost 64% of the sample hasn‘t felt the need to call up the customer care services.

This can lead us to infer that Airtel has been proactive in providing customer

services and minimising dissatisfaction.

Almost 70% of the sample, who don‘t use value added services, don‘t feel the need

for using value added services. While the operators are bullish about VAS being the

driver of ARPU‘s (average revenue per user) in the future, here is an insight where

the customer doesn‘t need VAS itself. Therefore Airtel has an important customer

segment to tap for growth.

Roaming is still the most important supplementary service required by customers.

Even though they might be using other value added services, for the customer

segment as a whole, roaming is still the most important VAS. Therefore, if Airtel is

able to differentiate its roaming services rather than just pricing it competitively, it

will be able to gain strategic advantage.

Airtel can gain goodwill of customer by providing the details of the account plan to

the customers after they subscribe. If Airtel is able to provide the details of the

account plan to the customers after they subscribe, the customers would get a

perception of the operator caring for them.

Most customers who call to customer care call regarding value added services, tariff

plan and billing charges.

Suggestions from customers regarding improving the customer complaint resolution

process are mostly towards empowering the customer care executives in solving the

customer‘s problem.

The most important criterion for overall quality of Airtel services is Ability to make

Calls/SMS and the network performance. On this criterion most customers are

satisfied with Airtel‘s services.



The second most important criterion for overall quality of Airtel services is tariff

and billing related aspects. Here there are mixed views among customers.

The third most important criterion for overall quality of Airtel services is the

customer services provided. However an important thing to note is the unnecessary

campaigns which Airtel runs a lot through calls and SMS. It should do target

campaigning more strategically with using Business analytics.

There is still not much awareness (only 21%) about the Do Not Call (DNC) registry

among customers. And those who have registered for DNC still keep receiving

(over 71%) the unwanted calls/SMS. This gives an important insight where Airtel

can focus to provide customer satisfaction. As these can lead to high rate of

customer dissatisfaction leading to higher churn.

Based on the overall findings of the study, we can now see the picture of Airtel‘s

perspective of serving its customer and the customer‘s perspective about Airtel‘s services.

This picture gave us areas for scope of improvement for Airtel. Based on the study of

Customer Relationship Management in the telecom sector in the literature review section,

we will be able to provide suggestions for improving the customer‘s perspective of Airtel‘s

services. Customer Relationship Management is one of the strategies which have to be

used, but it can be used as a strategic lever to provide competitive advantage. The rationale

for using CRM is that telecom being a data-driven industry with the service being provided

through a remote device, gives the operator opportunity to monitor the customer usage

pattern as well as its service delivery in real time without affecting the service. This

environment gives us an ideal opportunity to use Customer management to profitably

acquire new customers as well as retain loyal customers. With the price and product/service

features being quite similar as well as attainable in a short period of time, due to the

technological nature of the industry, the only differentiator for Airtel can be its customer

management strategy. Therefore we provide recommendations/suggestions based on

Customer Relationship Management for Airtel.

Chapter 6

RECOMMENDATIONS

RECOMMENDATIONS


6 RECOMMENDATIONS

6.1.1 Recommendations/Suggestions based on study of CRM for the present

situation of Bharti Airtel

We have analysed the case of Airtel to gain understanding of the situation of the wireless

telecom sector. The knowledge which we have gained from analysis is that Airtel is weaker

in the areas of customer service and value added services. The factors which affect the

Indian customer are predominantly customer service, billing, value added services,

customization, and network performance. This might be lead us to suggest Airtel to focus

on improving in those areas where customers rate Airtel‘s performance lower as well as

affect overall satisfaction considerably. In that manner we will be able to target Airtel‘s

weakness and improve overall satisfaction considerably. Therefore the areas identified to be

addressed using CRM are customer services, value added services, customized services,

customer segmentation based on analytics.

Customer care services

Customer services are an integral part of a service offering as it brings a sense of

assurance that someone is there in case of difficulty. In case of Airtel, has

outsourced its IT systems management to IBM, including customer services. Prior

to this the customer care services were handled by Oracle. Now to make the

outsourcing work on such a huge scale Airtel has created very tight, extremely

detailed Service Level Agreements (SLAs). But still the findings from analysis

show that the customer service satisfaction levels are quite low over the years. This

has been substantiated by TRAI data as well as survey data. The analysis also

proves that customer service is a very important factor in the determinant of overall

satisfaction. So this leads us to question the SLAs designed by Airtel. Are the SLAs

sufficiently ensuring quality of service is the question to be asked. Therefore Airtel

has to design the SLA from two perspectives. One is the actual performance shown

by IBM. The other is the perceived performance by customers of the services which

Airtel has outsourced to IBM. This can validate the actual performance. In this way

Airtel will be able to clear define its customer service strategy and give clear

guidelines for IBM to follow. This is very important because from the analysis we

have been able to find that the biggest weakness according to customers of Airtel is

RECOMMENDATIONS


its customer care services. And customer services have been contributing a lot to the

overall satisfaction scores as found from the analysis. Therefore Airtel has to

redefine its customer service strategy. As part of the customer services strategy,

Airtel can use its website as a strategic tool to service customers as well build

loyalty among the customers. For mobile users, websites aren‘t that important. But

Airtel can personalize and provide more ease of service through use of Airtel

website to help in the processes of billing, customer care, value added services.

Using innovative web 2.0 tools, services, add-ins, applications etc, Airtel can try to

build a community of Airtel users. Therefore Airtel website can act as the change

agent for Airtel in improving its Quality of services. Airtel should also realise the

strategic importance of people. They are the ones who enable all strategies and

make them functional and effective. Therefore Airtel can concentrate on its

employees and use them as strategic assets. It can also use customer care services

which have been outsourced at present, to come under its ambit and use it to provide

superior customer experience for the customer. Analysis shows that customers

mostly are unhappy with the complaint resolution process where customer reps are

not empowered to take desicions. Therefore Airtel has to use assets in the form of

people to communicate the same message across all the touch-points to the

customer.


The concept of value added services is that they should give value to the customers

on top of the communication services provided by the operator. Therefore Airtel has

to use traditional marketing methods like market research techniques to find out

useful value added services which can add value in the daily life of the customers.

Airtel has to look for latent needs which can be fulfil through value added services.

In the study, we have been able to find that Airtel has come up with a lot of value

added services which help people in their daily lives. Some of these are the

initiatives for the rural customers where they provide daily updates, m-Cheque

special SIM cards which help in financial transactions, Asklaila city search. These

value added services are value adding. Even if some of them are not value adding

for improving productivity, they can still be able to fulfil needs of customers. They

can create needs for the customer and market them like in the case of ipod. Findings

RECOMMENDATIONS


from the research point out to that most of the customers who don‘t use VAS, don‘t

feel the need for them. Therefore Airtel has a huge untapped market there to serve

with VAS. And VAS is termed as the engine for revenue growth for all the service

providers. So for Airtel it becomes more important to look at the requirements of

different segments and then target appropriate VAS by developing appropriate

products. Therefore product development also comes into picture here. Airtel also

has to look at the pricing of VAS, because customers are most dissatisfied from the

prices of VAS. This has been substantiated by the analysis of survey. Therefore

Airtel has to look at the tendency of customers to measure the prices of VAS in lieu

with voice charges. Therefore Airtel has to price the VAS carefully.

Customized services

The analysis of results showed us that customers wanted more customized offerings

from Airtel in all aspects of customer service. They are billing, customer care and

value added services. That means customers wanted services which were more in

tune with their needs. Therefore for Airtel it becomes imperative to find out what

personal information the customer wants it to know, so as to better serve the

customer by recommending usage plans which tuned to his/her needs. It must than

seek the customer‘s permission to use this information. The 3 steps it should follow

are:

o Interact: It should talk to customers, establish dialogue and understand their

needs. It should use market research to find out what customers want to be

personalized. While this is obvious, Airtel has to use the strategy of website

as an important component in building a community for Airtel. This will

help Airtel in building loyal customers who are ready to help in Airtel‘s

services and create a feeling of belongingness between them.

o Invent: It should use the data differently than competitors. Airtel has to use

the data it is already having about its customers to personalize the service

which is more meaningful for the customers.

o Personalize: It should personalize uniquely for each customer. For

personalizing they can modify the three levers of Content of the service,

Context of the use and Contact with the customer. Personalization doesn‘t

RECOMMENDATIONS


more costly for the customer. But if Airtel is able to provide customized

solutions using IT as a powerful tool, and then able to communicate this to

customers than Airtel can gain strategic advantage. Airtel also has to target

the segments with personalized content.

Customer retention strategy using churn modelling

Airtel has to articulate its customer retention strategy more clearly. Customer

retention is retaining loyal customers over a period of time so that they create a win-

win relationship for both the parties involved. The most important reason for

investing in retention is, because the cost of acquiring new customers is five times

more than the cost of retaining existing customers. Therefore it makes more sense

for Airtel to go for customer retention strategy than going for customer acquistion.

Therefore the objective is to nurture long-term relationships with customers through

trust, responsiveness, customized services and reliability. Customer care, therefore

has become the most important activity for providing superior customer satisfaction

as established from the analysis.

For articulating the customer retention strategy Airtel has to follow the following

steps:

o They have to analyse the internal data generated from customer usage of

service. They have to look at the activity patterns and needs of the

customers.

o They have to now segment the customers based on historic and real time

data being captured, using data mining tools like clustering into meaningful

segments.

o They have to identify the propensity to churn for each segment. That is the

probability of the customer disabling the services in a given time period.

This can be found out by using reporting tools to analyse characteristics of

customer churn.

RECOMMENDATIONS


o They have to identify the customer profitability in terms of net present value

of the difference between revenue from retaining customer to the campaign

costs.

o They have apply the propensity to churn model and customer profitability

models to the customer segments and then design campaigns which have net

present value of greater than zero.

o They have to than execute these campaigns effectively. While it shows the

importance of technology here. It is not so. The most important aspect are

the people who have to execute the strategies with customer in mind.

Customer segmentation based on analytics

Airtel has to look for new micro-customer segments within the broad segments

taking into account their location and other preferences. To help in the search of

micro segments it has to get a holistic picture of these customers from aspects like

cultural, psychological, behavioural, geographical etc. This can be done through

qualitative techniques as well as using data analytics. While Airtel as well as other

operators are already doing it, it hasn‘t resulted in strategic gains for any of them.

Therefore Airtel has to focus on this aspect. Analysis from the study suggests that

there can be micro segments of customers. This has been substantiated by the

different preferences shown by postpaid and prepaid customers. While the user

profile of the prepaid customer can be seen as younger with higher desires but less

propensity to pay. While the user profile of postpaid customer can be seen as

slightly older with desires but higher propensity to pay. Therefore here Airtel has to

understand customer preferences and than design campaigns specifically for these

micro-segments. Airtel has to use the concept of predictive CRM coming out of

analytical CRM. Predictive CRM is the ability to understand customer preferences,

anticipate customer needs, take proactive steps and deliver at the critical ‗moments

of truth‘ for the customer. This requires overall understanding of the consumption of

telecom service by the customer to provide him a hassle-free customer experience.

CHAPTER 7

CONCLUSIONS

CONCLUSIONS


7 CONCLUSIONS

7.1 Conclusion

The results of this study contribute to the recent, albeit sparse body of literature about

customer focus of wireless telecom industry. In this study we have been able to conclude

the following findings:

Airtel has been considered as a case as it is the leading service provider. It has got

average overall customer satisfaction of 71.95% while having weakness in customer

care services and value added services.

In customer services, Airtel has to look at its strategy of using SLAs to measure

performance of customer services. Therefore Airtel has to look at perceived

performance of customer service given by customers as an important criterion to

measure SLAs.



The factors affecting the overall satisfaction for Airtel‘s postpaid customers are

call/SMS ability, billing, VAS, network performance and customer service.

The factors affecting the overall satisfaction for Airtel‘s prepaid customers are

customer service, VAS and customization, billing, network performance and pre-

sales experience.

Therefore Airtel has to use CRM strategies to help in providing better customer

services and value added services.

Airtel also has to provide customized services using CRM, as customers are ready

for customization of telecom services.

Airtel has to push its utility-based value added services forward like m-cheque,

Asklaila city search etc to create the demand for VAS, as most customers don‘t feel

the need for VAS except roaming.

CHAPTER 8

APPENDIX

APPENDIX


8 APPENDIX

8.1 Questionnaire

Personal information

Note: please mark your response number in the box provided.

Name: __________________________________

Age:

Gender:

Occupation:

Operator:

1 Bharti airtel

2 Aircel

3 Reliance communications

4 Reliance telecom

5 Vodafone

6 Tata teleservices

7 Idea

8 Shyam telelink

9 BSNL

10 MTNL

11 Spice

12 BPL

13 HFCL

14 RISL

15 Dishnet

1 0-25 years

2 25-35 years

3 35-50 years

4 50 years and above

1 Male

2 Female

1 Employed

2 Self employed (Business owner)

3 Student

4 Housewife

5 Retired

APPENDIX


Others (Specify)_______________________________________

Area:

1. Metropolitan: In India, the Census Commission defines a metropolitan city as one

having a population of over 40 lakh (4 million). Mumbai, Delhi, Chennai, Kolkata,

Bengaluru, Hyderabad, Ahmedabad are the seven cities that qualify.

2. Urban: a geographical area constituting a city having a population between 40 lakh

and 1 lakh.

3. Semi-urban: a geographical area constituting a town having a population between 1

lakh and 10000.

4. Rural: An area with low population density such as a village or the countryside

having a population of 10000 or less.

User type:

Technology type:

Service provision

1. When did you apply for your latest mobile phone connection?

2. How much time was taken to activate the connection after you applied and

completed the formalities?

1 Metropolitan

2 Urban

3 Semi-urban

4 Rural

1 Prepaid

2 Postpaid

GSM

CDMA

1 Less than 6 months

2 6-12 months

3 Greater than 12 months

4 Don‘t remember

1 1 day

2 2-3 days

http://en.wikipedia.org/wiki/Republic_of_India

http://en.wikipedia.org/wiki/Mumbai

http://en.wikipedia.org/wiki/Delhi

http://en.wikipedia.org/wiki/Chennai

http://en.wikipedia.org/wiki/Kolkata

http://en.wikipedia.org/wiki/Bengaluru

http://en.wikipedia.org/wiki/Hyderabad,_Andhra_Pradesh

http://en.wikipedia.org/wiki/Ahmedabad

APPENDIX


3. How was the complete process of acquiring the mobile phone connection according

to you?

4. In case you had some problems with the connection, are you satisfied with the time

taken for reactivation?

Prepaid billing (for prepaid users only)

5. How satisfied are you with the accuracy of the charges, i.e. amount deducted on

every usage?

6. If you had issues or complaints with charges deducted, please specify the reasons

for your dissatisfaction?(multiple answers possible)

3 4-7 days

4 Greater than 7 days

5 Don‘t remember

1 Very dissatisfying

2 Dissatisfying

3 Neutral

4 Satisfying

5 Very satisfying

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Charges not as per plan

subscribed

2 Tariff plan changed without

notice

3 Charges for calls/services not

APPENDIX


Others:______________________________________________________

7. How satisfied are you if the tariff plan can be customized for your usage

requirements?

Postpaid billing (for postpaid users only)

Note: Accuracy of bills refers to charges in the bill as per the tariff plan subscribed.

8. How satisfied are you with the accuracy of the postpaid bills?

If your response is Satisfied or Very satisfied, please skip to question 10, otherwise

continue.

9. If you had issues or complaints with accuracy of bills, please specify the reasons for

your dissatisfaction? (multiple responses acceptable)

made/used

4 Charged for value-added

services not requested

5 Others(please specify)

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Charges not as per plan

subscribed

2 Tariff plan changed without

consent

3 Charges for calls/services not

made/used

4 Charged for value-added

services not requested


APPENDIX


Others:______________________________________________________

10. How satisfied are you with the timely delivery of the bills?

11. How satisfied are you with the payment process for the bills?


continue.

12. If you had issues or complaints with the payment process, please specify the reasons

for your dissatisfaction?(multiple answers possible)

Others:______________________________________________________

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Payment only at the designated

centers

2 Payment only through cash

3 Payment only during office

hours

4 Payment through internet not

available


APPENDIX


13. How satisfied are you if the tariff plan can be customized for your usage

requirements?

14. How satisfied are you if the bill payment options can be customized for your usage

requirements?

15. Have you made any billing related complaints in last 12 months?

If no, please skip to question 18, otherwise continue.

16. How many complaints have you made in the last 12 months?

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Yes

2 No

1 0-3

2 4-6

3 7-9

4 10-12

5 12 and more

APPENDIX


17. How satisfied are you with the process of resolution of billing complaints?

18. How satisfied are you with the clarity of the bills issued by your service provider in

terms of transparency and understandability?

If your response is Satisfied or Very satisfied, skip to question 20, otherwise continue.

19. If you had issues or complaints with the clarity of bills, please you specify the

reasons?(multiple answers possible)

Others:______________________________________________________

Customer care

20. Did you complain or make a query in the last 12 months to the customer care toll

free number of your service provider regarding any non-billing complaints?

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Difficult to read the bill

2 Difficult to understand the

language

3 Calculations not clear

4 Item-wise breakdown of charges

not given


1 Yes

2 No

APPENDIX


If yes, please skip to question 22, otherwise continue.

21. If no, can you specify the reasons? (multiple answers possible)

Others:______________________________________________________

22. Please specify the reasons for your response in question no. 20?

1) ___________________________________________________________________

_________________________________________________________________

2) ___________________________________________________________________

_________________________________________________________________

3) ___________________________________________________________________

_________________________________________________________________

23. How satisfied are you with the ease of access of call center/customer care/online

website?

24. How satisfied are you with the time taken to respond to your call by a customer care

executive?

1 Nothing to complain about.

2 There were small complaints.

3 I don‘t know the complaint

process

4 The complaint process is too

tedious


1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

APPENDIX


25. How satisfied were you with the problem solving ability of the customer care

executive(s)?

26. How satisfied were you with the time taken by the customer care to resolve your

complaint?

27. How satisfied are you with the present process of resolving customer complaints by

your service provider?


continue.

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

APPENDIX


28. If you have issues or complaints with the process of resolving customer complaints,

please you specify better solutions? (multiple answers possible)

Network performance

29. How satisfied are you with the availability of network signal of your service

provider in your locality?

30. How satisfied are you with the availability of network signal when on the move?

31. How satisfied are you with the ability of the service provider to resolve problems

related with the network signal?

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

APPENDIX


32. How satisfied are you with the ability to make or receive calls easily?

33. How satisfied are you with the ability to make or receive SMS?

34. How satisfied are you with the voice quality?

35. How satisfied are you with your ability to make or receive calls/SMS during peak

hours?


36. Do you use value added services like roaming, ring tone, GPRS, e-mail, voice mail

or any other such services?

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Yes

2 No

APPENDIX


If yes please skip to question 38, otherwise continue.

37. If no, please you specify the reasons? (multiple answers possible)

Others:______________________________________________________

38. If yes, please specify those value added services which you use most?

1) __________________________________________________________________

2) __________________________________________________________________

3) __________________________________________________________________

4) __________________________________________________________________

5) __________________________________________________________________

39. If yes, did the service provider get your explicit consent for providing the value

added service?

40. How satisfied are you with the quality of the value added services provided?

1 I was never informed by the

service provider

2 I knew, but it was very

complicated to try

3 I knew, but the service charges

were not affordable

4 I never felt the need for it


1 Yes

2 No

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

APPENDIX


41. How satisfied are you with the charges of value added services?

42. How satisfied are you if the value added services can be customized for your usage

requirements?

Overall customer satisfaction

43. How satisfied are you with the overall quality of your mobile service?

44. Please specify the reasons for your response to question no. 41 or any additional

comments?

1) ___________________________________________________________________

_________________________________________________________________

2) ___________________________________________________________________

_________________________________________________________________

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

1 Very dissatisfied

2 Dissatisfied

3 Neutral

4 Satisfied

5 Very satisfied

APPENDIX


3) ___________________________________________________________________

_________________________________________________________________

General information

45. Have you been informed in writing, at the time of subscription of service or within a

week of activation of service the complete details of your tariff plan?

46. Have you terminated you mobile phone connection in the last 12 months?

If no, please skip to question number 49, otherwise continue.

47. If yes, please name your previous service provider?

__________________________________________________________________

48. If yes please specify the reasons for your response to question no. 46?

1) ___________________________________________________________________

_________________________________________________________________

2) ___________________________________________________________________

_________________________________________________________________

3) ___________________________________________________________________

_________________________________________________________________

1 Yes

2 No

1 Yes

2 No

APPENDIX


49. How many days were taken by previous service provider for termination of your

mobile phone connection?

50. Did your service provider adjust your security deposit in the bill raised after you

requested for termination?

51. Have you registered your mobile number for the Do Not Call (DNC) registry with

your service provider so that you do not receive unsolicited commercial calls/SMS?

If yes, than please continue, or else stop here.

52. Do you still receive unsolicited commercial calls/SMS and whether there has been

any change in the frequency of such calls/SMS?

53. Have you made any complaint to your service provider on getting such unsolicited

calls/SMS after registering for the National Do Not Call (DNC) registry?

1 1 day

2 1-3 days

3 3-7 days

4 Greater than 7 days

5 Don‘t remember

1 Yes

2 No

1 Yes

2 No

1 Continued receiving

2 Slight decrease

3 Considerable decrease

4 Stopped receiving

1 Yes

2 No

APPENDIX


If no, please skip to question number 55, otherwise continue.

54. Please indicate the outcome of your complaint?

55. Please tell me the telephone number and the company/agency from which the

unsolicited calls/SMS were received?

_________________________________________________________________________

_________________________________________________________________________

____________________________________________________

1 Compliant was registered by the

service provider

2 Service provider refused to

register the complaint

APPENDIX


8.2 Tables

Table 36: Descriptives of Oneway ANOVA test between operators from survey

Descriptives

OVLQUAL



Mean


1 43 3.6977 .98886 .15080 3.3933 4.0020 .00 5.00

2 33 3.3030 1.21153 .21090 2.8734 3.7326 .00 4.00

3 8 3.7500 .46291 .16366 3.3630 4.1370 3.00 4.00

4 6 3.1667 1.94079 .79232 1.1299 5.2034 .00 5.00

5 6 3.5000 .83666 .34157 2.6220 4.3780 2.00 4.00

7 10 3.8000 .42164 .13333 3.4984 4.1016 3.00 4.00

Total 106 3.5472 1.06128 .10308 3.3428 3.7516 .00 5.00

Table 37: Games-Howell test for post-hoc analysis

Multiple Comparisons

OVLQUAL

Games-Howell

(I)

OPERA

TOR

(J)

OPERA

TOR

Mean Difference




1 2 .39464 .25927 .652 -.3682 1.1575

3 -.05233 .22255 1.000 -.7474 .6428

4 .53101 .80655 .980 -2.8124 3.8745

5 .19767 .37337 .993 -1.2110 1.6063

7 -.10233 .20129 .996 -.7093 .5046

APPENDIX


2 1 -.39464 .25927 .652 -1.1575 .3682

3 -.44697 .26695 .558 -1.2574 .3634

4 .13636 .81991 1.000 -3.1805 3.4532

5 -.19697 .40143 .995 -1.6117 1.2178

7 -.49697 .24951 .365 -1.2436 .2496

3 1 .05233 .22255 1.000 -.6428 .7474

2 .44697 .26695 .558 -.3634 1.2574

4 .58333 .80905 .971 -2.7560 3.9226

5 .25000 .37875 .981 -1.1689 1.6689

7 -.05000 .21110 1.000 -.7395 .6395

4 1 -.53101 .80655 .980 -3.8745 2.8124

2 -.13636 .81991 1.000 -3.4532 3.1805

3 -.58333 .80905 .971 -3.9226 2.7560

5 -.33333 .86281 .998 -3.6317 2.9651

7 -.63333 .80346 .959 -3.9844 2.7178

5 1 -.19767 .37337 .993 -1.6063 1.2110

2 .19697 .40143 .995 -1.2178 1.6117

3 -.25000 .37875 .981 -1.6689 1.1689

4 .33333 .86281 .998 -2.9651 3.6317

7 -.30000 .36667 .954 -1.7174 1.1174

7 1 .10233 .20129 .996 -.5046 .7093

2 .49697 .24951 .365 -.2496 1.2436

3 .05000 .21110 1.000 -.6395 .7395

4 .63333 .80346 .959 -2.7178 3.9844

5 .30000 .36667 .954 -1.1174 1.7174

APPENDIX


Table 38:‎Tukey’s‎test‎for‎homogeneous‎grouping‎of‎means

OPERATOR N

Subset for alpha = 0.05

1

4 6 3.1667

2 33 3.3030

5 6 3.5000

1 43 3.6977

3 8 3.7500

7 10 3.8000

Sig. .775



b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not

guaranteed.

Table 39: Descriptives of ANOVA TRAI operator-wise

Descriptives

OVLQUAL

N Mean

Std.

Deviation

Std.

Error

95% Confidence

Interval for Mean

Minimum Maximum

Between-

Component

Variance

Lower

Bound

Upper

Bound

1.00 9 3.0667 .47011 .15670 2.7053 3.4280 2.32 3.95

2.00 22 3.1132 .25203 .05373 3.0014 3.2249 2.67 3.90

3.00 22 3.0155 .27779 .05923 2.8923 3.1386 2.56 3.92

4.00 10 3.0210 .14791 .04677 2.9152 3.1268 2.71 3.19

5.00 22 3.0218 .28319 .06038 2.8963 3.1474 2.62 3.94

APPENDIX


6.00 19 3.0547 .15079 .03459 2.9821 3.1274 2.65 3.32

7.00 16 3.0844 .11838 .02959 3.0213 3.1475 2.89 3.37

8.00 5 3.1220 .12153 .05435 2.9711 3.2729 2.98 3.24

Total 125 3.0570 .24534 .02194 3.0135 3.1004 2.32 3.95

Model Fixed

Effects

.24948 .02231 3.0128 3.1012

Random

Effects

.02231a 3.0042

a 3.1097

a

-.00238

a. Warning: Between-component variance is negative. It was replaced by 0.0 in computing this random effects

measure.

Table 40: Tukey's test for ANOVA TRAI operator-wise

OVLQUAL

OPERA

TOR N

Subset for alpha

= 0.05

1

Tukey HSDa,,b

3.00 22 3.0155

4.00 10 3.0210

5.00 22 3.0218

6.00 19 3.0547

1.00 9 3.0667

7.00 16 3.0844

2.00 22 3.1132

8.00 5 3.1220

Sig. .966



APPENDIX


OVLQUAL

OPERA

TOR N

Subset for alpha

= 0.05

1

Tukey HSDa,,b

3.00 22 3.0155

4.00 10 3.0210

5.00 22 3.0218

6.00 19 3.0547

1.00 9 3.0667

7.00 16 3.0844

2.00 22 3.1132

8.00 5 3.1220

Sig. .966



b. The group sizes are unequal. The harmonic mean of

the group sizes is used. Type I error levels are not

guaranteed.

Table 41: Comparison of satisfaction scores of TRAI survey, survey and TRAI

benchmark

DETAILS TRAI DATA1 SURVEY DATA

TRAI BENCHMARK

OVERALL CSAC2 SCORE 70.43% 68.93% 95%

SERVICE PROVISION CSAC SCORE 72.43% 69.27% 95%

Satisfaction with time taken to provide new connection 69.27%

1 Data from the survey done for the year 2008-09 and has been consolidated across India.

2 Customer Satisfaction

APPENDIX


Satisfaction with re-activation 42.59%

PREPAID BILLING CSAC SCORE 71.05% 58.06% 90%

Accuracy of charges 58.06%

Tariff customization 73.36%

POSTPAID BILLING CSAC SCORE 69.49% 66.96% 90%

Accuracy of bills 69.77%

Timely delivery of bills 73.17%

Payment process for bills 74.42%

Tariff customization 73.17%

Bill payment customization 74.42%

Billing complaint resolution process 50.96%

Clarity of bills 66.46%

CUSTOMER CARE CSAC SCORE 66.92% 55.04% 90%

Ease of access 55.83%

Time to respond 56.07%

Problem solving ability 53.68%

Time to resolve complaint 54.13%

Customer complaint process 55.53%

NETWORK PERFORMANCE CSAC SCORE 72.25% 63.61% 95%

Local network 63.86%

Travel network 60.89%

Problem resolution regarding network 50.25%

Call ability 67.93%

SMS ability 71.78%

Voice quality 66.33%

Call/SMS during peak hours 64.25%

VALUE ADDED SERVICES CSAC SCORE 69.00% 53.38% 95%

VAS quality 59.24%

APPENDIX


VAS charges 47.53%

VAS customization 65.72%

CUSTOMIZATION SCORES 71.67%

Tariff customization-prepaid 73.36%

Tariff customization-postpaid 73.17%

Bill payment customization-postpaid 74.42%

VAS customization 65.72%

Table 42: TRAI data on customer satisfaction with provision of service

CIRCLE TRAI BENCHMARK 2001-02 2003-04 2006 2007 2008-09

AP 95.00% 93% 96% 97.00% 90.00% 83.00%

ASSAM 95.00% 99.00% 83.00% 67.00%

BIHAR 95.00% 86.00% 75.50% 65.00%

CHENNAI 95.00% 96% 96% 98.00% 89.50% 81.00%

DELHI 95.00% 96% 96% 100.00% 88.50% 77.00%

GUJARAT 95.00% 93% 98.00% 85.50% 73.00%

HARYANA 95.00% 98% 89.00% 81.30% 73.60%

HP 95.00% 100% 89% 88.00% 70.05% 52.10%

J&K 95.00% 87.00% 84.10% 81.20%

KARNATAKA 95.00% 93% 88% 100.00% 91.50% 83.00%

KERALA 95.00% 89% 100.00% 100.00%

KOLKATA 95.00% 90% 94% 97.00% 83.50% 70.00%

MAHARASHTRA 95.00% 90% 94.00% 83.50% 73.00%

MP 95.00% 82% 98.00% 83.50% 69.00%

MUMBAI 95.00% 90% 95.00% 81.00% 67.00%

NE 95.00% 73.00% 73.00%

ORISSA 95.00% 98.00% 89.50% 81.00%

PUNJAB 95.00% 94% 100.00% 87.80% 75.60%

RAJASTHAN 95.00% 96.00% 80.60% 65.20%

TAMILNADU 95.00% 96% 100.00% 87.00% 74.00%

UP EAST 95.00% 91.00% 81.65% 72.30%

UP WEST 95.00% 98% 94.00% 82.70% 71.40%

WEST BENGAL 95.00% 99.00% 82.50% 66.00%

OVERALL CSAC SCORE 94.67% 92.60% 95.64% 84.14% 72.43%

APPENDIX


TRAI BENCHMARK 85.00% 95.00% 95.00% 95.00% 95.00%

Table 43: TRAI data on customer satisfaction with postpaid billing performance


AP 90.00% 88% 90% 100% 91.50% 83.00%

ASSAM 90.00% 58.00% 66.00% 74.00%

BIHAR 90.00% 90.00% 76.50% 63.00%

CHENNAI 90.00% 92% 90% 82% 81.50% 81.00%

DELHI 90.00% 87% 91% 82% 74.00% 66.00%

GUJARAT 90.00% 90% 80% 74.50% 69.00%

HARYANA 90.00% 89% 87.00% 76.85% 66.70%

HP 90.00% 67% 80% 97.00% 81.35% 65.70%

J&K 90.00% 89.00% 78.50% 68.00%

KARNATAKA 90.00% 90% 84% 100% 87.50% 75.00%

KERALA 90.00% 76% 100.00% 100.00%

KOLKATA 90.00% 79% 77% 81% 71.50% 62.00%

MAHARASHTRA 90.00% 83% 100.00% 85.00% 70.00%

MP 90.00% 80% 100.00% 84.00% 68.00%

MUMBAI 90.00% 80% 99.00% 81.00% 63.00%

NE 90.00% 64.00% 64.00%

ORISSA 90.00% 78.00% 78.50% 79.00%

PUNJAB 90.00% 90% 98.00% 84.35% 70.70%

RAJASTHAN 90.00% 84.00% 76.45% 68.90%

TAMILNADU 90.00% 84% 99.00% 83.50% 68.00%

UP EAST 90.00% 92.00% 80.15% 68.30%

UP WEST 90.00% 87% 90.00% 78.20% 66.40%

WEST BENGAL 90.00% 100.00% 84.50% 69.00%


TRAI BENCHMARK 85.00% 90.00% 90.00% 90.00% 90.00%

Table 44: TRAI data on customer satisfaction with prepaid billing performance


AP 90.00% 88% 90% 100% 90.50% 81.00%

ASSAM 90.00% 98.00% 83.00% 68.00%

BIHAR 90.00% 85.00% 74.00% 63.00%

CHENNAI 90.00% 92% 90% 97% 88.50% 80.00%

APPENDIX


DELHI 90.00% 87% 91% 98% 83.80% 69.60%

GUJARAT 90.00% 90% 74% 72.00% 70.00%

HARYANA 90.00% 89% 91.00% 80.15% 69.30%

HP 90.00% 67% 80% 98.00% 82.85% 67.70%

J&K 90.00% 97.00% 90.35% 83.70%

KARNATAKA 90.00% 90% 84% 100% 89.50% 79.00%

KERALA 90.00% 76% 100.00% 100.00%

KOLKATA 90.00% 79% 77% 91% 78.00% 65.00%

MAHARASHTRA 90.00% 83% 92.00% 81.00% 70.00%

MP 90.00% 80% 100.00% 84.00% 68.00%

MUMBAI 90.00% 80% 98% 82.50% 67.00%

NE 90.00% 72.00% 72.00%

ORISSA 90.00% 89.00% 81.50% 74.00%

PUNJAB 90.00% 90% 99.00% 86.25% 73.50%

RAJASTHAN 90.00% 90.00% 79.45% 68.90%

TAMILNADU 90.00% 84% 99.00% 86.00% 73.00%

UP EAST 90.00% 77.00% 74.05% 71.10%

UP WEST 90.00% 87% 99.00% 82.70% 66.40%

WEST BENGAL 90.00% 98.00% 80.50% 63.00%


TRAI BENCHMARK 85.00% 90.00% 90.00% 90.00% 90.00%

Table 45: TRAI data on customer satisfaction with help services


AP 90.00% 92% 92% 64% 71.00% 78.00%

ASSAM 90.00% 78.00% 69.50% 61.00%

BIHAR 90.00% 65.00% 60.00% 55.00%

CHENNAI 90.00% 96% 92% 61.00% 70.50% 80.00%

DELHI 90.00% 89% 91% 86.00% 76.10% 66.20%

GUJARAT 90.00% 89% 74% 69.50% 65.00%

HARYANA 90.00% 93% 70.00% 69.00% 68.00%

HP 90.00% 78% 79% 67.00% 65.90% 64.80%

J&K 90.00% 62.00% 68.20% 74.40%

KARNATAKA 90.00% 90% 86% 61% 70.00% 79.00%

KERALA 90.00% 82% 60.00% 60.00%

KOLKATA 90.00% 81% 80% 69% 63.50% 58.00%

MAHARASHTRA 90.00% 81% 66.00% 65.00% 64.00%

APPENDIX


MP 90.00% 88% 76.00% 70.00% 64.00%

MUMBAI 90.00% 79% 68.00% 64.00% 60.00%

NE 90.00% 61.00% 61.00%

ORISSA 90.00% 68.00% 65.00% 62.00%

PUNJAB 90.00% 86% 69.00% 70.70% 72.40%

RAJASTHAN 90.00% 64.00% 68.60% 73.20%

TAMILNADU 90.00% 89% 60.00% 63.00% 66.00%

UP EAST 90.00% 68.00% 71.15% 74.30%

UP WEST 90.00% 91% 70.00% 69.95% 69.90%

WEST BENGAL 90.00% 72.00% 64.00% 56.00%


TRAI BENCHMARK 85.00% 90.00% 90.00% 90.00% 90.00%

Table 46: TRAI data on customer satisfaction with network performance, reliability

and availability


AP 95.00% 88% 93% 91% 86.00% 81.00%

ASSAM 95.00% 73.00% 72.50% 72.00%

BIHAR 95.00% 53.00% 59.00% 65.00%

CHENNAI 95.00% 85% 93% 73% 76.50% 80.00%

DELHI 95.00% 90% 93% 90% 80.80% 71.60%

GUJARAT 95.00% 89% 60% 63.00% 66.00%

HARYANA 95.00% 91% 89.00% 79.75% 70.50%

HP 95.00% 89% 83% 89.00% 78.50% 68.00%

J&K 95.00% 66.00% 81.20% 96.40%

KARNATAKA 95.00% 88% 84% 74% 76.00% 78.00%

KERALA 95.00% 76% 99.00% 99.00%

KOLKATA 95.00% 68% 78% 73% 65.50% 58.00%

MAHARASHTRA 95.00% 82% 82.00% 73.50% 65.00%

MP 95.00% 81% 86.00% 75.50% 65.00%

MUMBAI 95.00% 79% 88% 74.00% 60.00%

NE 95.00% 75.00% 75.00%

ORISSA 95.00% 72.00% 75.50% 79.00%

PUNJAB 95.00% 88% 96.00% 86.40% 76.80%

RAJASTHAN 95.00% 87.00% 79.15% 71.30%

TAMILNADU 95.00% 90% 58.00% 65.50% 73.00%

UP EAST 95.00% 76.00% 77.50% 79.00%

APPENDIX


UP WEST 95.00% 91% 79.00% 76.95% 74.90%

WEST BENGAL 95.00% 65.00% 64.50% 64.00%


TRAI BENCHMARK 85.00% 95.00% 95.00% 95.00% 95.00%

Table 47: TRAI data on customer satisfaction with maintainability


AP 95.00% 84% 91% 80% 80.50% 81.00%

ASSAM 95.00% 76.00% 74.50% 73.00%

BIHAR 95.00% 96.00% 80.50% 65.00%

CHENNAI 95.00% 90% 91% 76% 78.50% 81.00%

DELHI 95.00% 85% 89% 68% 69.25% 70.50%

GUJARAT 95.00% 85% 88% 77.50% 67.00%

HARYANA 95.00% 92% 73.00% 72.10% 71.20%

HP 95.00% 86% 77% 100.00% 83.20% 66.40%

J&K 95.00% 76.00% 84.40% 92.80%

KARNATAKA 95.00% 90% 83% 77.00% 77.00%

KERALA 95.00% 76% 100.00% 100.00%

KOLKATA 95.00% 73% 71% 78% 72.50% 67.00%

MAHARASHTRA 95.00% 71% 66.00% 66.00%

MP 95.00% 59% 81.00% 73.00% 65.00%

MUMBAI 95.00% 75% 80% 71.00% 62.00%

NE 95.00% 78.00% 78.00%

ORISSA 95.00% 82.00% 79.00% 76.00%

PUNJAB 95.00% 86% 90.00% 81.45% 72.90%

RAJASTHAN 95.00% 86.00% 78.70% 71.40%

TAMILNADU 95.00% 86% 100% 87.00% 74.00%

UP EAST 95.00% 71.00% 74.10% 77.20%

UP WEST 95.00% 79% 58.00% 63.15% 68.30%

WEST BENGAL 95.00% 88.00% 76.00% 64.00%


TRAI BENCHMARK 85.00% 95.00% 95.00% 95.00% 95.00%

Table 48: TRAI data on customer satisfaction with offered supplementary services


APPENDIX


AP 95.00% 87% 95% 96% 86.00% 76.00%

ASSAM 95.00% 98.00% 82.00% 66.00%

BIHAR 95.00% 97.00% 81.50% 66.00%

CHENNAI 95.00% 95% 87% 98% 86.00% 74.00%

DELHI 95.00% 92% 94% 100% 83.35% 66.70%

GUJARAT 95.00% 95% 98% 85.00% 72.00%

HARYANA 95.00% 93% 71.00% 71.55% 72.10%

HP 95.00% 95% 87% 72.00% 62.65% 53.30%

J&K 95.00% 100.00% 93.50% 87.00%

KARNATAKA 95.00% 96% 84% 95% 81.50% 68.00%

KERALA 95.00% 84% 100.00% 100.00%

KOLKATA 95.00% 87% 82% 98% 80.00% 62.00%

MAHARASHTRA 95.00% 86% 91% 82.50% 74.00%

MP 95.00% 93% 88.00% 76.50% 65.00%

MUMBAI 95.00% 83% 98% 83.50% 69.00%

NE 95.00% 74.00% 74.00%

ORISSA 95.00% 95.00% 81.00% 67.00%

PUNJAB 95.00% 91% 99.00% 82.85% 66.70%

RAJASTHAN 95.00% 92.00% 79.45% 66.90%

TAMILNADU 95.00% 89% 100% 85.00% 70.00%

UP EAST 95.00% 92.00% 79.35% 66.70%

UP WEST 95.00% 88% 96.00% 81.35% 66.70%

WEST BENGAL 95.00% 97.00% 79.00% 61.00%


TRAI BENCHMARK 85.00% 95.00% 95.00% 95.00% 95.00%

Table 49: TRAI data on customer satisfaction with overall quality of service

CIRCLE TRAI BENCHMARK 2001-02 2003 2006 2007 2008-09

AP 95.00% 85.00% 93.00% 91.00% 83.00% 75.00%

ASSAM 95.00% 86.00% 79.00% 72.00%

BIHAR 95.00% 78.00% 72.00% 66.00%

CHENNAI 95.00% 87.00% 93.00% 85% 83.00% 81.00%

DELHI 95.00% 85.00% 91.00% 93% 82.05% 71.10%

GUJARAT 95.00% 91.00% 78.00% 70.50% 63.00%

HARYANA 95.00% 88.00% 82.00% 76.65% 71.30%

HP 95.00% 78.00% 75.00% 85.00% 70.35% 55.70%

APPENDIX


J&K 95.00% 82.00% 89.30% 96.60%

KARNATAKA 95.00% 90.00% 86.00% 79.50% 73.00%

KERALA 95.00% 83.00% 98.00% 98.00%

KOLKATA 95.00% 66.00% 73.00% 83% 74.50% 66.00%

MAHARASHTRA 95.00% 76.00% 86% 74.00% 62.00%

MP 95.00% 80.00% 90.00% 75.50% 61.00%

MUMBAI 95.00% 86.00% 91% 77.50% 64.00%

NE 95.00% 83.00% 76.00% 76.00%

ORISSA 95.00% 82.00% 77.00% 72.00%

PUNJAB 95.00% 92.00% 83.30% 74.60%

RAJASTHAN 95.00% 84.00% 86.00% 79.00% 72.00%

TAMILNADU 95.00% 82% 77.50% 73.00%

UP EAST 95.00% 83.00% 83.00% 77.75% 72.50%

UP WEST 95.00% 87.00% 78.30% 69.60%

WEST BENGAL 95.00% 89.00% 84.00% 73.00% 62.00%


TRAI BENCHMARK 85.00% 95.00% 95.00% 95.00% 95.00%

Table 50: Comparison of satisfaction scores of TRAI survey, survey and TRAI

benchmark for Airtel

DETAILS TRAI DATA3 SURVEY DATA

TRAI BENCHMARK

OVERALL CSAC SCORE 70.43% 71.95% 95%

SERVICE PROVISION CSAC SCORE 72.43% 69.77% 95%

Satisfaction with time taken to provide new connection

69.77%

Satisfaction with re-activation 42.44

%

PREPAID BILLING CSAC SCORE 71.05% 53.57% 90%

Accuracy of charges 53.57

%

Tariff customization 77.38

%

3 Data from the survey done for the year 2008-09 and has been consolidated across India.

APPENDIX


POSTPAID BILLING CSAC SCORE 69.49% 62.84% 90%

Accuracy of bills 67.05

%

Timely delivery of bills 70.24

%

Payment process for bills 72.73

%

Tariff customization 67.86

%

Bill payment customization 77.27

%

Billing complaint resolution process 41.67

%

Clarity of bills 62.50

%

CUSTOMER CARE CSAC SCORE 66.92% 56.79% 90%

Ease of access 51.25

%

Time to respond 58.75

%

Problem solving ability 57.05

%

Time to resolve complaint 56.88

%

Customer complaint process 60.00

%

NETWORK PERFORMANCE CSAC SCORE 72.25% 69.24% 95%

Local network 70.73

%

Travel network 67.07

%

Problem resolution regarding network 52.44

%

Call ability 75.00

%

SMS ability 75.61

APPENDIX


%

Voice quality 73.72

%

Call/SMS during peak hours 70.12

%

VALUE ADDED SERVICES CSAC SCORE 69.00% 55.56% 95%

VAS quality 62.50

%

VAS charges 48.61

%

VAS customization 67.50

%

CUSTOMIZATION SCORES 72.50%

Tariff customization-prepaid 77.38

%

Tariff customization-postpaid 67.86

%

Bill payment customization-postpaid 77.27

%

VAS customization 67.50

%

Table 51: Descriptive statistics of factor analysis of Airtel postpaid customers


Mean Std. Deviation Analysis N

AQRCN 4.0500 .60481 20

REACT 2.6000 1.75919 20

ACCBL 3.6000 .99472 20

TIMBL 3.6500 1.38697 20

PAYBL 3.9000 .91191 20

TRFCZ 3.5000 1.31789 20

APPENDIX


BILCZ 4.0500 .94451 20

BILCM 1.8500 1.69442 20

BILCL 3.1000 1.29371 20

CCACS 3.0500 .75915 20

CCRST 3.5000 .82717 20

CCPSL 3.3000 .80131 20

CCRSC 3.4000 .59824 20

RSCPP 3.6000 .75394 20

NSAVL 3.8000 1.10501 20

NSMOV 3.6500 1.13671 20

NSPSA 3.2000 1.43637 20

MKCAL 4.0000 .91766 20

MKSMS 4.1000 .85224 20

VCQUL 3.8000 1.15166 20

MCLSM 3.7000 .97872 20

VASQL 3.4500 .94451 20

VASCG 2.8000 .89443 20

VASCZ 3.7500 1.01955 20

OVLQL 3.8000 .52315 20

Table 52: Communalities of factor analysis of Airtel postpaid customers

Communalities

Initial Extraction

AQRCN 1.000 .900

REACT 1.000 .649

ACCBL 1.000 .835

TIMBL 1.000 .932

APPENDIX


PAYBL 1.000 .938

TRFCZ 1.000 .929

BILCZ 1.000 .886

BILCM 1.000 .721

BILCL 1.000 .896

CCACS 1.000 .617

CCRST 1.000 .832

CCPSL 1.000 .929

CCRSC 1.000 .804

RSCPP 1.000 .854

NSAVL 1.000 .897

NSMOV 1.000 .813

NSPSA 1.000 .837

MKCAL 1.000 .943

MKSMS 1.000 .956

VCQUL 1.000 .752

MCLSM 1.000 .759

VASQL 1.000 .790

VASCG 1.000 .724

VASCZ 1.000 .948

OVLQL 1.000 .770

Extraction Method: Principal Component Analysis.

Table 53: Factor analysis of Airtel postpaid customers

Total Variance Explained

Component Initial Eigenvalues

Extraction Sums of Squared

Loadings

Rotation Sums of Squared

Loadings

APPENDIX


Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 7.671 30.686 30.686 7.671 30.686 30.686 5.748 22.991 22.991

2 4.090 16.362 47.047 4.090 16.362 47.047 3.574 14.296 37.288

3 2.877 11.508 58.556 2.877 11.508 58.556 3.549 14.198 51.485

4 2.109 8.436 66.992 2.109 8.436 66.992 2.338 9.351 60.837

5 1.768 7.074 74.066 1.768 7.074 74.066 2.062 8.249 69.085

6 1.240 4.961 79.028 1.240 4.961 79.028 2.062 8.248 77.333

7 1.154 4.616 83.644 1.154 4.616 83.644 1.578 6.310 83.644

8 .906 3.626 87.269

9 .821 3.284 90.554

10 .590 2.362 92.916

11 .521 2.086 95.002

12 .378 1.511 96.513

13 .237 .947 97.460

14 .225 .901 98.362

15 .171 .685 99.047

16 .100 .402 99.448

17 .064 .256 99.705

18 .051 .202 99.907

19 .023 .093 100.000

20 3.855E-

16

1.542E-15 100.000

21 2.062E-

16

8.249E-16 100.000

22 1.194E-

16

4.775E-16 100.000

APPENDIX


23 -8.487E-

17

-3.395E-

16

100.000

24 -2.049E-

16

-8.197E-

16

100.000

25 -2.601E-

16

-1.040E-

15

100.000


Table 54: Descriptive statistics for factor analysis of Airtel prepaid cusotmers


Mean Std. Deviation Analysis N

AQRCN 3.6000 1.42902 20

REACT 2.9500 1.87715 20

BILCG 3.2000 .95145 20

TRFCZ 4.1000 1.25237 20

CCACS 2.7500 1.71295 20

CCRST 2.9000 1.48324 20

CCPSL 2.8500 1.63111 20

CCRSC 2.9000 1.51831 20

RSCPP 2.9500 1.60509 20

NSAVL 3.8500 .98809 20

NSMOV 3.7500 .91047 20

NSPSA 3.0000 1.41421 20

MKCAL 3.8000 1.15166 20

MKSMS 3.9500 1.05006 20

VCQUL 3.7000 1.49032 20

MCLSM 3.9000 .96791 20

VASQL 2.7000 1.78001 20

APPENDIX


VASCG 2.3500 1.66307 20

VASCZ 3.5000 1.50438 20

OVLQL 3.9500 .60481 20

Table 55: Rotated Component Matrix for factor analysis for Airtel postpaid

customers

Rotated Component Matrixa

Component

1 2 3 4 5 6 7

NSAVL .886

MKCAL .885

NSMOV .853

BILCL .838

MCLSM .768

ACCBL .700

REACT

CCACS

VASCZ .950

RSCPP .751

VASQL .638

MKSMS

OVLQL

PAYBL .918

BILCZ .868

TIMBL .865

TRFCZ .613 .644

CCRSC .826

APPENDIX


CCPSL .698

BILCM .802

VASCG .786

CCRST .846

VCQUL .654

AQRCN .891

NSPSA .740


Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 8 iterations.


postpaid customers

Correlations

OVERALL_QU

ALITY

CRITIC

AL

CUSTOMIZA

TION

BILLI

NG

CUST_SER

VICE

SATISFAC

TION

DELIG

HT

EXT

RA

Pearso

n

Correlat

ion

OVERALL_QU

ALITY

1.000 .457 .632 .580 .379 .089 -.007 .249

CRITICAL .457 1.000 .341 .339 .510 .275 .213 .513

CUSTOMIZATI

ON

.632 .341 1.000 .484 .339 .121 .269 .018

BILLING .580 .339 .484 1.000 .020 -.076 .123 .176

CUST_SERVI

CE

.379 .510 .339 .020 1.000 .546 .350 .085

SATISFACTIO

N

.089 .275 .121 -.076 .546 1.000 .069 .014

DELIGHT -.007 .213 .269 .123 .350 .069 1.000 -.084

EXTRA .249 .513 .018 .176 .085 .014 -.084 1.00

0

APPENDIX


Sig. (1-

tailed)

OVERALL_QU

ALITY

. .019 .001 .003 .045 .351 .487 .138

CRITICAL .019 . .065 .066 .009 .114 .177 .009

CUSTOMIZATI

ON

.001 .065 . .013 .066 .301 .119 .469

BILLING .003 .066 .013 . .465 .372 .297 .223

CUST_SERVI

CE

.045 .009 .066 .465 . .005 .060 .356

SATISFACTIO

N

.351 .114 .301 .372 .005 . .383 .477

DELIGHT .487 .177 .119 .297 .060 .383 . .358

EXTRA .138 .009 .469 .223 .356 .477 .358 .

N OVERALL_QU

ALITY

21 21 21 21 21 21 21 21

CRITICAL 21 21 21 21 21 21 21 21

CUSTOMIZATI

ON

21 21 21 21 21 21 21 21

BILLING 21 21 21 21 21 21 21 21

CUST_SERVI

CE

21 21 21 21 21 21 21 21

SATISFACTIO

N

21 21 21 21 21 21 21 21

DELIGHT 21 21 21 21 21 21 21 21

EXTRA 21 21 21 21 21 21 21 21

Table 57: Communalities of factor analysis of Airtel prepaid customers

Communalities

Initial Extraction

AQRCN 1.000 .565

APPENDIX


REACT 1.000 .825

BILCG 1.000 .437

TRFCZ 1.000 .459

CCACS 1.000 .784

CCRST 1.000 .885

CCPSL 1.000 .863

CCRSC 1.000 .914

RSCPP 1.000 .875

NSAVL 1.000 .824

NSMOV 1.000 .845

NSPSA 1.000 .922

MKCAL 1.000 .422

MKSMS 1.000 .792

VCQUL 1.000 .707

MCLSM 1.000 .955

VASQL 1.000 .902

VASCG 1.000 .931

VASCZ 1.000 .810

OVLQL 1.000 .910

Extraction Method: Principal

Component Analysis.

Table 58: Factor analysis of Airtel prepaid customers

Total Variance Explained

Component Initial Eigenvalues

Extraction Sums of Squared

Loadings

Rotation Sums of Squared

Loadings

APPENDIX


Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 6.931 34.654 34.654 6.931 34.654 34.654 4.911 24.556 24.556

2 3.062 15.311 49.965 3.062 15.311 49.965 3.765 18.826 43.382

3 2.380 11.900 61.865 2.380 11.900 61.865 2.911 14.553 57.936

4 1.895 9.474 71.339 1.895 9.474 71.339 2.583 12.917 70.852

5 1.361 6.804 78.142 1.361 6.804 78.142 1.458 7.290 78.142

6 .938 4.692 82.835

7 .871 4.355 87.189

8 .759 3.796 90.985

9 .517 2.587 93.572

10 .426 2.128 95.699

11 .355 1.774 97.473

12 .198 .990 98.463

13 .107 .535 98.998

14 .089 .445 99.444

15 .066 .328 99.772

16 .020 .098 99.870

17 .016 .079 99.948

18 .005 .027 99.975

19 .005 .025 100.000

20 -2.815E-

16

-1.408E-

15

100.000


Table 59: Rotated Component Matrix for factor analysis for Airtel prepaid customers

Component

APPENDIX


1 2 3 4 5

CCRSC .930

CCRST .903

RSCPP .862

CCPSL .854

CCACS .837

AQRCN

MCLSM .894

REACT .879

NSMOV .697

MKSMS .657

OVLQL .823

BILCG .640

TRFCZ .623

MKCAL

NSAVL

VASCG .921

VASQL .913

VASCZ .677

NSPSA .873

VCQUL


Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 6 iterations.

APPENDIX



prepaid customers

Correlations

OVERALL_QUALI

TY

CUST_CA

RE

CALL_SMS_ABILI

TY

BILLIN

G VAS

NETWORK_PE

RF

Pearson

Correlati

on

OVERALL_QUALI

TY

1.000 -.023 .652 .749 .071 -.265

CUST_CARE -.023 1.000 .297 .030 .054 -.304

CALL_SMS_ABILI

TY

.652 .297 1.000 .406 -

.095

-.214

BILLING .749 .030 .406 1.000 .157 -.273

VAS .071 .054 -.095 .157 1.00

0

.068

NETWORK_PER

F

-.265 -.304 -.214 -.273 .068 1.000

Sig. (1-

tailed)

OVERALL_QUALI

TY

. .463 .001 .000 .386 .137

CUST_CARE .463 . .109 .452 .413 .103

CALL_SMS_ABILI

TY

.001 .109 . .042 .349 .190

BILLING .000 .452 .042 . .260 .129

VAS .386 .413 .349 .260 . .391

NETWORK_PER

F

.137 .103 .190 .129 .391 .

N OVERALL_QUALI

TY

19 19 19 19 19 19

CUST_CARE 19 19 19 19 19 19

CALL_SMS_ABILI

TY

19 19 19 19 19 19

APPENDIX


BILLING 19 19 19 19 19 19

VAS 19 19 19 19 19 19

NETWORK_PER

F

19 19 19 19 19 19

Chapter 9

Bibliography &

references

BIBLIOGRAPHY


9 BIBLIOGRAPHY AND REFERENCES

1. Anderson, E. W., Fornell, C., & Rust, R. T. (1997). Customer satisfaction,

productivity, and profitability: Differences between goods and services. Marketing

Science , 129-145.

2. BNET Business Dictionary. (2009, May 11). Customer Focus Definition and

additional resources from BNET. Retrieved October 21, 2009, from CBS Interactive

Inc website: http://www.bnet.com

3. BNET Business Dictionary. (2009, May 11). Customer Satisfaction: Definition and

additional resources from BNET. Retrieved October 21, 2009, from CBS Interactive

Inc. website: http://www.bnet.com

4. Britt, P. (2005). CRM gets the call. Customer Relationship Management , 40-44.

5. Business SA. (2004, December 3). Customer Focus. pp. 1-9.

6. Callaghan, D. (2001, May 2). Fighting to keep users loyal. eweek , p. 33.

7. Chau, F. (2005). CRM: moving back to customer centricity. Telecom Asia , 30-32.

8. Datamonitor plc. (2009). Bharti Airtel Limited : Company Profile. New Delhi:

Datamonitor plc.

9. Erevelles, S., Srinivasan, S., & Rangel, S. (2003). Consumer satisfaction for internet

service providers: an analysis of underlying process. Information Technology and

Management , 69-89.

10. Field, A. (2002). Discovering Statistics using SPSS for Windows. London: SAGE

Publications Ltd.

BIBLIOGRAPHY


11. Gerpott, T. J., Rams, W., & Schindler, A. (2001). Customer retention, loyalty, and

satisfaction in the German mobile cellular telecommunications market.

Telecommunications Policy , 249-269.

12. iSixSigma. (2002, November 1). Customer Focus. Retrieved November 14, 2009,

from iSixSigma website: http://www.isixsigma.com

13. Kim, M. K., Park, M. C., & Jeong, D. H. (2004). The effects of customer

satisfaction and switching barrier on customer loyalty in Korean mobile

telecommunication services. Telecommunications Policy , 145-159.

14. Koivisto, M., & Urbaczewski, A. (2004). The relationship between quality of

service perceived and delivered in mobile internet communications. Information

Systems and e-Business Management , 309-323.

15. Kotler, P., Keller, K. L., Koshy, A., & Jha, M. (2007). Marketing Management - A

South Asian Perspective. New Delhi: Dorling Kindersley (India) Pvt. Ltd.

16. Lai, T. L. (2004). Service quality and perceived value‘s impact on satisfaction,

intention and usage of short message service (SMS). Information Systems Frontiers

, 353-368.

17. Levine, S. (2002). Lessons in CRM. Telecom Asia , 38-42.

18. Lulla, S. (2009, November 14). How customer focus is helping Bajaj Auto, ITC cut

deeper - dnaindia.com. Retrieved November 14, 2009, from Diligent Media

Corporation website: http://www.dnaindia.com

19. Mani, S. (2008). Growth of India's Telecom Services (1991-2007): Can it Lead to

Emergence of a Manufacturing Hub? Economic & Political Weekly , 40-46.

20. Marques de Sa, J. P. (2007). Applied Statistics using SPSS, STATISTICA, MATLAB

and R. Berlin: Springer-Verlag Berlin Heidelberg.

21. Reserve Bank of India. (2008-09). Annual Report. Reserve Bank of India.

BIBLIOGRAPHY


22. Rubin, J. (1994). Handbook of Usability Testing. New York: John Wiley & Sons.

23. SPSS. (2008, August 23). SPSS Statistics 17.0. SPSS.

24. Stalk, G., Evans, P., & Shulman, L. E. (1992). Competing Capabilities: The New

Rules of Corporate Strategy. Harvard Business Review , 57-69.

25. Telecom Regulatory Authority of India. (2009). Quality of Service Assessment.

Telecom Regulatory Authority of India.

26. Telecom Regulatory Authority of India. (2005, July 1). Telecom Regulatory

Authority of India Notification. Telecom Regulatory Authority of India Notification .

New Delhi, New Delhi, India: Telecom Regulatory Authority of India.

27. Telecom Regulatory Authority of India. (2009). The Indian Telecom Services

Performance Indicators January-March 2009. New Delhi: Telecom Regulatory

Authority of India.

28. Thyfault, M. (2001, April 2). Eliminating the Middle Man. Interactive Week , pp.

45-46.

29. Wright, L. T., Stone, M., & Abbott, J. (2002). The CRM imperative — Practice vs

theory in the telecommunications industry. Journal of Database Marketing , 339-

349.

satya final project

Technology

project report

characteristics of customer

customer satisfaction

threat analysis

factor analysis

design of study

nature of study

objective of study