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Psychographic segmentation of youth inthe evolving Indian retail marketRitu Narang aa Department of Business Administration, University of Lucknow,Lucknow, U.P., IndiaPublished online: 24 Nov 2010.

To cite this article: Ritu Narang (2010) Psychographic segmentation of youth in the evolving Indianretail market, The International Review of Retail, Distribution and Consumer Research, 20:5,535-557, DOI: 10.1080/09593969.2010.520508

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Psychographic segmentation of youth in the evolving Indian retail

market

Ritu Narang*

Department of Business Administration, University of Lucknow, Lucknow, U.P., India

(Received November 2009; final version received June 2010)

Indian youth is emerging as a very powerful and significant consumer market.Marketers would be able to devise more effective strategies to tap this segment ifthey were able to get insights into their psychographic profiles. The present study,therefore, seeks to understand the psychographic along with demographicvariables of the youth in India. Based on cluster analysis, four psychographicclusters are identified: ‘Get-going Adopter’, ‘Inner Value-oriented Conservative’,‘Political and Sport Enthusiast’ and ‘Independent Life Lover’. The findings revealsignificant psychographic differences among the identified clusters and suggestthat it is more meaningful for the marketer to concentrate on two segments, ‘Get-going Adopter’ and ‘Independent Life Lover’ that account for 70% of therespondents rather than the other two clusters and design their marketingstrategies accordingly.

Keywords: psychographic segmentation; Indian youth

Introduction

India is one of the fastest growing economies in the world with increased disposableincome in the hands of the consumers who are experiencing a change in theirattitudes and increasingly becoming trend-conscious. There are over 12 million retailoutlets in India with 96% of them being smaller than five hundred square feet. Theorganized sector in the retail industry is around 4–5% and is expected to reach 16%by 2012 as forecast by KPMG (2009). The India Retail Report (2009) on the otherhand, has predicted that the country’s retail market will grow to $395 billion by 2010as organized retail is expected to be 13% of the total market. A large number ofIndian Corporate houses including Rahejas, Tatas, Reliance, Goenkas, Piramalshave already made their entry into the retail arena leading to the emergence ofdifferent retail formats such as departmental stores, discount stores, specialty stores,supermarkets, hypermarkets.

India has been rated as the fifth most attractive emerging retail market andranked first in a Global Retail Development Index of 30 developing countriesprepared by AT Kearney (2009). McKinsey Global Institute (2007) has estimatedthat the Indian consumer market is likely to quadruple to 1.5 trillion US dollars by2025 from about 0.38 trillion US dollars in 2005, powered by the growth of middleclass from 50 million to 583 million people during this period. Earlier, Lynch (2005)

*Email: ritu_vnarang@yahoo.co.in

The International Review of Retail, Distribution and Consumer Research

Vol. 20, No. 5, December 2010, 535–557

ISSN 0959-3969 print/ISSN 1466-4402 online

� 2010 Taylor & Francis

DOI: 10.1080/09593969.2010.520508

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had also predicted that India’s consumption spending would be driven by a growingmiddle class and large numbers of people entering the workforce. It estimated thatmore than 7 million people enter the 20–34 age group and 3 million enter the 20–24years age group every year.

A report by Ernst and Young (2007–2008) reveals that 54% of the Indians areaged below 25 years and ‘more than 60% of the population is estimated to constitutethe working age group (15–60 years) till 2050’. According to Dutta (2004), the newconsumer groups that are emerging in India can be classified into ‘The Young andRestless’, ‘The Bold and the Bountiful’, ‘The Golden Folks in High Spirits’ and ‘TheForeign Friends’. India has the youngest population profile in the world in differentincome segments that tend to exert substantial influence on their parents’ as well astheir own spending. The increased spending in the consumer market is expected to bedriven by the youth that constitute 20% of the global population under 25 years ofage (NCAER 2002). Another study by Farrell and Beinhocker (2007) of MckinseyGlobal Institute reveals that 1.2 million global Indian households accounted for 2trillion rupees of expenditure (the global Indian is one who earns more than 1 millionrupees). This figure of global Indian households is expected to rise to 9.5 million withtheir spending power of 14.1 trillion rupees1 by 2025 and account for 20% of totalIndian consumption (Farrell and Beinhocker 2007). This dramatic rise in spendingpower is expected to come from young graduates of India’s top colleges who areemerging as ‘ferociously upwardly mobile’ and will be in a position to commandlarge salaries from Indian and foreign multinationals. This discussion clearly pointsout the importance of Indian youth in terms of its sheer size and market with uniquecharacteristics. However, there is negligible information available in the publicdomain regarding the psychographic profile of the Indian youth in the context ofchanging retail environment. The present study, therefore, seeks to understand thepsychographic profile of college and University students in Lucknow.

Objectives and relevance

The market segmented on the basis of demographic factors alone fails to capture thecomplete characteristics of the consumers, thus making it difficult for the marketer todraw a meaningful picture (Cooper 1984). The consumers in the same demographicsegment possess different psychographic makeups. It has been widely recognized inmarketing and retail literature that the measurement of attitude and beliefs enablesmarketers to predict consumer behavior. A large number of studies have beencarried out on shopping behavior as revealed in a literature review but they havebeen confined mainly to developed nations. Very few studies have been conducted inIndia on this topic as is evident on the basis of information available in the publicdomain. Sinha and Uniyal (2005) have classified Indian shoppers into six segmentsbased on the observation of shopping behavior. Kureshi, Sood, and Koshy (2007)studied the demographic and psychographic profiles of the consumers in the city ofBangalore, India in three single-brand sport outlets and reported significantdifferences between ‘Browser’ and ‘Purposive’ customers. They identified fourdimensions: ‘Fashion Conscious’, ‘Shopping Styles’, ‘Health and Fitness Conscious’and ‘Outlook’ comprising 38 statements for the psychographic scale. Another study,conducted to understand the profile of the Indian customers of the newspapermarket based on psychographic lifestyles by using Value and Lifestyle Segmentationor VALS (Anandan, Prasanna, and Madhu 2006), suggested that psychographic

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segments should be targeted by the brands to sustain themselves in the competitivemarket environment.

Though Indian youth constitutes a powerful and significant segment of themarket in the changed retailing scenario but very limited research has been doneon them, most of which is unavailable to academic researchers. Furthermore,research conducted by marketing agencies on Indian youth does not provide anyinformation on the research instrument, methodology employed or the techniqueof statistical analysis. There is a study on the youth of Kolkata (Goswami 2007).Goswami’s work, however, captures the peculiar culture/subculture of that easternpart of India (West Bengal), which though Indian in nature, is distinct from thatof the northern part of the country. This current research is based on Lucknow,the capital city of Uttar Pradesh, which is representative of the northern part ofthe nation. Kolkata, a metropolitan city, represents a tier I city which saw theemergence of organized retail and infrastructure development much earlier thanthe city of Lucknow, which comes under the category of tier II cities. Theobjective of this paper is not to identify similarities/differences in thepsychographic profiles of youth from different parts of the nation, but is insteadto identify psychographic segments and compare them with those of youth fromdeveloping nations. The current study seeks to develop and thereby understandthe psychographic profile of Indian youth. This research will be useful not onlyfor academicians but marketers/retailers as well, seeking to understand the youthpurchase behavior. It will furnish adequate information to equip them withrequisite tools to attract and retain consumers. Furthermore, it will extendcurrent research and provide a basis for further study.

Literature review on psychographic factors

Segmentation is considered useful in identifying and grouping the differences so thatappropriate actions can be undertaken for consumer satisfaction (Plummer 1974).Demographic and psychographic segmentation can be utilized for media planningand designing of promotional strategy (Bearden, Teel, and Durand 1978). A numberof research papers have been devoted toward the development and use ofpsychographics (Wells 1974). Broadly, psychographics is any measurement andanalysis of consumer’s mind that seeks to point out how they feel, think, react andreflect (Nelson 1971). According to some researchers, attempts to measure lifestyleare known as psychographics (Demby 1994). The term ‘lifestyle’ was first coined byAlfred Adler in 1929 and refers to an individual’s activities, interests and opinions(AIO) and the way they spends their time and money. Bauman (1990) opines that‘lifestyles boil down almost entirely to styles of consumption’.

Lifestyle is considered to be an important determinant of consumer behavior(Assael 1995; Jobber and Lancaster 2003) as it provides valuable information aboutthe buyer (Wells and Tigert 1971) and helps in designing effective communicationstrategies (Moschis 1976). Lifestyle, demographic and media usage characteristicsprovide valuable insights into store choice (Bearden, Teel, and Durand 1978) and arelationship between shoppers’ store choice and socio-economic characteristics canbe studied by using a multidimensional scale. Other studies have also pointed out therelationship between customer characteristics and store choice (Aaker and Jones1971; Leszczyc, Sinha, and Timmermans 2000). The Theory of Reasoned Action(Ajzen and Fishbein 1980) has also been employed by marketers to predict consumer

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behavior with respect to product purchase. According to this theory, psychologicalconstructs such as attitudes and beliefs that are formulated through direct or indirectexperience with a product’s attribute impact an individual’s intention to act that inturn influences their purchase behavior. Consumer activities, interests and opinionsabout the shopping process have been termed as shopping orientation (Moschis1992) that tend to reflect consumer’s personal, economic, recreational and socialmotivations for shopping (Lumpkin, Hawes, and Darden 1986; Shim and Mahoney1992). Shopping orientation along with lifestyle impact the evaluation of storeattributes (Osman 2001). Some researchers have classified shoppers on post hoc basisby using lifestyle segmentation rather than conventional a priori segmentation andidentified two groups of shoppers: ‘shops importance motivation’ and ‘serviceimportance motivation’ (Dennis, Marsland, and Cockett 2001).

The measurement instrument employed to measure psychographic variables is anAIO battery of questions that comprises a large number of statements requiringrespondents to agree or disagree with them. This approach has been very popularwith researchers (Wells and Tigert 1971; Plummer 1974; Allred, Smith, and Swinyard2006; Aziz and Ariffin 2009; Hur, Kim, and Park 2010). Lifestyle has been defined as‘the manner in which people conduct their lives including activities, interests, andopinions’. Activities include actions such as work, hobbies, entertainment, shopping,sports, vacations, etc. while interests in objects, events or issues get manifested in thedegree of excitement that accompanies special and continued attention to matterslike family, food, fashion, job, home, community, recreation, achievements, etc.Opinions are beliefs on issues such as politics, education, products, culture, oneself,social matters, etc. The AIO framework seeks to measure activities, interests andopinions of the respondents by using long questionnaires with as many as 300 items(Wells and Tigert 1971).

The second wave of research seemed to replace the AIO approach with the valueconcept and researchers posited the importance of values in purchase behavior andsatisfaction (Oliver 1997). Values are desirable, trans-situational goals that differ inlevels of importance and serve to guide people in their lives. Kahle (1996) suggeststhat values are shaped by people’s experiences and social values are enduring beliefsthat drive behavior. The system of value dimensions known as Rokeach ValueSurvey or RVS proposed by Rokeach (1973) has been very widely used. He studied18 terminal and 18 instrumental values that he suggested impacted the determinationof attitude and behavior of consumers. The terminal values seek to measure therelative importance of personal goals while the instrumental values deal with themeans of reaching the end-state values. Kahle’s (1983) consumption-related List ofValues (LOV) developed at the University of Michigan Survey Research Centerincludes sense of belonging, excitement, fun and enjoyment, warm relationshipswith others, self-fulfillment, being well respected, a sense of accomplishment,security, and self-respect and has been employed in a number of studies. The LOVapproach is a parsimonious way to measure values as compared to the RVS andhence more easily implemented. Additionally, it contains items that people sayinfluence their daily lives (Kahle 1986) and posits that personal values are socialcognitions in abstract form that facilitate adaptation to one’s environment (Kahle,Kulka, and Klingel 1980; Kahle 1983) and make distinction between internal andexternal values. It was developed from a theoretical base of values proposed byMaslow’s (1954) hierarchy of values, Rokeach’s (1973) terminal values andFeather’s (1975) values.

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Lifestyle approach has evolved greatly in developed nations and the mostinfluential study has been perhaps that conducted by Arnold Mitchell and colleaguesat Stanford Research Institute on VALS – Value and Lifestyle profiles in 1983.VALS, though initially appreciated, was criticized later on. Hence, it was furtherrevised in 1988 and VALS II included eight groups: strugglers, believers, strivers,makers, fulfilled, achievers, experiencers and actualizers, based on several distinctvalue and lifestyle patterns. VALS typology assumes relationships between valuesand attitudes and behavior of the consumers. It seeks to point out differences inmotivation and reflects psychological as well as material constraints on buyerbehavior that may indicate cross-cultural or national differences. Some of the otherstudies include the Australian Age lifestyle studies (The Age 1976, 1982), ‘Outlook’,a British system (Baker and Fletcher 1987) and PRIZM, an American system(Hawkins, Best, and Coney 1989). Australian Age lifestyle study resulted in 15lifestyle groups while ‘Outlook’ typology classifies customers into six groups.PRIZM system is based on 62 life style clusters organized into 12 social groups.

The above discussion of the literature review may be summarized into threepertinent points. First, psychographic segmentation of the customers provides amulti-dimensional view about them and throws light on their underlying motives andaspirations behind the purchase and consumption of products and services. Lifestylepatterns corresponding to the consumers’ daily activities, interests, opinions, valuesand spending habits assist the marketer to make intelligent decisions in formulatingmarketing plans. Second, the lifestyle patterns of consumers are dynamic in natureand possess cultural and sociological connotations. This implies that the new lifestylepatterns are likely to emerge with the passage of time. Different instruments tomeasure lifestyle have evolved over a period of time in developed nations with AIO,LOV and VALS being the most popular tools among the researchers. Third, most ofthe research on lifestyle segmentation has followed a post-hoc model. The customersare first questioned about their lifestyles and then categorized into different groupsdepending upon the similarity/dissimilarity of their responses.

Methodology

The main purpose of the current study was to segment the Indian youth on the basisof psychographic variables like activities, interests, opinions and values. As discussedabove, the lifestyle scales have been well researched in developed nations and thestatements used therein have been culture specific. Hence, it was thought mostappropriate to adapt the scale so that it captures the psychographic profile of Indianyouth.

Research instrument

The first phase involved the development of a research instrument that profiles theyouth based on psychographics. The developed instrument comprised three sections.The first part dealt with statements on activities, interests and opinions while thesecond part based on LOV scale sought information on values important torespondents. Demographic information was elicited in the third part of thequestionnaire.

Statements used to develop the first part of the instrument were drawn fromextensive literature review of previous studies mentioned above; while LOV scale was

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employed for the second part of the research instrument. To ascertain whether thesame items could be included in the study, four focus group discussions and 10 in-depth interviews were conducted with youth. This resulted in the generation of alarge number of items overlapping with the statements in previous studies. Eighty-sixstatements on activities, interests and opinions were identified; and nine statementsbased on LOV were used for value determination. For the statements on activities,interests and opinions, a 7-point agree-disagree scale was employed where 1 stoodfor strongly disagree and 7 for strongly agree and a 9-point extremely important-extremely unimportant scale was used for LOV. The instrument was pretested on 30research associates of the University of Lucknow to make suitable modifications inthe framing of sentences. Subsequently, 170 young respondents between 16 and 26years were contacted outside a shopping mall to indicate their responses to thesestatements. One hundred and forty-three complete questionnaires were obtained thatwere factor-analyzed and tested for reliability using Cronbach’s alpha � 0.7 as anacceptable level in order to reduce the number of statements from 86 to 67, whichwas considered essential in the light of respondent disinterest, fatigue and non-cooperation likely to emerge in the event of a lengthy questionnaire (Churchill andPeter 1984; Cortina 1993). Subsequently, 67 statements on activities, interests andopinions and 9 statements on value were incorporated in the final researchinstrument.

The research instrument was administered on the youth from different collegesand a State University in the city of Lucknow and various analytical techniques suchas principal component analysis and Varimax rotation with Kaiser Normalization,chi-square test of association, cluster analysis and ANOVA analysis have beenemployed to analyze the data in a meaningful way.

Sample and data collection

The study was conducted among the young students of age group between 16 and 26years in the various colleges and a State University in Lucknow, the capital city ofUttar Pradesh, which is the most populous and fifth largest state of India. TheUniversities and colleges in Lucknow draw students in large numbers (0.12 millionapproximately) not only from within the city but also from adjoining towns, villagesand other smaller cities. Stratified sampling technique was employed for the study.The various academic institutions were stratified into government aided and privatecolleges/institutions. Great care was taken to ensure that the sample representedstudents from different courses such as management, engineering, commerce, generalstreams of science, humanities. Two hundred and seventy respondents werecontacted at random outside their college/university premises and the questionnaireswere self-administered by the respondents. Six questionnaires had to be rejected dueto incomplete responses resulting in 264 complete questionnaires. A majority ofrespondents were male (62.5%) and Hindi speaking (97%)2. About 93.93% of therespondents were Hindus; 54.16% of them hailed from general category, 39.77%belonged to other backward class while 5.3% were from scheduled caste. It may beworthwhile to mention that on the basis of social and economic condition, theGovernment of India classifies some of its citizens3 as ‘scheduled caste’ (SC),‘scheduled tribe’ (ST) and ‘other backward class’ (OBC). Indian law provides for thereservation of places for these socially and educationally backward classes of citizensin colleges, universities and workplaces so that they get properly represented in

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proportion to their numbers in general population. Caste is the criterion employed toidentify under-represented groups. In higher education institutions, 22.5% of seatsare reserved for scheduled caste (dalit) and scheduled tribe (adivasis) and 27% forother backward classes. General category includes those castes that do not fall underthe reserved categories.

Results and analysis

Scale properties

The factor analysis of the 67-item scale (activities, interests and opinions) on thebasis of principal component analysis resulted in 10 factors. One factor was droppedfrom further analysis as it did not possess an acceptable level of reliability score inthe form of Cronbach’s alpha. This resulted in dropping of eight statementson activities, interests and opinions. Subsequently, nine homogeneous sub-scales(Table 1) emerged. The scale had an overall Cronbach’s alpha value of 0.92. The sub-scales were named in accordance with their nature keeping in mind the items thathad higher loadings on a specific factor. Accordingly, the named factors were:Innovative leader; Pro-Politics Sport Lover; Fashion conscious compatible withopposite gender; Price conscious; Health conscious Community Lover; Religious-minded Conservative Homebody; Extrovert life-loving; Scientific InformationSeeker; Narrow interests. The total variance explained after rotation was 50.624%with communalities after extraction ranging from 0.287 to 0.794. The cut offCronbach’s alpha value for sub-scales was considered to be 0.5. Researchers (Daviesand Ware 1991; Bowling 1997; Tuckman 1999) have also considered alpha valuegreater than 0.5 to be acceptable.

Factor analysis of the nine items on values on the basis of principal componentanalysis resulted in two homogeneous sub-scales, external values and internal values(Table 2); these were very similar to two factors obtained by Kahle’s (1983) LOV.The scale possessed Cronbach’s alpha value of 0.88. The total variance explainedafter rotation was 63.25% with communalities ranging from 0.538 to 0.724. SPSSversion 13 software was used for performing all statistical analysis.

As indicated in Tables 1 and 2, nearly all items loaded on their respective factorconfirming the underlying structure of the data, the discriminant validity betweenscale items and the convergent validity among scale items (Gassenheimer, Davis, andDahlstrom 1998, 263). Later on, the 11 factors which evolved from factor analysiswere tested against the four clusters for significance of difference. Three tests offunctions resulted with Wilks’ lambda values ranging between .730 and .970. Thoughthe Wilks’ lambda values were quite high, for functions 1 to 3 the same was found tobe statistically significant thereby indicating that the group means appear to differ.

Cluster or segment formation

The nine interests, activities and opinions scale scores and two values scale scoreswere submitted to hierarchical clustering using Ward’s method and four clustersemerged as most acceptable. Initially, six clusters were generated but they did notdemonstrate distinguishable differentiation in properties. Subsequently, two to 10cluster solutions were examined but the four cluster results were found mostacceptable as they led to the emergence of well-defined clusters with differentiatingcharacteristics. Examination of the dendogram made the same suggestion.

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Table

1.

Scale

item

sandfactorloadingsforattitudes,interestsandopinions.

Variables

12

34

56

78

9

Innovativeleader

Ilikealotofvarietyin

mylife

.719

.137

.083

.029

.134

.022

.116

7.145

7.148

Ifollow

thelatest

trendsandfashions

.757

7.056

.206

.057

.146

.006

7.085

.014

7.173

Ilikebeingin

chargeofagroup

.487

.124

.294

.057

.134

.029

.141

7.355

7.075

Iliketo

learn

aboutart,culture

andhistory

.564

.031

7.027

.016

7.020

.029

.158

7.002

.262

Ioften

craveexcitement

.683

.026

.130

.110

7.005

.084

.045

.151

.222

Ihavemore

abilitythanmost

people

.729

.157

.059

.187

.191

7.019

7.016

7.022

7.077

Iliketryingnew

things

.642

.147

.162

7.240

.018

7.020

.206

7.211

7.015

Iliketo

dress

inthelatest

fashions

.549

7.012

.293

7.108

.061

.150

7.149

7.024

.206

Iliketo

leadothers

.476

.005

7.154

.012

.378

7.013

.070

7.115

.165

Iwould

liketo

spendayearormore

inaforeigncountry

.496

.092

7.167

7.029

7.089

.030

7.022

7.129

.105

Ilikealotofexcitementin

mylife

.557

7.029

.090

.077

.138

.011

.188

.105

.385

Ilikemakingthingsoutofwood,metalorother

such

material

.401

.223

.047

.002

.018

.161

7.122

.131

.132

Iwantto

beconsidered

fashionable

.550

.148

.281

7.053

.033

7.015

7.234

.216

.245

Ilikethechallengeofdoingsomething

Ihavenever

done

before

.534

7.063

.044

.092

.160

.048

.472

7.044

.031

Iliketo

learn

aboutthingseven

ifthey

maynever

beofanyuse

tome

.324

.176

7.030

.140

7.268

.248

.251

.255

.197

Iliketo

makethingswithmyhands

.493

.185

7.267

.222

7.091

.048

.220

.087

7.131

Iam

alwayslookingforathrill

.568

.153

.052

.341

7.027

.137

.154

.119

7.077

Ilikedoingthingsthatare

new

anddifferent

.507

.158

.015

.022

.066

.252

.385

.011

7.047

Pro-politics,sport

lover

Iliketo

lookthroughhardware

orautomotivestores

.139

.493

.032

.092

.277

.044

7.163

.314

.281

Ihavepersonally

worked

ina

politicalcampaign

orfora

candidate

oranissue

.063

.533

.181

.193

.116

.358

.084

.004

7.091

Ispendalotoftimetalkingwithmyfriendsaboutproducts

andbrands

7.079

.379

.352

.078

7.009

.361

7.038

.162

7.154

Iparticipate

insportsactivitiesregularly

.089

.644

7.060

.039

.008

.189

.216

7.076

.005

Ifrequentlyuse

vitaminsandmineralproductsto

keepfit

.170

.619

7.033

.016

.273

.033

7.147

7.100

7.081

(continued)

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Table

1.

(Continued).

Variables

12

34

56

78

9

People

likemeare

wellqualified

toparticipate

inpolitical

activityanddecisionmakingin

ourcountry

.139

.603

.154

7.157

7.119

7.057

.146

7.011

.127

Iwould

rather

goto

asportingeventthanadance

7.037

.568

.094

.147

.006

.280

.108

7.048

.122

Ido

volunteer

work

for

ahospitalor

socialservice

organizationonafairly

regularbasis

.161

.644

.107

.143

.292

7.106

7.053

.275

7.005

Iliketo

watchorlisten

tocricket

orfootballorhockey

.189

.524

7.318

7.026

.361

7.173

7.048

.013

.086

Ilikemylife

tobeprettymuch

thesamefrom

weekto

week

7.112

.316

.096

.313

.186

.219

7.031

.053

7.201

Idonotbelievein

practicingritualsin

religion

.029

.478

.206

.127

7.265

7.132

7.147

.189

7.053

Fashionconsciouscompatible

withopposite

gender

Idress

more

fashionably

thanmost

people

.428

.105

.463

.011

7.231

.093

7.327

.025

.185

Iusuallyhaveoneormore

outfits

thatare

oftheverylatest

style

.146

7.019

.548

7.011

.346

7.042

7.046

.168

.179

Ioften

trythelatest

hairdostyleswhen

they

change

.251

.254

.481

7.021

7.052

.041

7.111

.134

.086

Iam

alwayson

thelookoutfornew

productsthatsuit

my

requirem

ents

better

.065

.042

.544

7.083

.157

.117

.308

7.171

.183

Ioften

buyproductsthatare

new

inthemarket

sooner

than

myfriends

.045

.224

.585

.077

.118

.172

7.097

7.023

7.095

Ihavelots

offriendsoftheopposite

gender

.144

.035

.632

.284

.058

7.292

.171

.136

7.046

Ienjoycompanyofopposite

gender

.079

7.028

.397

.152

.290

7.129

.213

.132

7.166

Priceconscious

Ifindmyself

checkingthepricesin

thestore

even

forsm

all

item

s.023

.023

7.029

.837

.125

.075

.047

.023

7.113

Iusuallywatchtheadvertisements

forannouncements

ofsales

.130

.309

.506

.533

7.179

7.034

.130

7.110

.051

Ifindmyselfcheckingthepricesin

thestore

foralltypes

of

item

s.132

.003

7.020

.858

.078

.135

7.007

7.040

.021

Iusuallywait

fortheadvertisements

forannouncements

of

sales

.168

.245

.463

.621

7.179

7.062

.127

7.035

.203

Ispendmyspare

timeveryactively

.166

.130

.091

.259

7.050

.007

.011

7.610

.015

Iliketo

spendmyfree

timein

pursuingindooractivities

.106

.081

.189

.515

.209

.049

7.236

.140

.224

(continued)

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Table

1.

(Continued).

Variables

12

34

56

78

9

Healthconsciouscommunitylover

Anim

portantpart

ofmylife

andactivitiesisdressingsm

artly

.238

7.090

.184

7.101

.243

.152

.013

7.136

7.196

Iliketo

work

oncommunityprojects

.303

.116

.080

.135

.556

.212

.163

7.112

7.064

Iwould

characterizemyselfasbeingveryslim

ness-oriented

.207

.125

.205

.205

.324

7.017

7.312

7.294

7.260

Multivitaminsare

importantsupplements

todailynutrition

.080

.239

7.101

.047

.468

.264

7.102

7.127

.206

Myfriendsorneighbors

often

cometo

meforadvice

.053

.169

.172

.103

.679

7.074

.145

.085

.045

Religiousminded,conservativehomebody

Iliketo

paycash

foreverythingIbuy

.116

.089

7.054

7.066

7.013

.599

.431

7.109

.120

Thereistoomuch

sexontelevisiontoday

.334

.032

7.192

.189

.147

.609

.096

.081

.066

Iwould

rather

spendaquieteveningathomethangooutto

aparty

.248

.045

.214

7.118

.375

.516

.107

.081

7.015

Iam

ahomebody

.058

.181

7.038

.068

7.028

.720

7.074

7.033

7.009

Iam

religiousminded

7.058

.007

.160

.343

7.090

.510

7.145

.260

7.026

Extrovert

life-loving

Iliketo

havecompany

.219

.222

.144

.108

.196

.091

.691

7.107

.019

Iwantto

enjoylife

tothefull

.388

7.056

.236

7.035

.328

.011

.443

.005

.168

Scientificinform

ationseeker

Iam

veryinterested

inhowmechanicalthings,such

asengines,

work

.450

.315

.153

.049

7.057

7.042

7.067

.520

7.203

Iwould

liketo

understandmore

abouthowtheuniverse

works

.195

.324

.058

.020

.157

.094

.093

.686

7.088

Narrow

interests

Ionly

eatvegetarianfood

.137

.154

.075

.166

.153

7.167

.148

.185

.490.

Iam

reallyinterested

only

inafew

things

7.001

.077

.077

.077

7.136

.110

7.048

7.233

.675

Imust

admit

thatmy

interestsare

somew

hatnarrow

and

limited

7.034

.217

.187

.112

7.100

.331

7.271

7.057

.510

Variance

Explained

(%)

11.05

7.45

5.95

5.44

4.62

4.56

4.15

4.05

3.67

Eigen

values

7.4

5.0

4.0

3.6

3.09

3.06

2.8

2.7

2.3

Cronbach’salphavalue

.88

.82

.71

.81

.51

.65

.64

.61

.59

Principalcomponents

factoranalysis,

VarimaxrotationwithKaiser

Norm

alizationresultsofactivities,

interestsandopinionsstatements

withcorrespondingCronbach’s

alpha

scoresandfactorloadingsofitem

s.Therotationhadconverged

in25iterations.

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Moreover, K-means mode of non-hierarchical clustering was examined for clustersranging from two to 10. However, hierarchical clustering using Ward’s methodprovided more meaningful solutions. Therefore, four clusters were accepted andcharacterized as Get-going Adopter, Inner Value-oriented Conservative, Politicaland Sport Enthusiast and Independent Life Lover. The characteristics of theseclusters are summarized as follows:

Cluster 1: get-going adopter

This segment comprising 42% of the respondents is extremely fond of company, likesexcitement and wants to enjoy life to the full. The Get-going Adopters are fashionconscious who try new things, like a lot of variety in their lives and want to learnabout art, culture and history. They like to be in charge of a group and feel that theypossess more ability than most people. They are somewhat curious about the workingof the universe as well as mechanical things such as engines. They like the challenge ofdoing something that they have never done before and would want to spend a year ortwo in a foreign country. They are on the lookout for new products that suit theirrequirements better and often buy products that are new in the market sooner thantheir friends though they are slightly price conscious. They have some friends ofopposite gender and enjoy their company. They are somewhat disillusioned withpolitics, have weak value sets and believe in practicing rituals in religion.

Cluster 2: inner value-oriented conservative

Twenty percent of the respondents constitute this segment which is neither aninnovative leader nor fashion conscious. Inner Value-oriented Conservative is notmuch interested in understanding the workings of the universe or the operations ofmechanical things and enjoys being inactive in spare time. Furthermore, they aredisinterested in both sports and politics. However, the youth in this segment possessesa very well defined set of internal values, is religious-minded and feels that there is too

Table 2. Scale items and factor loadings for values.

Variables 1 2

External values

Sense of belonging .828 .088Excitement .773 .267Fun and enjoyment .743 .297Warm relationships with others .722 .128Being well respected .589 .529

Internal values

Self-fulfillment .501 .548A sense of accomplishment .221 .759Security .270 .743Self-respect .046 .850

Variance explained (%) 34.19 29.06Eigen values 3.08 2.62Cronbach’s alpha value .84 .79

Principal components factor analysis, Varimax rotation with Kaiser Normalization results of valuesstatements with corresponding Cronbach’s alpha scores and factor loadings of items.

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much sex on television currently. They characterize themselves as being very slimness-oriented who consider that multivitamins are important supplements to dailynutrition though they hardly use them. They enjoy working on community projects,attracting friends and neighbours who often seek their advice. However, they find itslightly difficult to make friends with the opposite gender. They thoroughly enjoygoing out and believe in cash payment for making purchases.

Cluster 3: political and sport enthusiast

They constitute 10% of the respondents and have somewhat narrow and limitedinterests with only external value orientation. They are disinclined towardinnovation and prefer their lives to be pretty much the same from week to week.Political and Sport Enthusiasts are disinterested in latest fashion, hairdos and newproducts and are not keen for the company of the opposite gender and find it difficultto make friends with them. They are vegetarians and do not believe much inpracticing rituals in religion. However, they are extremely interested in politicalactivities and decision making of the country and participate in a political campaignfor a candidate or an issue. They exhibit high interest in sports activities and enjoywatching or listening to cricket, football or hockey and like to participate in sportsactivities. They enjoy looking through hardware or automotive stores and sometimesuse vitamins and mineral products to keep fit.

Cluster 4: independent life lover

This segment is highly innovative and fashionable wanting to outdo others in fashionand latest hairstyle. Twenty-eight percent of the respondents comprise IndependentLife Lovers who crave excitement, variety and thrill, thriving on challenges, leadingothers, trying out new things with high sense of belief in self-abilities. The youth inthis segment exhibit strong liking for a lot of variety in their life and are extremelydesirous to learn about art, culture and history. They enjoy making things with theirhands particularly of wood, metal or other such material and like to learn aboutthings even if they may never be of any use to them. They are extremely curiousabout the working of the universe as well as the mechanical things such as engines.Youth in this segment thoroughly enjoy political participation and are great sportslover. They frequently use vitamins and mineral products to keep fit and workvoluntarily for a hospital or social service on a regular basis. They find it extremelydifficult to make friends with the opposite gender though they thoroughly enjoy theircompany and do not believe in practicing religious rituals despite being veryreligious-minded. In addition to being interested in latest products and fashion, theyare very price conscious and check prices in the store even on small items and usuallywatch the advertisements for the announcement of sales to ensure that they get valuefor their money. They are very active in spare time and enjoy spending time at home.

Differences among clusters

Statistically, no significant inter-cluster differences were seen among different clusterswith respect to age, caste, language, religion and income. However, a significantdifference among clusters was observed in case of gender (.013) with a chi-squarevalue of 10.808 at 3 degrees of freedom (Table 3). It was observed that in Clusters 3

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and 4, the proportion of males was significantly higher as compared to Clusters 1and 2. It was interesting to note that in Indian society females are neither tooinnovative (Cluster 4) nor are they disinclined toward innovation (Cluster 3). Theyare by and large, either ‘Get-going Adopter’ or ‘Inner value-oriented Conservative’.

ANOVA analysis and 95% confidence intervals for each set of data wereemployed to identify the psychographic differences among clusters and the extent ofsuch differences (Table 4). Statistically significant differences were seen for the meanscore on ‘Innovative Leader’ among different clusters. It was observed that Cluster 4had the maximum mean value while Cluster 3 had minimum value for this attribute.For the attribute ‘Pro-Politics, Sport Lover’, statistically significant differences inmean scores were seen among different groups (p ¼ .001). The maximum mean scorewas seen for Cluster 4 while minimum was seen for Cluster 2. Statistically significantdifferences in mean scores were seen among different groups (p ¼ .003) for theattribute ‘Fashion conscious compatible with opposite gender’ as well. Themaximum mean score was seen for Cluster 4 while minimum was observed forCluster 3. Statistically significant differences in mean scores were reported amongdifferent clusters (p ¼ .001) for the factor ‘Price conscious’. The maximum meanscore was seen for Cluster 4 while minimum was recorded for Cluster 2. However, nostatistically significant differences among various clusters were noticed for theattribute ‘Health conscious community lover’. Cluster 1 had the maximum scorefollowed by Cluster 4, Cluster 2 and Cluster 3. Moreover, no significant differenceamong clusters was seen for any of the five items under ‘Religious minded,conservative homebody’ attribute except for one item ‘I am a homebody’. Cluster 4had maximum score while Cluster 2 had minimum score. Statistically significantdifferences (p ¼ .013) among different clusters were seen for the attribute ‘extrovertlife-loving’ with Cluster 1 showing the maximum score followed by Cluster 4, Cluster3 and Cluster 2, respectively. The differences among different clusters were significantstatistically for the item ‘I like to have company’. No statistically significantdifference could be observed among different clusters for the attribute ‘Scientificinformation seeker’ (p 4 .05) though the mean value of Cluster 4 for this attributewas maximum followed by Cluster 1, Cluster 3 and Cluster 2 in that order. For theattribute ‘narrow interests’, statistically significant differences were reported amongdifferent clusters with Cluster 4 showing maximum score and Cluster 1 showing theleast.

Table 3. Differences among clusters: gender wise.

Gender

Clusters

Total1 2 3 4

Male 63 27 17 58 165Female 47 25 10 17 99Total 110 52 27 75 264

Value df Asymp. sig. (2-sided)

Pearson chi-square 10.808a 3 .013Likelihood ratio 11.261 3 .010No. of valid cases 264

a0 cells (.0%) have expected count less than 5. The minimum expected count is 10.13.

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Table

4.

Attitudes,interests,opinionsandvalues:differencesamongclusters.

Factors

Cluster

NMean

SD

SE

95%

CI

Min

Max

F‘p’

Lower

bound

Upper

bound

Innovative

leader

1110

1.139

.881

.084

.972

1.305

72.235

2.778

5.587

0.001

252

.937

.894

.124

.689

1.186

7.889

2.333

327

.553

1.311

.252

.035

1.072

72.235

2.000

475

1.307

.622

.072

1.164

1.451

7.889

2.333

Total

264

1.087

.896

.055

.978

1.196

72.235

2.778

Pro-politics,

sport

lover

1110

.519

.991

.094

.332

.706

72.308

2.308

5.587

.001

252

.326

1.011

.140

.045

.608

71.923

2.250

327

.654

.862

.166

.313

.995

71.308

1.769

475

.842

.935

.108

.627

1.057

72.308

2.154

Total

264

.587

.979

.060

.468

.705

72.308

2.308

Fashion

conscious

compatible

with

opposite

gender

1110

.756

1.048

.100

.558

.954

72.857

2.714

4.895

.003

252

.690

.831

.115

.459

.922

71.286

2.429

327

.465

1.324

0.255

7.059

.988

72.857

2.000

475

1.165

.743

0.086

.994

1.336

71.571

2.714

Total

264

.829

.984

.061

.710

.949

72.857

2.714

Price conscious

1110

.997

1.114

.106

.787

1.208

73.000

3.000

5.996

.001

252

.415

1.471

.204

.006

.824

73.000

2.333

327

.886

1.007

.194

.488

1.285

71.833

2.333

475

1.247

.769

.089

1.070

1.424

72.250

2.333

Total

264

.942

1.133

.070

.805

1.079

73.000

3.000

Health

conscious

community

lover

1110

2.045

1.192

.114

1.820

2.271

73

32.424

0.066

252

1.731

1.622

.225

1.279

2.182

73

33

27

1.333

1.494

.287

.742

1.924

73

34

75

1.787

1.142

.132

1.524

2.050

73

3Total

264

1.837

1.317

.081

1.678

1.997

73

3

(continued)

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Table

4.

(Continued).

Factors

Cluster

NMean

SD

SE

95%

CI

Min

Max

F‘p’

Lower

bound

Upper

bound

Religious

minded,

conservative

homebody

1110

.781

1.004

.096

.591

.971

71.600

3.000

.959

.413

252

.555

1.070

.148

.257

.853

71.500

3.000

327

.776

.811

.156

.455

1.097

7.800

2.000

475

.859

1.061

.122

.615

1.103

71.600

2.600

Total

264

.758

1.016

.063

.635

.881

71.600

3.000

Extrovert

life-loving

1110

1.955

.959

0.091

1.773

2.136

73.000

3.000

3.641

.013

252

1.375

1.527

.212

.950

1.800

73.000

3.000

327

1.389

1.416

.273

.829

1.949

73.000

3.000

475

1.680

1.114

.129

1.424

1.936

73.000

3.000

Total

264

1.705

1.200

.074

1.559

1.850

73.000

3.000

Scientific

Inform

ation

Seeker

1110

1.195

1.448

.138

.922

1.469

73.000

3.000

1.942

.123

252

.798

1.566

.217

.362

1.234

73.000

3.000

327

.815

1.539

.296

.206

1.424

73.000

3.000

475

1.327

1.209

.140

1.048

1.605

73.000

3.000

Total

264

1.116

1.427

.088

.943

1.288

73.000

3.000

Narrow

interests

1108

.151

1.434

.138

7.122

.425

73.000

3.000

5.170

0.002

251

.412

1.495

.209

7.009

.832

73.000

3.000

325

.547

1.343

.269

7.008

1.101

72.333

2.333

474

.941

1.042

.121

.700

1.183

72.333

3.000

Total

258

.468

1.369

.085

.300

.636

73.000

3.000

Note:Fconnotesproportionofbetweengroupdifferencesandwithin

groupdifferences(A

NOVA)atp5

0.05.

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Maximum mean score for external values was observed for Cluster 3 followed byCluster 1, 4 and 2. Statistically significant differences were seen among the clusters(p 5 .001). For items ‘sense of belonging’, ‘excitement’, ‘fun and enjoyment’ and‘being well respected’ significant inter-cluster differences were seen with Cluster 3revealing maximum scores for these items. For internal values Cluster 2 hadsignificantly higher mean score as compared to other clusters while Cluster 3 showedminimum mean score. Statistically significant inter-cluster differences were noticedfor items ‘self- fulfillment’, ‘security’ and ‘sense of accomplishment’. Cluster 4 hadmaximum score for the first two of these items whereas Cluster 2 had maximumscore for the last item. For all the items, Cluster 3 had minimum scores (Table 5).

Discussion

The paper sought to develop a psychographic profile of Indian youth and thereafterdevelop an understanding of these segments for marketing purposes. The fourclusters identified were addressed as Get-Going Adopter, Inner Value-orientedConservative, Political and Sport Enthusiast and Independent Life Lover.Psychographic variables were found to be more useful than demographic factorsin discerning differences among the clusters. Chi-square results pointed out that onlyone out of six demographic variables was significant while multivariate analysisrevealed that eight out of 11 psychographic variables were significant in revealingdifferences among different segments. Gender was found to be the only significantdemographic factor. However, a large number of psychographic factors accountedfor distinction among the various segments.

The identification of different clusters of youth consumers brought to the fore thefact that a large majority of them (42%) are Get-going Adopters. They exhibitsimilarities to the ‘fashion-oriented consumers’ in China (Forest Ma 2004) and‘Contemporary Seekers’ found in Thailand, Malaysia and Philippines (Ewing, deBussy, and Leyland 1998). They are extroverts, fashion conscious and compatiblewith the opposite gender. They possess a weak value set, low political consciousnessand are keen to try out new things. They follow innovators and are not trendsettersthemselves like their Chinese counterparts and the ‘Contemporary Seekers’ therebyimplying that that the marketers can attract them by using a Role Model forendorsement in their communication strategy – a role model can be an innovator inthe society, a sportsperson, a cinema star or even a young politician. Though theGet-going Adopters are price conscious they always have some extra money in theirpocket so disguised pricing can be a suitable alternative to beguile them. Their beingextrovert and life loving provides a significant cue to the marketer. If the latter issuccessful in attracting some such youth then more of them are likely to follow as achain reaction. As these youth are desirous to acquire knowledge about things, themarketer must utilize this opportunity to push more information toward them andreinforce it. Before long they are likely to keep themselves very well informed aboutthe marketer and his offerings. As they exhibit wide interests, they can be luredtoward a large variety of products. For instance, these youth may be very interestedin a brand new mobile phone with camera and at the same time show keen interest ina book on philosophy. This makes the marketer’s task both easy as well as difficult –one doesn’t know when what will click to them yet at the same time considering theirlarge size one is sure that something will appeal to some of them. The weak valuesthey hold make them less reliable as they can easily switch over to other brands or

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Table

5.

Values:differencesamongclusters.

Factors

Cluster

NMean

SD

SE

95%

CI

Min

Max

F‘p’

Lower

bound

Upper

bound

Externalvalues

1109

1.308

2.270

.125

72.021

2.518

73.6

46.658

5.001

251

.787

2.416

.110

72.194

2.637

.63.8

327

2.013

1.193

.387

7.396

1.989

73.6

3.4

475

.959

2.219

.111

71.998

2.439

71.0

4.0

Total

262

1.268

2.173

.078

72.018

2.327

73.6

4.0

Internalvalues

1109

2.738

.940

.090

2.559

2.916

.04

4.886

.003

251

2.998

.750

.105

2.788

3.209

.75

43

27

2.111

1.571

.302

1.490

2.733

72.75

44

75

2.800

.937

.108

2.584

3.016

72.75

4Total

262

2.742

1.011

.062

2.619

2.865

72.75

4

Note:Fconnotesproportionofbetweengroupdifferencesandwithin

groupdifferences(A

NOVA)atp5

0.05.

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stores. A shopping mall or arcade can successfully meet their requirements of largevariety of new products. Although Get-going Adopters are price conscious they tendto spend money without knowing the actual worth of the product. Goods that maybe priced high but available in sale seem a good deal to this segment. It has beenobserved that this kind of pricing strategy is being successfully adopted in the Indianshopping malls. The retailer must remember that they are not the leaders but theadopters. They seek novelty and excitement from the products that they consume butare likely to be motivated by the traditional Indian customs, manners, festivals andtraditions. To attract them the retailers may take advantage of discounts and specialoffers during festivities to push variety of new offerings.

The large chunk of Get-going Adopters is followed by a substantial number ofshrewd and intelligent buyers ‘Independent Life Lover’ (28%) who are quite similarto ‘Kampong Trendsetters’, young Malaysian males (Survey Research Malaysia1990) and ‘Achievement-oriented consumers’ in China (Forest Ma 2004). Moses(2000), who has utilized the results of a study of more than 27,000 teenagers in 44countries and offered insights into the today’s teens, has identified the presence of‘Bootstrappers’, a youth segment present in Nigeria, Mexico, United States, Chile,Puerto Rico, Peru, Venezuela, Colombia and South Africa that compares very wellwith the Independent Life Lovers identified in this study. They are innovativeleaders, politically alert, sport lover, health and fashion conscious, religious minded,not so much of an extrovert but an information seeker with flexible value set butunlike the ‘Achievement-oriented consumers’ and the ‘Bootstrappers’, is very priceconscious. This gives a picture of a person with strong psychographic profile – who isalert to changes taking place in the environment and knows how to derive value fromhis money. They are sharply focused in their life with narrow interests and do notdeviate easily. Independent Life Lovers are somewhat value-oriented but do notalways adhere to them. This feature differentiates them from the ‘Bootstrappers’ whowant to play by society’s rules to succeed and ‘brands that convincingly connect tothe positive values of the good life will stand a strong chance with these teens’. Withthese characteristics, one can find Indian youth who may be very difficult to tap, butonce tapped, they do not change fences easily, that is, one can bank upon them. Butto keep them tamed one has to be always continuously up grading the old productsor introducing technologically advanced products thereby ensuring the supply ofnew products for the trend setters who would get dissuaded by ‘out of fashion’products. The retailer must not only furnish sufficient information to theseinformation seekers for the products and services being marketed but also employinnovative techniques to attract them. Specialty stores particularly the categoryspecialists are likely to attract the ‘Independent Life Lover’ as they seek exclusiveproducts at best possible price. Department stores in terms of the services they offerand the shopping experience created can also lure this segment into the stores andmake sales through special promotional offers particularly during festive season.

The next cluster, Inner Value-oriented Conservative (20%) comprises thereluctant buyers as they are disinterested in trying out any new thing; rather theyare happy with whatever they are doing. Even trying to convince them can be futile.They are highly religious with strong internal values, largely unconcerned aboutfashion and do not try to come out of their shell. Their interests are not very wideand even if they do try something new they don’t bring significant amount ofbusiness. From a marketer’s point of view, they are the most difficult and at the sametime least revenue-generating customers. Inner Value-oriented Conservative segment

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is very similar to the ‘Not-Quite-Theres’ youth segment identified by SurveyResearch Malaysia (1990) in a psychographic study in Malaysia except that the latterprefers involvement in sport activities. It exhibits some similarities to the ‘Upholders’(Moses 2000) found predominantly in Vietnam and Indonesia that value oldtraditions and extended family relationships and ‘do not like to take consumer risks’.They may be easily dismissed by the modern marketer but are of great importance tothe neighborhood or traditional stores. The fact that they do not experiment and aretoo conservative in approach is indicative of their being a loyal customer. Once theystart a buyer-seller relationship, they do not easily break it for the lure of somediscount or want of something new. Their demands are very limited and are easilysatisfied with the limited stocks a neighborhood retailer can afford to maintain. InnerValue-oriented Conservatives enjoy being given importance and heard patiently.Appreciating their community-serving behavior and their efforts in keeping the valuesystem intact is likely to ensure their repeat visits. They are unlikely to becomfortable in big shopping malls. The neighborhood retailer who can build strongrelationship bonds with them is best suited for this segment.

A small chunk of youth, Political and Sport Enthusiasts (10%) consists of thosewho are ‘non-experimenter’ buyers. They are least interested in being innovators orfashion conscious. They can be perhaps judged as followers. To attract them themarketer needs to tap the Get-going Adopter and Independent Life Lover. Nospecial set of marketing strategy is required for them as they get pulled according totheir requirement but what needs to be kept in mind is that they would buy theproducts their friends/relatives are using rather than pick a new one for trial even if itpromises better performance. This set of buyers seems to give a run for money to aretailer. First, their purchases are limited and second, they prefer to make them oncredit. However, they do not demand much in terms of product innovation and canbe served best by the traditional retail formats like ‘mom and pop’ and ‘kirana’stores.

The above discussion reveals that it is more meaningful for the modern marketerto concentrate on two segments, ‘Get-going Adopter’ and ‘Independent Life Lover’that account for 70% of the respondents rather than the other two clusters, ‘InnerValue-oriented Conservative’ and ‘Political and Sport Enthusiast’. ‘Inner Value-oriented Conservative’ accounting for 20% of the respondents is of least significanceto the marketer. While promoting products and designing communication strategy,the marketer must keep in mind the lifestyle of ‘Get-going Adopter’ and‘Independent Life Lover’ groups. This knowledge can also be successfully utilizedby the store in adoption of retail mix strategy in conjunction with additionalinformation.

Conclusion and directions for future research

The Indian retail market which offers tremendous potential to the modern marketeris largely driven by enhanced income, changing lifestyles and emergence of youth asa powerful consumer segment. The current study has been successful in meeting itsobjective of drawing up a psychographic profile of Indian youth and developingvaluable insights into their lifestyle. The findings are consistent with those of earlierstudies (Cooper 1984; Anandan, Prasanna, and Madhu 2006) which had emphasizedthe greater relevance of the psychographic segmentation in drawing comparisonsamong different customer groups to the marketer, rather than the demographic

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segmentation. The study has demonstrated that the psychographic segmentation isable to provide deeper insights into the leisure behavior, motives, interests andactivities encompassing daily life of different segments of Indian youth. This can helpthe marketer to draw more meaningful and effective marketing strategies. Thisconclusion finds support from earlier studies (Moschis 1976; Bearden, Teel, andDurand 1978; Cooper 1984; Ewing, de Bussy, and Leyland 1998; Forest Ma 2004).

The four clusters of Indian youth identified in the study were found to possesssome similarities with their counterparts in other developing nations. However,despite strong identification with some clusters there were some discernabledifferences as well. For instance, a ‘fashion-oriented consumers’ youth segment inChina identified more closely with ‘Contemporary Seekers’ of Thailand, Malaysiaand Philippines than their Indian counterpart ‘Get-Going Adopters’. Similarconclusion has been reached for ‘Independent Life Lover’ of India who despite closeresemblance to ‘Achievement-oriented consumers’ of China and ‘Bootstrappers’ ofother developing nations is different in terms of sensitivity to price. The researcher,however, could not identify any youth cluster in the above-mentioned studies thatcould compare well with a very distinct Indian segment ‘Political and SportEnthusiasts’. This implies that there may be some overlapping characteristics in youthacross the developing nations but the marketer needs to exercise prudence in luringIndian youth who may be eager to demonstrate their identity and adopt latest fashionbut his purchases are governed by prices. Ignoring this difference could pose risks forthe marketer against which they need to be cautioned.

To conclude, it may be said that the current study has made a valuablecontribution to the existing literature by identifying psychographic clusters ofIndian youth with distinct characteristics apart from providing direction to themodern marketer who may devise the marketing communication and promotionstrategies accordingly. However, though great care was exercised in selecting thesample representative of the population, it is possible that the sample results mayhave failed to capture the population characteristics as the study was based inLucknow only. Another limitation of the study is that the purchase frequency ofthe different products by these segments has not been studied. Further research canbe carried out to identify the products purchased by the different psychographicsegments of youth for their personal consumption and the frequency of suchpurchases. Store selection criterion adopted by the different psychographic clustersof the youth could also be researched upon in order to formulate the store retailstrategy. Furthermore, the shopping orientation of these clusters in relation tostore variables such as merchandising, location, service and communication couldalso be explored.

Notes

1. 1 US dollar ¼ 45 Indian rupees approximately (May 2010).2. Hindi is the principle language spoken in Lucknow.3. The Government of India has officially documented castes and sub-castes in order to

provide reservation or positive discrimination in education and jobs to socially andeconomically backward people of the country. The framers of the Indian Constitutionopined that due to prevalence of the caste system in the country Scheduled Castes (SC)and Scheduled Tribes (ST) were historically oppressed and denied equal opportunity innation-building activities. They provided for 15% and 7.5% of vacancies as reservedquota for the SC and ST candidates respectively for a period of five years in 1950. Thisreservation was applicable for admission to government aided educational institutes and

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jobs in the government/public sector,. However, the succeeding governments havecontinued to extend this policy of reservation till today and have also included otherbackward classes by providing reservation to them to the level of 27%. Scheduled Castescomprises ‘untouchables’ or ‘Dalit’, Scheduled Tribes consists of tribal groups and OtherBackward Classes covers more than 3,000 castes. The Supreme Court (apex court of thecountry) has put a cap on this reservation at 50%. General category comprises forwardcastes that do not qualify for reservation. This has caused resentment among the forwardclass who complain of reverse discrimination.

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