ananto case synopsis_customer experience_agony threshhold

7/27/2019 Ananto Case Synopsis_Customer Experience_Agony Threshhold

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Ananto Case Synopsis

IdentifyingAgony Threshold

to enhanceCustomerServiceExperience

Case Synopsis


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Introduction

Harnessing data to predict customer choices is a tricky combination of art and science; it

gets trickier and harder when we try to narrow the field to what one given person would

want, versus a likely outcome of the choices of a large group of people. In the present

scenario of volatile market and fast changing customer mindset and expectations, customer

oriented strategies are the key to competitive differentiation. Determination of the

likelihood of customer churn and Propensity to buy are classical tactical strategies

adopted by retail industry to safeguard the firms revenue interests. Increasing the

prediction of customers behavior, analysis of BIG DATA and other consumer centrictechniques have been gaining ground in the recent past. This has enabled the firms to

predict outcomes using the science of consumers behavior and reactions.

Understanding the Challenges in Business Processes

A large consumer product company uses online forums and consumer complaints sites to

monitor negative feedback about its brands. The company strongly believed in the

ingenuity and true nature of such feedback, however, soon they realized that these

comments were also a matter of reputation management. Unlike the real world, where

consumer complaints are known only to customer and the brand, any negative comment in

digital media has significant magnification leading to loss of present and potential client in

the future. Comments are not only read by the one who posts but also by other users of the

brand and prospective users as well. While most firms in this space focus on responding to

negative comments and treating this issue as customer service, this specific firm decided to

go one step ahead by figuring out how to reduce negative comments.


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This consumer product company has more than 6 million customer base. They already had

the following process in place:

Extraction: A third party service provider used to extract comments only frombrands own sites. These comments were sent to customer service team of the brand

as batch file at the end of a day.

Case Initiation: Only for the cases where the consumer provided necessary details,customer service team issued trouble tickets, which were routed to specific teams

Consumer Engagement:o Where consumer provided contact details, contact center executives used to

call customer, listen to the complaint once again, resolved the problem or

provide a road map to resolution.

o Once the complaint resolution report wasgenerated, the customer care team updated the

specific blog with a case closure script.

Consumer Feedback measurement: Though theintention was to seek consumer feedback on the same

blog where the consumer initiated the complaint, no specific team was found

responsible to ensure that this happened. Invariably after resolution, there was no

digital imprint of action taken.

Analysis and Process Improvement: Existing analysis practice was largely focusedon measurement, ignoring more important insights. Insights if analyzed could

provide guidance for process improvements, eliminating similar complaints.


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With the help of descriptive analytics, different trends and patterns of consumerengagement were found and segmented by geography, product, nature of complaint,

life stages, and various other

attributes

The analytics team thendetermined consumer behavior

dimensions that were key drivers

of the negative comments. Positivecomments key driver analysis was

also done to judge propensity to

increase positive sentiments

This provided us with the abilty to build predictive models to determine the AgonyThreshold of consumers

The model was deployed every day on the freshly mined dataset. Two lists ofconsumers with negative sentiments and others with positive sentiments was

generated. A reach-out was made to those having negative sentiments.

Once every quarter, the model was recalibrated to align with changed variables likekey drivers, degree of influence.

A revised performance measurement matrix was put in place, some of the included

parameters were:

o Negative comment rate on social mediao Positive comment rate on social mediao TAT improvement on service


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Key Benefits

Proactive engagement with consumers with negative sentiments. Better-quality complaint resolution time (TAT improved from 3 days to few hours) Proactive reach-out to customers, many were pleasantly surprised with this

proactive gesture.

Identification of key drivers for improved customer satisfaction. Reduction in negative comments about the brand, month over month (by >15%)

and increase in brand imagery scores

About Ananto

Ananto is Big Data Analytics Solutions and Services Company, supporting firms with Data

Insight, Predictive Intelligence, Technology Integration and Advisory and Professional

Solutions and Services.

The word Ananto means Infinite, depicting the very nature of endless possibilities of

business solutions that can be achieved using effective analytics.

Our mantra is to convert your data to dollars. Data itself has no value, unless it can be

harnessed smartly and transformed into deeper consumer insight and channelized

towards enhancement in productivity and efficiency. This deep insight into data can help

organizations to Re-focus, Re-align, Re-engineer and be Relevant and Resilient.

Started by customer experience industry veterans with global experience in technology,

process management, consulting and business solutions. In his last assignment, AparupSengupta was the CEO and MD and Anil Modi was the CMO of a $1bn business services

organization.

www.ananto.com ananto_tweet
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ananto case synopsis_customer experience_agony threshhold

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