Guide to Customer Retention Analytics- Part 1

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This week we have a special guest post by Sandhya Kuruganti and Hindol Basu, authors of a book on Business Analytics titled Business Analytics: Applications to Consumer Marketing”. Thanks Sandhya and Hindol for taking the time  to so lucidly explain to us retention and attrition in the context of Customer Retention Analytics.  

This post will be a two part series. The first part focuses on understanding retention, attrition and the various retention strategies used by marketers. Part two will explain retention analytics, along with a Telecom Case Study that showcases the Proactive Approach to Retention Management using Churn Model.

 

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Many of you may be in your second or third job. Do you recall when you last put in your papers? Your employer may have been very upset to hear this announcement from you. Perhaps persuaded you to stay on with multiple incentives of a better role, a promotion around the corner, a salary hike, or a sweet HR talk on how valuable and indispensable you are to the organization. Imagine management apprehension around the negative buzz in the office once your resignation news hits the grape vine!  Most of you must have felt good when your boss left no stone unturned to retain you (even though it was a bit too late?)… Similarly, customer retention is not too different and is as important as employee retention for an organization that values its customers and of course its employees!

Definition of Retention

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Customer retention is an activity and process that a product/service provider undertakes in order to reduce customer defections or attrition. Successful customer retention starts with the first contact a product/service provider has with a customer and continues throughout the entire lifetime of a relationship. It is an important CRM (customer relationship management) strategy for improving customer lifetime value. Customer life time value simply put is the profit stream measured over the lifetime of the customer.

Customer retention is traditionally defined by the customer retention rate.  The customer retention rate is a metric that indicates the proportion of customers that have stayed with the product/service provider for a specified period of time.  The retention rate can be calculated annually, monthly or weekly. The retention rate is also an indicator of the performance of the company in terms of keeping its customers satisfied and loyal. 

Various Definition of Attrition

Attrition is multifarious and has several facets as highlighted in the figure below.

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Definition of Attrition by Industry

The following table shows a few examples of terminology and definition by industry.

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Benefits of Retention

The impact of an effective retention strategy can be significant. For example, it has been observed that a 5 percentage point improvement in customer retention can result in a 75% and upwards increase in customer lifetime value (CLV) across a range of industries (Source: Frederick Reichheld “The Loyalty Effect”). In fact, studies by Bain & Company, along with Earl Sasser of the Harvard Business School, have shown that even a 5 percent increase in customer retention can lead to an increase in profits of between 25%-95%. The following chart graphically highlights the workings behind these findings.

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Reasons for Attrition

Major factors underlying attrition behaviour for a credit card are illustrated in the following figure.

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Retention Strategy

Retention strategies can be classified into proactive, reactive and win-back.

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Click here for Part 2  of the post which explains retention analytics, along with a Telecom Case Study that showcases the Proactive Approach to Retention Management using Churn Model. 

Sandhya Kuruganti and Hindol Basu are authors of the book “Business Analytics: Applications to Consumer Marketing”, recently published by McGraw Hill and available on Flipkart and Amazon India/UK/Canada.  Jigsaw students can avail of a discount of 20% with a coupon code at McGraw Hill website (valid until Nov 30, 2015).  . The authors are seasoned analytics professionals with a collective industry experience of more than 30 years.

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