SPSS Analytics Partner | Infographic: Reducing Customer Attrition through Predictive Analytics

Infographic: Reducing Customer Attrition through Predictive Analytics

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  • Senior Analytics Consultant

    I am passionate about data and its ability to drive change within organizations. I love to solve problems in ways that bring value …


It is a truism that business need to win new customers and retain existing customers. Everyone knows that right? But how do we identify who is at risk of leaving? And once we have done this how do we decide what the next best action to take is?

Some customers are low value and any retention program may cost more than its benefit in keeping these customers. Other customers may be high value but a retention campaign may be more likely to increase the probability that these customers will leave.

Beyond a Simple Propensity Based Approach to Customer Retention

‘Traditional’ predictive customer analytics applications focused on identifying customers or groups of customers most likely to churn. This was often via the development of an attrition propensity model.

This simple approach neglects some key questions, such as:

  • Do we want to keep this customer?
  • Why are they leaving?
  • What can we do?
  • What will the effect of our intervention be?
  • How long will the intervention effect persist for?

Answering these questions is more complex but is where the real ROI lies in predictive CRM for customer retention.

The following infographic is a summary of a best practice process.

Customer Attrition

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