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How to Use Data Analytics to Fuel a Proactive Customer Retention Strategy

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08 June 2021
BLOG > DATA SCIENCE

How to Use Data Analytics to Fuel a Proactive Customer Retention Strategy

08 June 2021

Even a correct decision is wrong when it is taken too late.

A proactive customer retention strategy will help a brand to save unhappy customers before they take action to cancel. More commonly, brands wait until customers tell them they want to quit, then try to persuade them to stay. That’s a ‘reactive’ customer retention strategy.

Proactive retention strategies operate further upstream in the customer lifecycle and allow you to do something positive and proactive at the first indication customers might leave.  

And analytics will help you identify the customers at risk of cancelling.

It starts with analysing behavioural data for customers who have already cancelled to find the early warning indicators that customers might leave. By incorporating these early warning indicators within predictive models, you can then score existing customers for their likelihood to leave, creating lists of ‘at risk’ customers to target with relevant communications and offers.

Once operationalised, monitor how accurate the model is in predicting cancellations over time. And overlay a value calculation to make sure you’re focusing efforts on the customers you definitely want to retain. Testing different interventions for different cancellation reasons will also help you refine your model further.

And all in good time too.

200 words not enough? Learn more about data-driven customer retention strategies by reading the full article.
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