customer churn

Brief

The decorative surface manufacturer waned to reduce customer churn and improve marketing effectiveness

Challenge

A well-known decorative surface manufacturer was keeping limited engagement directly with the end customer – as its products were sold through dealers. It was witnessing slow growth in revenue at dealer end despite being in the growing market. The client wanted to find out the factors –both controllable and uncontrollable factors – leading to customer churn at dealer end.

Our Action

• Customer profiling was done as per demographic data. Further segmentation was done based on product type and application areas
• Trade promotion at the dealer end were analysed to understand the behaviour of the customer  and ROI was measured on different campaigns
• TheMachine learning Model were developed for predictive analysis
• Analysis was carried to understand the attrition drivers at dealer end. Around 30 hypotheses were prepared and tested.

Results

• Identification of sales driver helped client in re-strategizing its product portfolio and reduced customer churn
• Thanks to the predictive analytics, additional revenue opportunity was created