nanthan987/customer-churn-prediction

RNN based prediction of customer churn at a supermarket

RNN based prediction of customer attrition

This is the submission by my team, "KOALACODERS", for the final round of the data analytics competition "Data Storm 1.0" by OCTAVE.

Teammates: G. Ganeshaaraj (ganeshaaraj97), R. Thushany

Problem

Use Case definition

Identify customers who will completely stop shopping at the supermarket (i.e. basket value drops to 0) in the next 2 consecutive months. For example - the customer who have shopped in January 2019 but not in February 2019 and March 2019 is identified as a churn case.

Business Problem

The sales and marketing team needs to identify high risk customers before they churn, to make targeted proactive interventions to ensure continued business. Current efforts to reduce customer churn are reactive (i.e. offers are targeted towards churned customers who have not returned to the business for a few months) . These efforts have not been regular in response to specific situations (eg- store re-fitting)

Key question to answer

Which regular customers (clue – define regularity by looking at average monthly transaction frequency and tenure of the customer) are most likely to stop shopping at the supermarket?