CUSTOMER STORY | RETAIL
Delhaize predicts churn across 37 product categories with 1,013 variables
A large retailer was losing valuable business as customers gradually disengaged. TIMi’s predictive models detect churners on time, so that retention offers can be sent.
Product categories analyzed for churn risk
37
Predictive variables
1,013
OVERVIEW
The challenge.
Traditional retention methods were not effective.
Growing churn
Customers gradually disengaged and the retailer was losing valuable business.
Who and why
The retailer needed to predict which customers were at risk of leaving, and the underlying reasons.
SOLUTION
What was done.
Predictive models by category, linked to relevant offers.
37 categories
Churn risk is analyzed in 37 product categories.
1,013 variables
1,013 predictive variables are used to identify potential churners.
Coupon Factory
Relevant offers are sent as part of the churn prevention strategy.
RESULTS
What changed.
Churners detected on time, so that action is possible.
Timely detection
The methodology enables the detection of churners on time.
Timely intervention
Teams can act before customers leave.
Relevant offers
Retention offers are sent with the Coupon Factory.
SEE FOR YOURSELF
Test it on your own data.
Run TIMi on your own data with a free trial, or talk to us about your case.
