Case Study: Valpak reduces customer churn with AgileThought's predictive analytics discovery

Reducing Customer Churn with Predictive Analytics Discovery

Valpak, one of North America’s leading direct marketing companies, wanted to reduce customer churn but was unsure whether its historical data could predict which customers might leave or why. AgileThought used its Predictive Analytics Discovery service to assess the data, define the churn problem as a data science objective, and determine whether a machine learning approach was feasible.

AgileThought built and tested a proof of concept using logistic regression and gradient boosted trees, then delivered the codebase, a final report, and guidance so Valpak could run and retrain the models independently. The engagement helped Valpak identify churn drivers such as infrequent customer contact, evaluate the value of each customer, and broaden its internal data science capabilities with a low-risk path to scaling predictive analytics.

Valpak

Chris Cate

Chief Operating Officer and CIO