Subscription churn modeling | Marley Spoon case study

Putting data science to work for smarter churn prevention strategies

Marley Spoon operates on a subscription model, making retention a focal point of their growth strategy. Here’s how Faraday helped them detect churn better with data science.

Here’s the gist:

Customer background

Higher churn rates make it more difficult to cover acquisition costs and scale revenue. Marley Spoon wanted a better approach to churn prediction than traditional rules-based segmentation.

Churn modeling

Faraday built and validated a predictive churn model from a combination of Marley Spoon’s customer data and Faraday’s third-party consumer data.

Analysis and results

A comparison of Marley Spoon’s traditional approach and the Faraday churn model revealed a 5X improvement in churn prediction when using the predictive model.