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Home > Nia > Case Studies > Customer Churn in Retail

Motivation

An online retailer with over $100M in revenue and 19 million opt-in registrants had lots of customers disengaging after the initial sign-up. They could not identify a clear reason for this passive customer churn via the lack of engagement. Their in-house system used analytics and off-the-shelf statistics but no machine learning.

Solution

We developed an advanced analytics solution that not only provided churn prediction, but also identified the variables that most reliably contribute to an accurate prediction. This gave the customer insight into why their customers were disengaging, which in turn allowed them to take action to improve retention. The result was a large reduction in churn combined with a large predicted revenue increase.

Benefits

  • Churn reduced by 55% – 68%

  • Predicted revenue increase of 200 – 400%

  • Insight into reasons for churn enables corrective action

  • Identify which members are likely to churn

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