Case Study: Transforming Customer Churn
Can You Proactively Identify Customer Churn Before it Becomes a Costly Problem?
INSIGHT analyzed patterns from a large regional fitness club to identify lagging churn indicators, then configured a machine learning model to predict churn and inform intervention strategies, resulting in a 2x increase in margin.
The Challenge
A large regional fitness club faced significant customer churn due to uncontrollable macroeconomic conditions as well as a lack of understanding of the root cause. This limited insight prevented them from distinguishing where churn was natural versus a risk to their business, leading to undesirable revenue, margin, and volume loss.
The Solution
INSIGHT began by retrospectively analyzing and identifying patterns, which revealed internal and external factors that were lagging indicators of churn. Collaborating with the business, we built a machine learning attrition algorithm to set parameters distinguishing normal variations from those requiring attention. This approach uncovered trends within specific customer groups, highlighting and predicting those at risk of churn in the future.
To ensure sustainability, INSIGHT’s implementation plan provided ongoing actionable guidance, empowering sales teams to target the right customers, discuss relevant topics/services, and effectively convey the value proposition to proactively manage ongoing churn
