For large fitness franchises, high early churn rates threaten revenue and growth, making it critical to identify interventions that keep new members engaged.
Problem
Which targeted interventions most effectively reduce early membership churn in a large fitness franchise?
Process
AI-driven big data analytics:
• We analyzed membership data and identify the 10% of at-risk members most likely to stay with targeted interventions. This predictive analysis helped pinpoint key intervention points and risk scores.
Ethnography:
• Next, we conducted ethnographic research to gain deep insights into the behaviors and motivations of these members. This qualitative research informed the development of 2-3 highly impactful retention strategies tailored to the specific needs of the identified members.
Results
By focusing on the 10% of members most likely to be retained, the company implemented 2-3 targeted intervention strategies that sustainably reduced churn by 2-5%. This approach led to a significant improvement in EBITDA, adding millions to the company’s bottom line. The targeted strategy not only addressed immediate churn issues but also ensured long-term member loyalty and financial stability.
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