Proprietary Machine Learning model identifies fitness club members most likely to purchase Personal Training.
Rocky Hill, CT: Easalytics today announced the launch of its Personal Training Purchase Probability model, a subscription-based Machine Learning predictive model built specifically for small to mid-size fitness organizations. The predictive model rates the likelihood of each member to purchase Personal Training services within the next 3 months using a variety of member demographic and behavior variables unique to a club’s members.
“Before this, the power of Data Science was the expensive domain of only the largest brands. We’re excited to put it within reach of fitness businesses of all sizes,” says Doug Young, Chief Operating Officer at Easalytics. “Our member analytics and predictive model outputs like PT Purchase Probability and Attrition Risk Probability are especially powerful when integrated with a CRM for efficient and scalable data-driven action.”
Benefits of the Personal Training Purchase Probability predictive model include:
- Present the best Personal Training marketing messaging and offers at the optimum time a member may be ready to purchase
- Identify member segments underperforming their purchase potential and/or underserved by the product offering or messaging
- Realistically predict size of addressable Personal Training market with a given club location
The Easalytics Personal Training Purchase Probability model is available with no setup fee and a tiered monthly subscription based upon the number and size of locations.
