Maximize Customer Lifetime Value at at each stage of the Customer Journey
Customer Journey for Fitness Industry
Case Study for Fitness Franchise Industry
The Fitness Network
A leading national fitness and membership-based wellness network, operating thousands of locations across North America, manages a broad customer base with a lean, centralized marketing team. Despite strong brand awareness and consistent new-member acquisition, the organization faced mounting pressure from high churn levels, which were limiting long-term revenue growth and reducing profitability.
Although the company had CRM systems and retention processes in place, these tools were largely reactive—surfacing issues only after members showed signs of disengagement. The team needed a more predictive and prescriptive way to understand member behavior, identify early indicators of churn, and determine where revenue was most at risk across its customer base.
The Challenge
The core challenge was to move beyond traditional reporting and manual segmentation toward a system capable of anticipating churn before it happened. The organization aimed to improve Customer Lifetime Value by identifying risk earlier, prioritizing high-value members, and enabling timely, targeted engagement at scale.
​
Case Study for Sports Training Industry
Sports Training Network
The organization is a rapidly expanding network of technology-enabled training centers operating across North America. Its mission is to help individuals improve their performance through precision training, structured development programs, and data-driven insights. With thousands of active participants and memberships across multiple tiers, the organization generates a significant volume of behavioral and engagement data. This rich dataset represents a major opportunity to better understand player performance patterns, loyalty drivers, and spending behaviors.
The Challenge
The organization had extensive player and membership data but lacked the ability to turn it into timely, revenue-driving actions. They needed clearer insight into which players were likely to upgrade, increase spend, or disengage—and which segments offered the highest growth potential.
​
The goal was to use data more intelligently to identify the right players at the right moment and engage them with targeted retention and upgrade campaigns, ultimately improving loyalty and accelerating revenue performance.
