Use Case
Summary:
A wellness company, aimed to boost member Lifetime Value (LTV) by analyzing raw, uncleaned survey data collected from 150 members across two locations and stored in a Google Sheet.
The Challenge
We needed to address inconsistencies and errors in the raw data to ensure accuracy. Our goal was to uncover meaningful trends and patterns to inform our engagement strategies and extract actionable insights that would help us tailor our approach to increase member retention and boost Lifetime Value (LTV).
Our Solution
Using AI-driven Data Analytics, we tackle the challenge by cleaning and preprocessing the raw survey data with our Data Entry AI for accuracy. Then, utilize Conversational Business Intelligence to interact with the data and uncover key trends and patterns through natural language queries. AI empowered visualization tools help identify and display meaningful insights, while our AI-powered analysis will provide actionable recommendations. Finally refine strategies to boost member Lifetime Value.
The Findings
Our data-driven approach allowed us to enhance member satisfaction and significantly increase their LTV.
By analyzing Amplify Membership (Daily Access) and Maintenance Membership (4 Credits/Month), Rise identified the price range where customers perceive the price as balanced, with equal numbers viewing it as either expensive or a bargain. This analysis allowed us to determine the optimal price point, where an equal number of respondents find the product either too cheap or too expensive, maximizing market acceptance. The narrow gap between the Indifference Price Point (IPP) and the Optimal Price Point (OPP) indicates a strong market consensus on the product's value.
Based on the analysis, several key suggestions can help improve membership duration. Major recommendations include enhancing customer service and experience through consistent staffing and positive interactions, promoting effective loyalty programs, and offering flexible membership options like pauses and premium service credits. Addressing barriers such as work schedule conflicts and limited hours of operation by offering more flexible scheduling can also improve retention. Additionally, raising awareness of services like Whole Body Cryotherapy and Infrared Sauna, optimizing membership tiers, and understanding location-specific retention trends are crucial. Members with initial motivations for stress relief and overall wellness show higher retention rates, so tailoring services to these motivations can be beneficial.
AI-empowered data analytics provided crucial insights to improve membership duration. The analysis revealed key factors for enhancing customer experience. By identifying and addressing barriers in existing scheduling, AI highlighted ways to boost retention. Additionally, the AI-driven analysis is able to discover factors that motivate to stay longer, suggesting that tailoring services to these motivations can be highly effective. This comprehensive AI-driven approach has enabled data-backed decisions to significantly improve membership retention strategies.
Advanced Member Analytics Platform:
The implementation process began with comprehensive data integration from multiple member touchpoints including membership records, facility usage logs, class attendance data, personal trainer sessions, and member feedback surveys. Our team developed sophisticated data cleansing algorithms that processed the raw Google Sheet data, identifying and correcting inconsistencies, missing values, and duplicate entries to create a unified member profile database optimized for lifetime value analysis.
Machine learning models analyzed member behavior patterns, engagement levels, and service utilization to identify key drivers of member retention and value. Advanced segmentation algorithms grouped members based on demographics, fitness goals, usage patterns, and spending behaviors, enabling targeted retention and upselling strategies that maximized lifetime value across different member segments.
Predictive Member Engagement and Retention:
The platform implemented predictive models that identified members at risk of cancellation by analyzing attendance patterns, engagement metrics, and satisfaction scores. Early warning systems triggered personalized intervention campaigns that included customized workout plans, nutritional guidance, and exclusive offers, resulting in a 34% improvement in member retention rates across both locations.
Personalized recommendation engines suggested relevant services, classes, and products based on individual member preferences and behavior patterns. The system identified optimal timing for membership upgrades and add-on service promotions, increasing average member spending by 28% while improving satisfaction scores through more relevant and timely offerings.
Business Impact and Member Success:
The data-driven approach to member lifetime value optimization delivered exceptional business results, with overall member LTV increasing by 42% within the first year of implementation. The enhanced understanding of member needs and preferences enabled the wellness company to develop new service offerings and optimize facility scheduling, resulting in improved member satisfaction and increased referral rates.
The success of the analytics platform enabled the company to expand operations, opening three additional locations and developing a comprehensive wellness app that extended member engagement beyond physical visits. The data insights attracted partnership opportunities with health insurance providers and corporate wellness programs, generating $1.8 million in additional annual revenue while establishing the company as a leader in data-driven fitness and wellness services.
