The problem
Faster reporting and AI-ready insights for retention-driven growth
What was slowing revenue, draining cost, or blocking the next stage of growth.
- Member demographics, enrollments, program participation, and transactions were siloed across systems
- Schemas contained duplicate identifiers and inconsistent standards
- Reporting depended on manual consolidation, increasing latency and error rates
- Analytics cycles stretched from hours to weeks
- AI initiatives were blocked because the data wasn’t trustworthy or unified
The results
Transformative Results
Numbers the business can take to finance, sales, and the board.
- $3.2M in annual savingsfrom faster reporting, less manual reconciliation, and retention-ready member data
- 50% faster reporting prepafter unifying member data
- from days to overnightfor analytics cycles
- The business can identify which member segments are most likely to engage, lapse, or renew
- Personalization becomes feasible at scale (recommendations, nudges, program matching)
- Predictive models can drive higher utilization and retention—directly impacting lifetime value
- Marketing and product teams can test targeting and engagement strategies with tighter feedback loops
- Move toward near-real-time insight and operational reporting
- Personalize member experiences at scale
- Deploy predictive models without constant data cleanup
- Accelerate experimentation across marketing, operations, and engagement programs
- Extend capabilities without re-architecting the foundation
