The challenge
Innovate’s leadership team was making decisions about retention and revenue using data scattered across spreadsheets and disconnected tools. Bringing those figures together required manual work, and the team lacked confidence in the numbers they were using.
Cohort retention analysis that should have taken an hour was taking days. Leaders needed a consistent view of customer behaviour without waiting for someone to assemble another spreadsheet or pull a separate report.
What we built
We built a data warehouse pipeline that moved information from Innovate’s production PostgreSQL database into Amazon Redshift. The warehouse was designed around the analytical queries the team needed to answer, giving retention and revenue reporting a shared data foundation.
On top of that, we built a React dashboard with real-time cohort retention and churn views. Leadership could explore customer patterns directly, rather than relying on an analyst to prepare each report.
Bringing the data together also made previously hidden patterns easier to identify. The dashboard surfaced a churn pattern within a specific customer segment that the spreadsheet-based process had missed.
Key features
- Centralised data warehouse: A PostgreSQL-to-Redshift pipeline brings production data into a shared environment for analytical reporting.
- Cohort retention views: Interactive dashboards help the team understand how different customer groups retain over time.
- Churn visibility: Segment-level analysis makes it easier to identify patterns that can be difficult to spot in disconnected spreadsheets.
- Self-service reporting: A React interface gives leadership direct access to key insights without requesting a new report each time.
- A shared reporting foundation: One source of truth helps the team work from consistent retention and revenue information.
The outcome
Innovate’s team gained a single place to explore retention and churn, reducing its reliance on manual spreadsheet analysis. Leadership could investigate customer behaviour with a clearer view of the underlying data.
The analysis identified a previously hidden churn pattern in a specific customer segment, pointing to a $2M revenue opportunity. This gave the team a concrete area to investigate and prioritise in its retention efforts.
What they said
“Their AI integration expertise saved us months of R&D. They didn't just build, they advised. Invaluable.”
Lisa Rodriguez
Head of Product, Innovate
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