Accenture · Avanade · Case study
Microsoft Data IntegratorReversing adoption decline on an established platform
Took a product with falling usage, found the trust gap through research, and drove a ~90% increase in adoption.
Data PlatformsAdoptionCustomer ResearchUX
~90%
Adoption increase
↓
Support ticket volume
↑
Time-to-first-value
The problem
A mature data integration product was losing usage quarter over quarter. The internal narrative was 'we're missing connectors'. Renewal conversations were getting harder and the roadmap was a list of competitor parity items.
Discovery
Funnel analytics told a different story: users who completed a first successful sync retained well. Most never got there. Drop-off concentrated in setup, credentials and error recovery.
Customer research
- 20+ interviews with admins, data engineers and partner consultants
- Usability sessions on first-run configuration — repeated failure at the same three steps
- Support ticket clustering: 'what does this error mean' dominated volume
- Insight: the product was capable but illegible
Product strategy
One theme for two quarters: time-to-first-successful-sync. Stop shipping parity features; make the product explain itself. Convert every error into a next action.
Prioritisation & tradeoffs
- Killed or deferred 60% of the existing backlog against the single north star
- Weighted fixes by drop-off volume at each funnel step
- Held the line with stakeholders using a shared adoption dashboard
Solution
- Guided setup with validation at each step instead of on submit
- Human-readable errors with remediation links and diagnostics
- Run observability: what ran, what moved, what failed and why
- Templates for the most common integration patterns
Architecture
- Instrumented funnel events across setup, first run and recovery
- Error taxonomy mapped to remediation content
- Progressive disclosure of advanced configuration
Execution
- Weekly research readouts to keep stakeholders anchored to evidence
- Partnered with support to close the loop on ticket themes
- Phased release with cohort-based adoption tracking
Lessons learned
- The loudest internal theory is usually a proxy for 'we haven't talked to users recently'.
- A single north star metric is a political tool as much as an analytical one.
- I'd bring support data into the roadmap ritual permanently, not just during the turnaround.