Data team built a great funnel. Product came up with hypotheses. Design prepared solutions. The numbers looked convincing. Everyone felt confident before rollout.
Then someone noticed one tiny difference in the implementation.
Same feature. Same event. Same parameters. But:
- Android tracked the button tap before validation
- iOS tracked it after validation succeeded
One line of code difference.
Suddenly the funnels meant completely different things.
One platform measured:
"user intended to continue"
The other measured:
"user successfully passed validation"
The dashboard still looked correct. But the semantics behind the numbers were completely different.
This is one of the hardest parts of product analytics:
sometimes the biggest problems are not in the dashboards or SQL.
They're hidden inside implementation details nobody thinks about during feature development.
Originally published on LinkedIn by X91 Tech.
