One wrong analytics conclusion can easily cost a company thousands of dollars.
And the most expensive part is often not the money.
It’s the lost time.
Imagine this situation:
– PM prepares a solution
– Designer redesigns the flow
– 2-3 developers implement changes
– QA tests everything
– Product discussions continue for weeks
A small team can easily spend 2 weeks on this. That’s already thousands of dollars burned.
But the real problem starts later.
Because if the original analytics was wrong, the company now needs:
– time to discover the issue
– time to fix tracking
– time to collect clean data again
– time to re-evaluate hypotheses
– time to rebuild trust in the metrics
And suddenly one tracking mistake delays product decisions by another few weeks or even months.
I recently saw a case where teams believed there was around 70% drop on one registration step.
Solutions were discussed. UX changes were considered. Work was already moving forward.
But after reviewing raw events and platform consistency, the real drop was much closer to ~10%.
The product problem barely existed. The data problem did.
That’s why analytics reliability is much more important than many teams think.
Broken tracking doesn’t just affect dashboards. It changes roadmap priorities, product strategy, and company focus.
And unlike broken features, analytics problems often look completely believable.
#productmanagement #analytics #growth #productanalytics #mobiledevelopment #firebase #mixpanel #abtesting #softwareengineering #startup
Originally published on LinkedIn by X91 Tech.
