Before scaling a growth strategy, I want to see a stable event taxonomy, a known activation moment, and evidence that at least one onboarding or pricing change improved retention rather than only sign-up conversion. Otherwise the team may just be moving churn forward in time.
Three evaluation axes to compare:
- speed to user value
- durability of the retention effect
- clarity of experiment attribution
Review materials:
- Intercom on user onboarding: intercom.com/blog/user-onboarding/
Helpful for teams redesigning the first-run experience around actual user value.
- PostHog docs: posthog.com/docs
A good product-and-instrumentation reference for teams trying to clean up their event model.
- PostHog source: github.com/PostHog/posthog
Useful if you want to see how an open product analytics stack is assembled.
Save the strongest examples, scorecards, and decision memos in this folio so future teammates can see what good evaluation looked like at the time.
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