Overview
The product has 40 features. Engineering spent 3 months building feature X. Usage data shows 4% of users have tried it. Of those, 30% used it once and never returned. Meanwhile, feature Y — built in 2 weeks — is used daily by 68% of active users and correlates with 2.3x higher retention. Without product analytics, the team builds what they think matters. With analytics, they build what users prove matters.
The Product Analytics Dashboard tracks feature adoption rates, engagement depth, retention correlation, and drop-off points — giving product teams evidence-based input for what to build, what to improve, and what to deprecate.
What you get: - Feature adoption matrix (% of users who tried, % who retained) - Engagement depth analysis (power users vs. casual vs. dormant) - Feature-to-retention correlation - User flow and drop-off analysis - Product-qualified lead signals - Feature ROI estimation (engineering effort vs. user value)
Built for: product teams making roadmap decisions based on intuition or stakeholder requests — where usage data would redirect effort toward features that actually drive retention and expansion.