Analytics in product development — decision-grade, not dashboard-deep.

Usage analytics converts opinions into prioritization when events are trustworthy and tied to outcomes leadership recognizes.

Products improve faster when teams share a factual picture of activation, retention drivers, and funnel leakage. Analytics fails when events are inconsistent or vanity metrics crowd out substance.

Foundations

Define schemas collaboratively with engineering — naming, sampling bias, identity stitching — before trusting downstream dashboards.

From charts to decisions

We tie analytics initiatives to named decisions each sprint will make — pricing tests, onboarding experiments, segment comparisons — so instrumentation earns its maintenance cost.