02 — Capability · BC-1260
Product Analytics & Experimentation
Understand how customers actually use the product — which features, how often, where they give up — and test changes against real behavior before committing to them, so product decisions rest on evidence rather than the loudest opinion in the room.
- Product Analytics
- Growth Analytics
- A/B Testing
- Usage Intelligence
In scope
- Instrumenting the product and governing the events it emits
- Adoption, engagement, retention and funnel analysis
- Controlled experiments and their statistical interpretation
- Account health signals derived from usage, shared with success and sales
Out of scope
- Enterprise data platform, warehousing and company-wide analytics (see BC-750)
- Market research and customer surveys outside the product (see BC-410)
- Production health telemetry and alerting (see BC-1230)
Realized by · 0
- No product in the catalog yet.
Used in · 2
- Commit-to-Production · 04 Release Progressively via BC-1260.30
- Commit-to-Production · 06 Communicate & Learn via BC-1260.20
Build it · 1
- pattern Feature Flags via BC-1260.30.20
Decomposes into · 4
- BC-1260.10Instrumentation & Event GovernanceDecide what the product records about user behavior, name it consistently, and keep the event stream trustworthy as the product changes underneath it.
- BC-1260.20Usage & Behavioral AnalysisTurn the event stream into answers about adoption, engagement, retention and where users struggle, in a form product teams check as routinely as they check their builds.
- BC-1260.30ExperimentationRun controlled experiments on real users, read the results with honest statistics and act on them, so the product learns from what people do rather than what they say.
- BC-1260.40Customer Health SignalsDerive account-level signals from usage — expanding, stalling, at risk — and share them with the teams who own the relationship, so churn is predicted rather than reported.