By name: product-behavior-signals description: Convert mixed-method research and live telemetry into actionable user insight loops that guide product bets.
Behavior Signal Intelligence
Intent
- Triangulate qualitative stories with quantitative funnels to uncover true motivation, anxiety, and habit loops.
- Maintain a living evidence stack that de-risks product, game, or web3 bets.
Required Inputs
- Latest analytics dashboards or raw event exports.
- Recent interview/UGC transcripts, community threads, customer support logs.
- Current instrumentation coverage map (events, properties, cohorts).
Workflow
- Instrument gap check
- Audit current telemetry vs. critical behaviors; file gaps immediately.
- Pattern mining
- Cluster behaviors by intent (explorers, creators, whales, lurkers, churned) using both quant cuts and qual quotes.
- Map anxieties vs. triggers vs. rewards.
- Insight synthesis
- For each cluster, craft a “belief statement” (user tension + evidence + implication).
- Link to supporting artifacts (charts, clips, tickets).
- Action routing
- Translate belief statements into testable hypotheses or backlog items with owners.
- Set review cadence (weekly insight review, monthly deep dive).
Verification
- Every belief statement references at least one quantitative and one qualitative source.
- Instrumentation gaps tracked with owners/dates.
- Insight backlog reviewed with product/game leads and updated within the last sprint.