product-behavior-signals

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

1. Latest analytics dashboards or raw event exports.
2. Recent interview/UGC transcripts, community threads, customer support logs.
3. Current instrumentation coverage map (events, properties, cohorts).

Workflow

1. Instrument gap check
   • Audit current telemetry vs. critical behaviors; file gaps immediately.
2. Pattern mining
   • Cluster behaviors by intent (explorers, creators, whales, lurkers, churned) using both quant cuts and qual quotes.
   • Map anxieties vs. triggers vs. rewards.
3. Insight synthesis
   • For each cluster, craft a “belief statement” (user tension + evidence + implication).
   • Link to supporting artifacts (charts, clips, tickets).
4. 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.