analyzing-customer-patterns
CommunityTurn shipped outcomes into actionable lessons.
Product & Management#pattern detection#customer feedback#lesson generation#release pipeline#Linear issue tracking#outcome analytics#BVI metrics
AuthorCleanExpo
Version1.0.0
Installs0
System Documentation
What problem does it solve?
It closes the open loop between shipping features and understanding whether they actually delivered value (or caused regressions) by analyzing post-ship signals.
Core Features & Use Cases
- Outcome feedback analysis: Reads shipped feature records plus post-ship signals to detect patterns in what worked vs. what didn’t.
- Lesson writing to the build pipeline: Produces structured outcome lessons and appends them to
lessons.jsonlfor future briefs. - Stale feature detection with review triggers: Flags features with no signals for 30+ days and creates a Linear review issue.
- BVI contribution for performance reporting: Summarizes positive, negative, stale, and pending-signal counts to feed the BVI “features delivered” component.
Quick Start
Ask the AI to run the monthly outcome feedback loop and write the resulting patterns and lessons into lessons.jsonl based on shipped-features.jsonl and post-ship Linear signals.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: analyzing-customer-patterns Download link: https://github.com/CleanExpo/Pi-Dev-Ops/archive/main.zip#analyzing-customer-patterns Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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