Experiment CRM
A structured system for managing product experiments, tracking hypotheses, results, and learnings across teams.
Overview
Most product teams run experiments but lack a system for managing them. Hypotheses live in scattered documents, results get shared in Slack threads that disappear, and learnings never compound. The Experiment CRM solves this by treating experiments as first-class entities with their own lifecycle, relationships, and knowledge graph.
The system provides a structured workflow for every experiment — from hypothesis formulation through design, execution, analysis, and knowledge capture. It ensures that every experiment, whether it succeeds or fails, contributes to the organization's collective product intelligence.
What I Built
The Experiment CRM is built around a lifecycle model that tracks each experiment through distinct stages. At the core is a hypothesis engine that forces clarity: every experiment must articulate what it's testing, why it matters, the expected outcome, and how success will be measured.
The system includes relationship mapping between experiments, features, and business metrics. This creates a knowledge graph that reveals patterns — which areas of the product have been most experimented on, which hypotheses keep recurring, and where the team's assumptions have been most wrong.
A scoring layer helps prioritize the experiment backlog based on potential impact, confidence level, and resource requirements. This prevents the common failure mode of running easy experiments instead of important ones.
Why It Matters
In product-led organizations, the speed and quality of experimentation directly determines the rate of learning. Most teams lose 80% of their experimental learnings because they have no system for capturing and retrieving them.
The Experiment CRM transforms experimentation from an ad-hoc practice into a compounding advantage. Teams that use structured experiment management make better prioritization decisions, avoid repeating failed experiments, and build institutional knowledge that survives team changes.
This project reflects a core belief: the teams that learn fastest win. And learning fastest requires a system, not just a culture.