9-Agent Product
9-Agent CRO Workflow
A structured multi-agent system for conversion optimization — breaking a business problem into nine specialist lenses, each contributing a distinct layer of product judgment.
The nine lenses
How the workflow thinks
Each agent represents a distinct layer of product judgment. The goal is not output volume — it is structured decision quality.
Data Agent
Establishes the baseline — what is actually happening in the funnel before any opinion enters the room.
UX Agent
Translates numbers into interface problems — where the experience breaks down and why users leave.
Research Agent
Grounds the diagnosis in market reality — are these problems unique to us or industry-wide patterns?
Customer Voice Agent
Brings the human layer — what buyers actually say, fear, and need before they convert.
Tech Agent
Stress-tests every idea against the stack — filters out what cannot be shipped before prioritization.
Experimentation Agent
Turns validated problems into testable bets — structured hypotheses with measurable success criteria.
Prioritization Agent
Forces a decision — which bets get resources first, ranked by impact, effort, and confidence.
Risk Agent
The final filter — what could go wrong, what are we assuming, and what needs a contingency.
Documentation Agent
Closes the loop — converts decisions into a format engineering can act on without a follow-up meeting.
Workflow
How it runs — step by step
Each agent hands off to the next, building a complete picture from raw data to a dev-ready execution plan.
Your business data
GA4 · Google Ads · Sheets dashboard
Finds funnel leaks, drop-offs, and device splits using GA4, Google Ads, and dashboard data.
Identifies page friction, confusing flows, and interaction barriers using data insights.
Validates UX findings against market benchmarks and competitor behaviour.
Maps findings to buyer psychology, trust gaps, and real customer language.
Validates technical feasibility on your stack and flags implementation constraints.
Designs A/B tests with hypothesis statements, variants, and lift targets.
Ranks every action by RICE and ICE score against effort and business impact.
Flags implementation risks, conversion risks, and edge cases before execution.
Produces a dev-ready action plan, decision memo, and 30-day execution summary.
Final output
Top 3 actions · Revenue impact · 30-day plan
Color key
Three phases
Observe
Data Agent reads funnel signals, drop-offs, and device splits to frame the problem.
Diagnose
UX, Research, Customer Voice, and Tech agents each contribute a specialist lens on the problem.
Decide
Experimentation, Prioritization, Risk, and Documentation agents produce a ranked, dev-ready action plan.