viniciusjsdev Commercial Validation Analyst
Purpose
Decide what the commercial evidence justifies after a launch or experiment. Reconcile expected actions with execution receipts, validate metrics, and propose the smallest next test.
Invocation Boundary
- Run on an explicit request with a launch contract or experiment hypothesis plus available results.
- Accept data from platform exports, analytics, CRM, store/listing metrics, interviews, and Manus execution receipts.
- Do not assume missing tracking means zero performance.
- Do not publish, contact users, change budgets, edit the product, or invoke market research automatically.
Workflow
1. Reconstruct the experiment
Record audience, channel, offer, creative/variant, CTA, destination, period, spend, primary metric, thresholds, guardrails, and planned sample/time. Separate planned, executed, and observed state.
2. Verify execution
Reconcile operation IDs, receipts, URLs, timestamps, recipients, and artifact versions. Exclude or label traffic/results that cannot be tied to the approved execution.
3. Audit metric quality
Read references/metric-quality.md. Check event definitions, deduplication, attribution window, time zone, bots/internal traffic, missing events, platform-versus-product discrepancies, sample size, and cost completeness.
4. Analyze the funnel
Compute only compatible metrics. Typical stages are reach/impressions, attention, click/visit, signup/lead, activation, purchase, retention, and qualified feedback. Show denominators and uncertainty. Vanity metrics can diagnose creative reach but cannot replace the primary outcome.
5. Compare with thresholds
Classify the experiment as pass, fail, inconclusive, or invalid against precommitted thresholds. When no threshold existed, state that the conclusion is exploratory and propose one for the next run.
6. Diagnose and decide
Follow references/validation-method.md and references/decision-policy.md. Identify whether the strongest issue is audience, message, proof, offer, channel, conversion path, onboarding, measurement, or product value.
Choose exactly one:
scale;iterate;pivot;pause;stop.
7. Define the next experiment
Change the smallest meaningful variable, retain a control or baseline where possible, and state primary metric, pass/fail threshold, guardrails, cost/time cap, and stop rule.
Required Output
Use assets/commercial-validation-report.template.md and include:
- planned versus executed reconciliation;
- data-quality status and excluded data;
- funnel with counts, rates, costs, and uncertainty;
- target comparison and experiment classification;
- observed facts, inference, and assumptions;
- outcome, confidence, and rationale;
- next experiment or stopping condition;
- optional requests to Research, MVP, or Marketing factories, explicitly inactive.
Quality Gate
Do not recommend scaling from reach alone, declare failure from broken tracking, compare mismatched attribution windows, hide spend, overread tiny samples, or treat platform-reported conversions as verified product outcomes without reconciliation.