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experiment-design-kit

@gtmagents/gtm-agents
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Toolkit for structuring hypotheses, variants, guardrails, and measurement

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SKILL.md

name experiment-design-kit
description Toolkit for structuring hypotheses, variants, guardrails, and measurement plans.

Experiment Design Kit Skill

When to Use

  • Translating raw ideas into testable hypotheses with clear success metrics.
  • Ensuring experiment briefs include guardrails, instrumentation, and rollout details.
  • Coaching pods on best practices for multi-variant or multi-surface tests.

Framework

  1. Problem Framing – define user problem, business impact, and north-star metric.
  2. Hypothesis Structure – "If we do X for Y persona, we expect Z change" with assumptions.
  3. Measurement Plan – primary metric, guardrails, min detectable effect, power calc.
  4. Variant Strategy – control definition, variant catalog, targeting, and exclusion rules.
  5. Operational Plan – owners, timeline, dependencies, QA/rollback steps.

Templates

  • Experiment brief (context, hypothesis, design, metrics, launch checklist).
  • Guardrail register with thresholds + alerting rules.
  • Variant matrix for surfaces, messaging, and states.
  • GTM Agents Growth Backlog Board – capture idea → sizing → prioritization scoring (ICE/RICE) @puerto/README.md#183-212.
  • Weekly Experiment Packet – includes KPI guardrails, qualitative notes, and next bets for Marketing Director + Sales Director.
  • Rollback Playbook – pre-built checklist tied to lifecycle-mapping rip-cord procedures.

Tips

  • Pressure-test hypotheses with counter-metrics to avoid local optima.
  • Document data constraints early to avoid rework during build.
  • Pair with guardrail-scorecard to ensure sign-off before launch.
  • Apply GTM Agents cadence: Monday backlog groom, Wednesday build review, Friday learnings sync.
  • Require KPI guardrails per stage (activation, engagement, monetization) before authorizing build.
  • If a test risks Sales velocity, include Sales Director in approval routing per GTM Agents governance.

GTM Agents Experiment Operating Model

  1. Backlog Intake – ideas flow from GTM pods; Growth Marketer tags theme, objective, expected impact.
  2. Prioritization – score with RICE + qualitative "strategic fit" modifier; surface top 3 bets weekly.
  3. Design & Instrumentation – reference Serena/Context7 to patch code + confirm documentation.
  4. Launch & Monitor – use guardrail-scorecard to watch leading indicators (churn, complaints, latency).
  5. Learning Loop – run Sequential Thinking retro; document hypothesis, result, decision, follow-up in backlog card.

KPI Guardrails (GTM Agents Reference)

  • Activation rate change must stay within ±3% of baseline for Tier-1 segments.
  • Revenue per visitor cannot drop more than 2% for more than 48h.
  • Support tickets tied to experiment variant must remain <5% of total volume.

Weekly Experiment Packet Outline

Week Ending: <Date>

1. Portfolio Snapshot – tests live, status, KPI trend (guardrail vs actual)
2. Key Wins – hypothesis, uplift, next action (ship, iterate, expand)
3. Guardrail Alerts – what tripped, mitigation taken (rollback? scope adjust?)
4. Pipeline Impact – SQLs, ARR influenced, notable customer anecdotes
5. Upcoming Launches – dependencies, owners, open questions

Share packet with Growth, Marketing Director, Sales Director, and RevOps to mirror GTM Agents's cross-functional communication rhythm.