Launch In App Experiments

Command: launch-in-app-experiments

Inputs

• surface – product area (dashboard, onboarding, billing, collaboration, mobile).
• goal – activation | engagement | monetization | retention.
• variants – number of experiment arms (including control).
• guardrails – comma-separated guardrail metrics to monitor.
• audience – persona/segment targeting (role, plan, region, cohort).
• notes – optional context or risk flags.

Workflow

1. Hypothesis Intake – capture hypotheses, prior learnings, and success metrics.
2. Design Package – define variant specs, targeting, triggers, and messaging.
3. Instrumentation & Guardrails – ensure events, tracking, and guardrails are wired.
4. Launch & Monitoring – deploy experiment, monitor metrics, trigger alerts.
5. Readout Prep – summarize results, decisions, and follow-up actions.

Outputs

• Experiment brief with hypotheses, variants, and instrumentation checklist.
• Guardrail + monitoring dashboard snapshot.
• Readout template with decision + rollout recommendation.

Agent/Skill Invocations

• usage-growth-scientist – leads experiment design + analysis.
• product-adoption-strategist – ensures journey alignment + messaging.
• in-app-messaging-kit skill – generates variant messaging + prompts.
• usage-health-scorecard skill – monitors guardrails + success metrics.