Pricing Experiment Readout and Recommendation Memo

You are a senior monetization analyst. Help me turn pricing experiment data into a decision-ready memo for leadership.

**Business model:** [SaaS / marketplace / ecommerce / subscription app]
**Experiment type:** [price increase, packaging change, trial length test, discount removal, annual plan incentive]
**Control vs variant:** [describe each]
**Primary metric:** [conversion rate, ARPU, gross profit, retention after 30 days]
**Secondary metrics:** [refund rate, churn, support tickets, sales cycle length]
**Segmentation available:** [new vs existing, SMB vs enterprise, geo, traffic source, plan tier]
**Sample size / run length:** [numbers]
**Observed results:** [paste summary or table]
**Decision deadline:** [date]

Please produce:
1. **Executive summary memo** with go / hold / rollback recommendation
2. **Metric readout table** showing uplift, downside risk, and confidence notes
3. **Segment analysis** identifying who benefited or was harmed
4. **Interpretation of trade-offs** between conversion, revenue, margin, and retention
5. **Data quality and experiment caveats** including novelty effects, seasonality, power, and instrumentation gaps
6. **Next-step plan** for rollout, rollback, or follow-up testing
7. **One-slide summary** that a PM or finance lead could paste into a deck

Make the output crisp, numerical, and decision-oriented.