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AI Growth Experiment Portfolio Allocator

Turn experiment backlog sprawl into one ranked monetization portfolio with owner accountability, MRR-impact scoring, and sprint-capacity guardrails.

Allocate limited experiment capacity to the highest-return lanes across activation, pricing, expansion, and retention. Generate one ranked backlog with owner accountability and export-ready outputs.

Portfolio summary

Pressure score: 71.0 / 100 (High)

Estimated quarterly new MRR baseline: $189,000

Estimated monthly churn-risk MRR: $3,087

Recommended cadence: Run one weekly portfolio board with owner-level escalation for blocked lanes.

LaneOwnerExpected MRR impactPriority scoreSprintSupporting workflow
Pipeline leakage recoveryRevOps Director$17,2503277.5Sprint 1AI Pipeline Leakage Audit Generator
Experiment governanceGrowth Lead$10,5002730Sprint 3AI A/B Test Manager Generator
Activation friction reductionProduct Activation Lead$13,5001944Sprint 1AI Trial-to-Paid Conversion Rescue Generator
Expansion packagingRevOps Director$14,2501909.5Sprint 2AI Expansion Revenue Playbook Generator
Pricing and package experimentGrowth Lead$15,7501785Sprint 1-2AI Pricing and Packaging Experiment Planner
Churn and win-back defenseLifecycle Marketing Lead$16,5001760Sprint 2-3AI Win-Back Reactivation Playbook Generator
# AI Growth Experiment Portfolio - AI Growth Portfolio Team

## Baseline
- Quarter: 2026 Q2
- Monthly qualified trials: 2,400
- Trial-to-paid conversion: 12.5%
- Current ARPA: $210
- Gross margin: 74.0%
- Expansion rate: 8.2%
- Monthly logo churn: 4.9%
- Experiment capacity per sprint: 5
- Primary constraint: Low trial-to-paid conversion
- Monetization pressure score: 71.0 / 100 (High)
- Recommended cadence: Run one weekly portfolio board with owner-level escalation for blocked lanes.

## Revenue context
- Estimated new MRR per month: $63,000
- Estimated new MRR per quarter: $189,000
- Estimated monthly churn-risk MRR: $3,087

## Owner model
- Growth owner: Growth Lead
- Product owner: Product Activation Lead
- RevOps owner: RevOps Director
- Lifecycle owner: Lifecycle Marketing Lead

## Prioritized experiment portfolio (6 lanes)
| # | Lane | Owner | Expected MRR impact | Effort | Confidence | Priority score | Sprint | Supporting route |
|---|---|---|---|---|---|---|---|---|
| 1 | Pipeline leakage recovery | RevOps Director | $17,250 | 4 | 76% | 3277.5 | Sprint 1 | AI Pipeline Leakage Audit Generator (/ai-pipeline-leakage-audit-generator) |
| 2 | Experiment governance | Growth Lead | $10,500 | 3 | 78% | 2730 | Sprint 3 | AI A/B Test Manager Generator (/ai-ab-test-manager-generator) |
| 3 | Activation friction reduction | Product Activation Lead | $13,500 | 5 | 72% | 1944 | Sprint 1 | AI Trial-to-Paid Conversion Rescue Generator (/ai-trial-to-paid-conversion-rescue-generator) |
| 4 | Expansion packaging | RevOps Director | $14,250 | 5 | 67% | 1909.5 | Sprint 2 | AI Expansion Revenue Playbook Generator (/ai-expansion-revenue-playbook-generator) |
| 5 | Pricing and package experiment | Growth Lead | $15,750 | 6 | 68% | 1785 | Sprint 1-2 | AI Pricing and Packaging Experiment Planner (/ai-pricing-packaging-experiment-planner) |
| 6 | Churn and win-back defense | Lifecycle Marketing Lead | $16,500 | 6 | 64% | 1760 | Sprint 2-3 | AI Win-Back Reactivation Playbook Generator (/ai-winback-reactivation-playbook-generator) |

## Next sprint capacity cut (5 lanes)
1. Pipeline leakage recovery - Owner: RevOps Director; Impact: $17,250; Priority: 3277.5
2. Experiment governance - Owner: Growth Lead; Impact: $10,500; Priority: 2730
3. Activation friction reduction - Owner: Product Activation Lead; Impact: $13,500; Priority: 1944
4. Expansion packaging - Owner: RevOps Director; Impact: $14,250; Priority: 1909.5
5. Pricing and package experiment - Owner: Growth Lead; Impact: $15,750; Priority: 1785

## Weekly operating ritual
1. Re-rank all active experiments by priority score and unresolved blocker count.
2. Freeze capacity for low-score experiments until higher-score lanes are unblocked.
3. Publish one decision memo with stop/continue/scale decisions and expected MRR impact.
4. Update backlog confidence based on real outcomes, not hypothesis confidence alone.

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