AI Lead Qualification Playbook Generator

# AI Lead Qualification Playbook - Revenue Operations Team

## Baseline
- Monthly inbound leads: 540
- Current MQL to SQL rate: 24.0%
- Target MQL to SQL rate: 35.0%
- MQL to SQL gap: 11.0 percentage points
- Current SQL to win rate: 21.0%
- Average deal size: $18,500
- Qualification SLA: 26 hours
- Primary bottleneck: Slow qualification follow-up
- Qualification pressure: 82.6 / 100 (Critical)
- Recommended cadence: Run daily qualification standups with same-day blocker escalation.

## Owner model
- Marketing owner: Demand Gen Lead
- Sales owner: Sales Manager
- RevOps owner: RevOps Lead

## Estimated current economics
- Estimated qualified leads per month: 130
- Estimated qualified pipeline per month: $2,405,000

## 90-day qualification lines
| # | Stage | Objective | Owner | Due window | Success metric | Supporting route |
|---|---|---|---|---|---|---|
| 1 | ICP and entry criteria | Tighten ICP filters and form-level qualification fields before routing leads into sales. | Demand Gen Lead | Week 1 | Invalid lead share drops and qualified lead acceptance increases | AI Growth and Monetization Hub (/ai-growth-monetization-hub) |
| 2 | Qualification SLA and routing | Set SLA windows and owner-based triage so inbound leads are qualified before intent decays. | RevOps Lead | Week 1 | Median first qualification touch falls below SLA target | AI Rollout KPI Scorecard Generator (/ai-rollout-kpi-scorecard-generator) |
| 3 | Discovery scorecard | Standardize discovery quality checks to improve SQL consistency across reps. | Sales Manager | Week 2 | MQL to SQL conversion trends toward target with fewer low-quality SQLs | AI Model Evaluation Test Plan Generator (/ai-model-evaluation-test-plan-generator) |
| 4 | Handoff and pipeline hygiene | Enforce stage-entry criteria and handoff completeness to reduce pipeline leakage. | RevOps Lead | Week 2-3 | Stage regression rate decreases and stale SQL count drops | AI Business Case Memo Generator (/ai-business-case-memo-generator) |
| 5 | Monetization feedback loop | Run monthly feedback from win/loss data back into qualification rules and offer design. | Demand Gen Lead | Week 4 | SQL to win rate and revenue per qualified lead trend upward | AI A/B Test Manager Generator (/ai-ab-test-manager-generator) |

## Weekly review ritual
1. Review MQL to SQL trend, SLA misses, and stage-regression count in one scoreboard.
2. Escalate one bottleneck with an accountable owner and due date.
3. Validate discovery quality samples and retire low-signal qualification rules.
4. Publish one weekly summary with net conversion uplift and next sprint focus.