# RevOps — Marketing Skill for AI Agents

RevOps fixes the handoffs where revenue leaks. Start by defining the lead lifecycle on paper — Subscriber, Lead, MQL, SQL, Opportunity, Customer, Evangelist — with entry/exit criteria and an owner for each, because automating a broken process just breaks things faster. An MQL requires both fit (matches your ICP) and engagement (shows buying intent); a perfect-fit company that never engages isn't one, and neither is a student downloading ebooks. Score leads on explicit (fit), implicit (behavior), and negative signals, with an MQL threshold usually set at 50-80 of 100 points and recalibrated quarterly. Then enforce speed-to-lead: contacting a lead within 5 minutes makes it ~21x more likely to qualify, and after 24 hours it's effectively cold.

> Maintained by Corey Haines · v2.0.0 · Updated 2026-05-13

Install: `npx skills add coreyhaines31/marketingskills`
Source: https://github.com/coreyhaines31/marketingskills/tree/main/skills/revops

## What's inside

**The playbook covers:** Before Starting, Core Principles, Lead Lifecycle Framework, Lead Scoring, Lead Routing, Pipeline Stage Management, CRM Automation Workflows, Deal Desk Processes, Data Hygiene & Enrichment, RevOps Metrics Dashboard, Output Format, Task-Specific Questions, Tool Integrations

### Reference library

- [Automation Playbooks](https://github.com/coreyhaines31/marketingskills/blob/main/skills/revops/references/automation-playbooks.md) — Platform-specific workflow recipes for HubSpot, Salesforce, scheduling tools, and cross-tool automation.
- [Lifecycle Stage Definitions](https://github.com/coreyhaines31/marketingskills/blob/main/skills/revops/references/lifecycle-definitions.md) — Complete templates for lead lifecycle stages, MQL criteria by business type, SLAs, and rejection/recycling workflows.
- [Lead Routing Rules](https://github.com/coreyhaines31/marketingskills/blob/main/skills/revops/references/routing-rules.md) — Decision trees, platform-specific configurations, territory routing, ABM routing, and speed-to-lead benchmarks.
- [Lead Scoring Models](https://github.com/coreyhaines31/marketingskills/blob/main/skills/revops/references/scoring-models.md) — Detailed scoring templates, example models by business type, and calibration guidance.

## Key data

- Fit score (40% weight):**
- Engagement score (60% weight) — weight product usage heavily:**
- Fit score (60% weight) — weight fit heavily:**
- Engagement score (40% weight):**
- Fit score (50% weight):**
- Engagement score (50% weight):**

## Example

**Prompt:** Help me set up our lead lifecycle stages. We're a B2B SaaS company selling to mid-market. We use HubSpot as our CRM and have marketing and sales teams that aren't aligned on lead definitions.

**MQL-to-SQL handoff SLA**

MQL crosses 65-point threshold → instant alert to routed rep → rep makes first contact within 4 business hours → qualifies or rejects within 48 hours → rejected MQLs return to recycling nurture with a reason code.

**Lead scoring snippet**

Demo request +30 | Pricing page visit +20 (decay -5/wk) | VP+ title +20 | Competitor domain -50 (auto-flag) | Student/intern title -25

## FAQ

### What actually makes a lead an MQL?

Both fit and engagement. Fit is who they are — company size, industry, role, tech stack. Engagement is what they've done — visited pricing, requested a demo, returned multiple times. Neither alone qualifies: a perfect-ICP company that never engages isn't an MQL, and a student downloading every ebook isn't either. And if sales won't work your MQLs, the definition is wrong — realign it.

### How fast do I need to respond to a new lead?

As fast as possible — speed-to-lead is the single biggest factor in conversion. Contacting within 5 minutes makes a lead about 21x more likely to qualify; after 30 minutes conversion drops roughly 10x; and after 24 hours the lead is effectively cold. Build routing rules that alert reps immediately and escalate when the SLA is missed.

### How do I set a lead-scoring threshold?

Pull 6-12 months of closed-won data, retroactively score each deal with your model, and find the natural breakpoint that separated wins from losses. Set the MQL threshold just below where ~80% of closed-won deals would have scored, then validate against closed-lost. Recalibrate monthly for high-volume PLG and quarterly for mid-market or enterprise.

## Related skills

- **cold-email** — For outbound prospecting emails
- **emails** — For lifecycle and nurture email flows
- **pricing** — For pricing decisions and packaging
- **analytics** — For tracking pipeline metrics and attribution
- **launch** — For go-to-market launch planning
- **sales-enablement** — For sales collateral, decks, and objection handling

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Canonical: https://marketing-skills.com/skills/revops