| name | revops |
| description | When the user wants help with revenue operations, lead lifecycle management, or marketing-to-sales handoff processes. Also use when the user mentions 'RevOps,' 'revenue operations,' 'MQL to SQL,' 'lead scoring,' 'funnel alignment,' or 'pipeline management.' |
| allowed-tools | Read, Write, WebSearch, WebFetch, AskUserQuestion |
| model | sonnet |
Revenue Operations (RevOps)
Expert knowledge for aligning marketing, sales, and customer success around a unified lead lifecycle, accurate attribution, and scalable revenue processes.
What RevOps Is
Revenue Operations (RevOps) is the organizational function that aligns marketing, sales, and customer success under shared data, shared definitions, and shared accountability for revenue outcomes.
RevOps answers: "Why is our pipeline number different from what marketing reports? Why are leads being ignored? Why can't we forecast accurately?"
Lead Lifecycle Stages
Define lifecycle stages before building any scoring, automation, or reporting. Shared definitions prevent the "we sent 100 MQLs, they only worked 10" argument.
Standard lifecycle stages:
| Stage | Definition | Owner |
|---|
| Subscriber | Opted in to marketing but no further intent signals | Marketing |
| Lead | Provided contact info; some profile or activity data | Marketing |
| MQL (Marketing Qualified Lead) | Met threshold score; ready for sales contact | Marketing → Sales handoff |
| SAL (Sales Accepted Lead) | Sales confirmed it meets their criteria | Sales |
| SQL (Sales Qualified Lead) | Sales has engaged and confirmed a real opportunity | Sales |
| Opportunity | Active deal in pipeline | Sales |
| Customer | Closed/won | Sales → CS |
| Churned | Customer who has left | CS |
| Disqualified | Explicitly not a fit | Sales |
Critical: SAL stage. If marketing sends MQLs and sales can reject them without recording why, you have no feedback loop. The SAL stage (where sales accepts or rejects with a reason) is the handoff accountability mechanism.
MQL Criteria Design
An MQL is a lead that marketing has qualified to the point where sales engagement is appropriate.
MQL threshold approach:
Demographic fit (who they are):
- Job title match (e.g., VP Marketing, Head of Revenue, Marketing Manager)
- Company size match (e.g., 50-500 employees)
- Industry match
- Geography match
Behavioral intent (what they did):
- Requested a demo or trial
- Visited pricing page 2+ times
- Downloaded a bottom-of-funnel resource (ROI calculator, comparison guide)
- Attended a webinar
- Replied to an email
Disqualifying signals (automatic exclusions):
- Free email domain (Gmail, Yahoo) for B2B products
- Competitor domain
- Student or job seeker indicators
- Out-of-ICP company size
MQL scoring formula example:
| Attribute | Score |
|---|
| Demo request | +40 |
| Pricing page visit (2+) | +25 |
| Bottom-of-funnel content download | +20 |
| Webinar attendance | +15 |
| Top-of-funnel content download | +5 |
| ICP title match | +20 |
| ICP company size match | +15 |
| Free email domain | -50 |
| Competitor domain | -100 |
MQL threshold: Score ≥ 50 (tune based on conversion data)
SLA Design Between Marketing and Sales
An SLA (Service Level Agreement) defines what each team commits to.
Marketing → Sales SLA:
- We will only send leads that meet MQL criteria [defined explicitly]
- We will send leads with complete data (name, email, company, title, lead source)
- We will include behavioral context (what they did to become an MQL)
Sales → Marketing SLA:
- Sales will attempt contact within [X] hours of MQL creation (typically 4-8 hours for hot leads)
- Sales will accept or reject each MQL within [Y] business days with a documented reason
- If rejected, sales will provide reason from a predefined list (not a fit, bad timing, duplicate, etc.)
SLA reporting cadence: Weekly review of SLA adherence in both directions. This is a shared meeting with both marketing and sales.
Pipeline Velocity
Pipeline velocity measures how fast opportunities move through your pipeline.
Formula:
Pipeline Velocity = (Qualified Opportunities × Average Deal Value × Win Rate) / Average Sales Cycle Length
Example:
- 50 qualified opportunities
- Average deal value: $12,000
- Win rate: 25%
- Average sales cycle: 45 days
→ Pipeline velocity = (50 × $12,000 × 0.25) / 45 = $3,333/day
Using pipeline velocity to identify problems:
| Metric drops | Problem area |
|---|
| Fewer opportunities | Top-of-funnel; MQL quality or volume |
| Lower average deal size | ICP misalignment; wrong segments |
| Lower win rate | Competitive pressure; sales process; product gaps |
| Longer cycle | Evaluation friction; wrong stakeholders; missing content |
Funnel Conversion Benchmarks
Use these as reference points, not targets (every market differs).
B2B SaaS benchmarks:
| Stage → Stage | Typical Rate |
|---|
| Lead → MQL | 20-30% |
| MQL → SAL | 70-85% (if MQL criteria are tight) |
| SAL → SQL | 60-75% |
| SQL → Opportunity | 80-90% |
| Opportunity → Closed/Won | 20-30% (enterprise), 30-50% (SMB) |
If your rates deviate significantly, investigate:
- Lead → MQL drop: Is your lead volume low quality or high intent? Review source mix.
- MQL → SAL drop: Are MQL criteria too loose? Interview sales about rejection reasons.
- Opportunity → Won drop: Competitive? Product gap? Sales skills? Check loss reasons.
CRM Hygiene Standards
Bad CRM data produces bad decisions. Enforce hygiene at the point of entry.
Required fields for every lead/contact:
- First name, last name
- Business email
- Company name
- Job title
- Lead source (original source, specifically — not just "web")
- MQL date (when they crossed the threshold)
Required fields for every opportunity:
- Close date (realistic, not aspirational)
- Stage (with clear entry/exit criteria for each)
- Deal value
- Primary competitor
- Loss reason (mandatory on close-lost)
CRM hygiene automation:
- Duplicate detection on create (email match)
- Email validation on create (block free domains for B2B)
- Required field enforcement (prevent save without critical fields)
- Automated inactivity alerts (opportunities with no activity in 14+ days)
Attribution Reporting
Attribution models:
| Model | Credit logic | Use for |
|---|
| First touch | 100% to first touchpoint | Understanding what creates awareness |
| Last touch | 100% to last touchpoint before conversion | Understanding what closes deals |
| Linear | Equal across all touchpoints | Understanding the full journey |
| Time decay | More credit to recent touchpoints | Mid-length sales cycles |
| W-shaped | 40% first, 40% last, 20% MQL creation point | Most balanced for marketing |
| Data-driven | Algorithm based on actual path analysis | When you have enough conversion data |
Multi-touch attribution requirement: Any single-touch model will under-credit content and top-of-funnel activities. Use at minimum a W-shaped or linear model for marketing reporting.
Tools: HubSpot, Salesforce (native), Bizible/Marketo Measure (best-in-class), Dreamdata.
Marketing-to-Sales Handoff Process
Handoff checklist for each MQL:
- Lead enriched with company data (Clearbit, Apollo enrichment)
- MQL reason documented (which criteria triggered; what they did)
- Lead assigned to correct rep (routing rules applied)
- Rep notified via CRM notification + Slack alert
- 4-hour SLA clock started
- If not contacted in 4 hours: escalation to SDR manager
Handoff notification template (Slack or email):
New MQL: [First Name Last Name] at [Company]
Title: [Job Title]
Score: [Score]
Why MQL: [Brief — e.g., "Requested demo + pricing page 3x + VP Marketing"]
Company size: [X employees]
Key pages: [List of last 3 pages visited]
CRM record: [Link]
Suggested approach: [1-line context hint]
Common Rationalizations
| Rationalization | Reality |
|---|
| "Marketing and sales just have different definitions of a good lead" | That's a RevOps problem to solve, not accept. Shared definitions are the foundation. |
| "We track attribution — last touch is fine" | Last touch credits the salesperson's close, not the content that created the opportunity. You'll systematically defund top-of-funnel. |
| "The CRM is sales' responsibility" | CRM data quality is everyone's responsibility. Marketing's reporting is only as good as the data sales enters. |
| "We don't have time for SLAs — we just respond as fast as we can" | "As fast as we can" without measurement produces undocumented inconsistency. SLAs are measurable; effort is not. |
| "Lead scoring is too complicated for our stage" | A simple scoring model (fit × intent) beats no model. You don't need Marketo to implement a spreadsheet score. |
Verification
