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revenue-operations

operationsv1.0.0

RevOps frameworks, funnel metrics, forecasting models, GTM alignment, and operational efficiency for scaling teams.

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Revenue Operations

Workflow

1. Revenue Funnel Definitions

Align ALL teams on the same definitions:

StageDefinitionOwnerSLA
VisitorHit website or contentMarketing
LeadKnown contact (form fill, signup)MarketingEnrich within 24h
MQLMeets scoring threshold (fit + engagement)MarketingRoute within 5 min
SALSales accepted, meeting bookedSDR/BDRContact within 1 hour
SQLQualified by sales (BANT/MEDDIC confirmed)AEDiscovery within 3 days
OpportunityIn pipeline with defined next stepsAEAdvance or close within 90 days
Closed WonContract signed, revenue bookedAE → CSHandoff within 48h

Conversion benchmarks (B2B SaaS):

Stage transitionBenchmark
Visitor → Lead2-5%
Lead → MQL15-30%
MQL → SAL60-80%
SAL → SQL40-60%
SQL → Opportunity50-70%
Opportunity → Closed Won20-30%

2. Forecasting Models

Weighted pipeline (standard):

Deal forecast = Deal value × Stage probability
Total forecast = Σ all deal forecasts

Historical conversion (more accurate):

Expected revenue = Current stage count × Historical stage-to-close rate × Average deal size

Bottoms-up (most accurate, most work):

Rep forecast = Committed + (Best case × 0.5) + (Pipeline × 0.15)
Team forecast = Σ rep forecasts × Historical accuracy multiplier

Forecast accuracy tracking:

MonthForecastActualAccuracy
Jan$250k$230k92%
Feb$280k$310k90%
Mar$300k$275k92%

Target: ±10% accuracy consistently. If not: reps are sandbagging or being optimistic.

3. GTM Alignment

Weekly GTM standup (30 min):

  • Marketing: pipeline contribution this week, upcoming campaigns
  • Sales: deal updates, blockers, competitive intel
  • CS: churn risks, expansion opportunities, product feedback
  • RevOps: funnel health, forecast update, process issues

Monthly revenue review (60 min):

  • Funnel conversion rates vs targets
  • Pipeline coverage (3x target = healthy)
  • Win rate trends by segment, source, rep
  • Churn and expansion ARR
  • Forecast vs actual analysis

4. Quota & Territory Planning

Quota setting formula:

Company target = Board-approved ARR target
Sales capacity = # ramped AEs × quota per AE
Quota per AE = Company target / # ramped AEs × 1.15 (buffer for attrition)

Territory design principles:

  • Equal opportunity (similar pipeline potential per territory)
  • Minimize travel (geographic clustering)
  • Account for existing relationships (don't reassign active deals)
  • Review quarterly (territories drift as markets change)

Ramp schedule:

Month% of full quotaExpectation
1-20%Training, shadowing, certification
325%First qualified meetings
450%First deals in pipeline
575%First closed deals
6+100%Fully ramped

5. Handoff Processes

Marketing → SDR (MQL handoff):

Trigger: Lead score ≥ MQL threshold
Data passed: Lead source, content consumed, pages visited, company info, score breakdown
SDR action: Research (5 min) → personalized outreach within 1 hour
Feedback loop: SDR marks SAL accepted/rejected with reason → Marketing adjusts scoring

SDR → AE (SAL handoff):

Trigger: Discovery call completed, BANT confirmed
Data passed: Pain points, budget range, timeline, decision process, competitors
AE action: Review notes → demo prep → schedule demo within 3 days
Handoff format: Warm intro email (SDR introduces AE + summarizes conversation)

AE → CS (Closed Won handoff):

Trigger: Contract signed
Data passed: Contract terms, use case, success criteria, stakeholders, technical requirements
CS action: Onboarding kickoff within 48 hours
Handoff format: Internal doc + joint call (AE + CS + customer)

6. Tech Stack Audit

Core RevOps stack:

LayerToolPurpose
CRMHubSpot / SalesforceSingle source of truth
EngagementOutreach / SalesloftSales sequences
IntelligenceGong / ChorusCall recording + analysis
EnrichmentClearbit / ApolloContact and company data
AttributionHubSpot / DreamdataMarketing attribution
BILooker / MetabaseCross-functional dashboards
CommunicationSlack + CRM integrationReal-time notifications

Audit checklist:

  • Data flows bidirectionally between all tools
  • No manual data entry between systems
  • Single source of truth for each data type
  • Reporting pulls from one source (not multiple conflicting dashboards)
  • Total cost < 15% of ARR (healthy range)

7. RevOps Metrics Dashboard

MetricCadenceTarget
Pipeline coverage ratioWeekly3-4x quarterly target
Win rateMonthly20-30%
Average sales cycleMonthlyTrack trend, reduce 10% YoY
CAC paybackMonthly< 12 months
Net revenue retentionMonthly> 110%
Forecast accuracyMonthly±10%
Speed to leadReal-time< 5 minutes
Pipeline created per repWeeklyEven distribution