PLAYBOOK · 08
Revenue Operations Install
A 30-day sprint to stand up the revenue operating system. CRM architecture rebuilt, lifecycle stages defined, attribution chain wired, forecasting model installed, reporting layer joined to CRM closed-won. The foundation every other layer depends on.
01CAPABILITY LAYER
This lives inside the Revenue Operations layer.
Revenue Operations is the systems layer that makes pipeline visible and forecasts repeatable. Without it, marketing reports ROAS, sales reports closed-won, finance reports MRR — and the three numbers do not reconcile. This playbook installs the architecture that makes them reconcile.
See: Revenue Operations layerOutcomes
What this hands you when it lands.
- 01CRM data model rebuilt with auditable stage definitions + required fields
- 02Lifecycle stages wired with explicit promotion criteria and automation triggers
- 03Server-side attribution APIs deployed (Meta CAPI, Google Enhanced Conversions, LinkedIn CAPI)
- 04Forecasting model: stage-weighted, conversion-velocity, win-rate by source
- 05Looker Studio dashboard joining ad spend → leads → opps → closed-won
- 06Operations cadence: weekly pipeline, monthly forecast, quarterly funnel + CAC review
The problem
Why most teams get this wrong.
Most companies hit a ceiling at $5–20M ARR where pipeline becomes opaque. Stages mean different things to different reps. Attribution is a guess. Forecast is a vibe. The fix is not a new CRM — it is the operating model on top of the existing CRM. This playbook installs that operating model.
The system
Six modules. One installed revenue OS.
CRM data model rebuild
Stage definitions, required fields, ownership rules, automation triggers, data hygiene. Same architecture pattern across HubSpot, Salesforce, GHL, Pipedrive, Close.
Lifecycle stage definitions
Explicit promotion criteria for every transition. "Stage 2" means the same thing across the whole GTM team. Automation fires on every transition.
Attribution chain
Server-side conversion APIs (Meta, Google, LinkedIn) tied to CRM closed-won. Acquisition source captured, propagated, joined to revenue.
Forecasting model
Stage-weighted forecast, conversion-velocity model, win-rate by source, payback period by channel. Defensible numbers, not optimistic ones.
Reporting layer
Looker Studio (or Hex / Tableau) joining ads spend, GA4 sessions, CRM opps, finance closed-won. One dashboard, one number.
Operations cadence
Weekly pipeline review, monthly forecast review, quarterly funnel + CAC review. Cadence + dashboards + ownership = reliability.
Deliverables
Artifacts handed off, in writing.
Timeline
A 30-day sprint, four phases.
Audit + architecture
Existing CRM data model audit. Stage definitions inventory. Attribution gap analysis. Forecasting model review. Output: target architecture.
Rebuild + wire
New CRM stages deployed. Required fields + automation triggers configured. Server-side APIs deployed. Reporting reconciled.
Build forecasting + dashboards
Forecasting model + Looker Studio dashboard built. Stage-weighted forecast + payback model live.
Train + cadence kickoff
GTM team training. Cadence kickoff (weekly + monthly + quarterly). Hand-off documentation. Optional Embedded Retainer.
FAQ
Questions we get asked.
01Is this the same as hiring a fractional RevOps person?+
No. Fractional RevOps fills a seat. This playbook installs a system. The fractional or in-house RevOps person AFTER this engagement operates what we built — the system is the asset.
02Can this work in our existing CRM?+
Yes — HubSpot, Salesforce, Pipedrive, Close, GoHighLevel. The architecture pattern is consistent across CRMs; the platform is the substrate, not the strategy.
03How does this handle ATT / iOS 14 / cookie restrictions?+
Server-side conversion APIs (Meta CAPI, Google Enhanced Conversions, LinkedIn CAPI), first-party cookies, CRM tie-out. Attribution survives all three. We deploy the full stack.
04Will this disrupt our existing GTM team?+
It will give them better data. We do not change ownership rules without consensus from sales + marketing leadership. The new system is built around the existing org chart.
05How long until forecast accuracy improves?+
First reasonable forecast: end of week 4. Forecast accuracy improves over 6–12 months as cohort data accumulates. Conversion velocity calibrates over the same window.
06What deliverables do we own?+
CRM data model, automation triggers, attribution endpoints, Looker Studio dashboard, SOP documents, training materials. Code and configurations belong to you.
07Does this work for B2C / B2B / e-commerce?+
Yes — the discipline is universal; implementations vary. B2B emphasizes pipeline + forecasting; B2C emphasizes lifecycle + LTV; e-commerce emphasizes attribution + retention.
08What does this cost?+
Audit: fixed fee, low five figures. Build sprint: 4–6 weeks, fixed fee, mid-five-figures. Embedded Retainer for ongoing operations: monthly, scoped to surface area.
Run it
Install the revenue operating system.
A strategy call gets you a tailored 30-day plan scoped to your stack within 48 hours.