RevOps Audit Checklist: 50 Points to Assess Your Revenue Operations Health

Most companies don't know their revenue operations are broken until something dramatic happens — a missed forecast, a botched handoff that loses a six-figure deal, or a board meeting where nobody can explain why pipeline is down 30%.

A RevOps audit prevents those surprises. It's a systematic review of every system, process, and data flow that touches revenue. Think of it as a health checkup for your go-to-market machine.

We've run these audits for dozens of B2B companies. Here are the 50 checkpoints we evaluate, organized into 10 categories.

How to Use This Checklist

Score each item on a 0-2 scale:

0 = Not in place or severely broken
1 = Partially implemented or inconsistent
2 = Fully implemented and maintained

Total possible score: 100

Score Range	Rating	Interpretation
80-100	Excellent	Fine-tuning stage. Focus on optimization.
60-79	Good	Solid foundation with gaps. Prioritize the zeros.
40-59	Fair	Significant operational debt. Needs a focused RevOps initiative.
20-39	Poor	Revenue operations are actively costing you deals. Urgent.
0-19	Critical	Operating on heroics, not systems. Full rebuild needed.

Category 1: CRM Health (10 points)

1. CRM adoption rate exceeds 90%. Every rep logs activities, updates stages, and uses the CRM as the system of record — not spreadsheets, not their head.

2. Record deduplication process is in place. Duplicate accounts, contacts, and leads are identified and merged regularly (automated via tools like Dedupely, RingLead, or native CRM dedup rules).

3. Required fields are enforced at each deal stage. Reps cannot advance a deal without filling in critical data (MEDDPICC fields, close date, amount, next steps).

4. CRM customization follows a documented schema. Custom objects, fields, and picklist values follow naming conventions. There's a data dictionary that anyone can reference.

5. Inactive/stale records are archived or flagged. Leads untouched for 90+ days, closed-lost deals older than 12 months, and contacts with bounced emails are systematically cleaned.

Category 2: Data Quality (10 points)

6. Contact and account data is enriched automatically. Tools like Clearbit, ZoomInfo, or Apollo enrich records with firmographic and technographic data on creation or on a regular schedule.

7. Data completeness exceeds 85% for critical fields. Fields that drive routing, scoring, reporting, and segmentation are populated on 85%+ of relevant records.

8. There's a defined data governance owner. One person (or team) owns data quality standards, runs audits, and enforces hygiene processes. This isn't a side project for an intern.

9. Standardized picklist values are used (no free text for critical fields). Industry, company size, lead source, loss reason — all use controlled picklists, not free text where reps type whatever they want.

10. Data decay is actively managed. Job titles change, people leave companies, phone numbers go stale. There's a process (automated or manual) to refresh data at least quarterly.

Category 3: Process Documentation (10 points)

11. Lead-to-opportunity handoff is documented and followed. There's a written process for when, how, and under what criteria marketing hands leads to sales. Both sides agree on it.

12. Sales stages have clear definitions and exit criteria. Every stage in your pipeline has a written definition of what's true about the deal at that stage and what must happen before it advances.

13. Opportunity-to-CS handoff is documented. When a deal closes, there's a defined process for transitioning the customer to the post-sales team — including what data transfers, what meetings happen, and who's responsible.

14. Escalation paths are defined. Reps know who to escalate to for pricing exceptions, legal review, security questionnaires, and executive engagement. It's not tribal knowledge.

15. Process documentation is version-controlled and current. Docs are stored centrally (Notion, Confluence, Google Docs), have last-updated dates, and are reviewed at least quarterly. Not a dusty wiki from 2022.

Category 4: Tech Stack (10 points)

16. There's a documented tech stack map. Every tool in the revenue tech stack is listed with its owner, cost, renewal date, and integration points. You can draw the data flow on a whiteboard.

17. Tool utilization is tracked. You know whether the team actually uses the tools you're paying for. License utilization below 60% is a red flag.

18. No redundant tools exist. You don't have two email sequence tools, two data enrichment providers, or three different places where reps log calls.

19. Integration health is monitored. Syncs between CRM, marketing automation, and other tools are monitored for errors. Broken syncs are caught and fixed within 24 hours, not discovered weeks later.

20. There's a tool evaluation and procurement process. New tools go through a defined review (security, integration, cost, overlap with existing stack) before purchase. No more rogue credit card purchases.

Category 5: Lead Management & Scoring (10 points)

21. Lead scoring model is documented and active. There's a scoring model that combines demographic/firmographic fit with behavioral engagement. It's not just "downloaded a whitepaper = MQL."

22. MQL definition is agreed upon by sales and marketing. Both teams can articulate what an MQL is, and the definition hasn't changed in the last 6 months without both teams agreeing.

23. Lead routing rules are automated and tested. Leads are routed automatically based on defined rules (territory, segment, round-robin). Manual routing is the exception, not the norm.

24. Lead SLAs are defined and enforced. There's a defined time window for sales to follow up on marketing-qualified leads, and there's an escalation process when SLAs are missed.

25. Recycling and nurture paths exist. Leads that don't convert aren't just abandoned. There's a process to recycle them back to marketing for nurture or re-engage them after a defined period.

Category 6: Pipeline Management (10 points)

26. Pipeline coverage ratio is tracked weekly. You know your pipeline-to-quota ratio by segment and by rep. The benchmark is 3-4x for most B2B SaaS.

27. Pipeline creation targets are set and monitored. It's not just about closing pipeline — you're tracking whether enough new pipeline is being generated to hit future quarters.

28. Deal velocity metrics are calculated. You track the average days in each stage and the overall sales cycle length. You can spot deals that are stalling.

29. Pipeline hygiene reviews happen weekly. Managers review pipeline with reps at least weekly, pushing on stale deals, validating close dates, and challenging amounts.

30. Win/loss analysis is conducted regularly. You systematically analyze why deals are won or lost, and findings are shared with product, marketing, and leadership.

Category 7: Forecasting (10 points)

31. Forecasting methodology is defined. There's a documented method (weighted pipeline, stage-based probability, AI-assisted, rep commit, or combination) used consistently.

32. Forecast accuracy is tracked over time. You compare forecasted vs actual results each quarter and track the variance trend. Best-in-class teams hit within 10% accuracy.

33. Multiple forecast views exist. You don't rely on a single number. You have best case, commit, and worst case — or a similar tiered approach.

34. Forecast submissions happen on a regular cadence. Reps submit forecasts weekly. Managers roll up by segment. VP presents to leadership. The cadence is defined and followed.

35. Sanity checks are built in. Deals with close dates in the past, opportunities with no activity in 30+ days still in "commit," or pipeline with 0% probability are automatically flagged.

Category 8: Reporting & Analytics (10 points)

36. There's a defined reporting hierarchy. Different stakeholders get different reports at different cadences. ICs see activity metrics daily. Execs see pipeline and revenue metrics weekly. The board sees strategic metrics quarterly.

37. Reports are automated, not manually built. Dashboards pull from live data. Nobody is spending Friday afternoon copy-pasting numbers into a slide deck.

38. Marketing attribution model is in place. You can attribute pipeline and revenue to marketing channels and campaigns. The model (first-touch, last-touch, multi-touch, or W-shaped) is documented and understood.

39. Unit economics are tracked. CAC, LTV, CAC payback period, and magic number are calculated regularly and inform investment decisions.

40. Reporting definitions are standardized. Everyone means the same thing when they say "pipeline," "MQL," "win rate," or "ACV." Definitions are documented and shared.

Category 9: Customer Success & Retention (10 points)

41. Health scoring model is in place. Customer accounts are scored based on usage, engagement, support ticket volume, NPS, and other signals. At-risk accounts are identified proactively.

42. Renewal process starts 90+ days before expiration. Renewals aren't a fire drill. There's a defined timeline with triggers, outreach sequences, and escalation points.

43. Expansion pipeline is tracked separately. Upsell and cross-sell opportunities have their own pipeline metrics, not lumped in with new business.

44. Churn reasons are systematically captured. When a customer leaves, the reason is logged in a structured field (not free text), analyzed quarterly, and shared with product and leadership.

45. NRR (Net Revenue Retention) is calculated and tracked. You know your NRR number, how it trends over time, and what's driving it (expansion vs contraction vs churn).

Category 10: Alignment & Governance (10 points)

46. RevOps has a seat at the leadership table. RevOps isn't buried under sales or marketing. The RevOps leader has a direct line to the CRO or CEO and influences go-to-market strategy.

47. Cross-functional SLAs exist. Marketing-to-sales handoff SLAs, sales-to-CS handoff SLAs, and support escalation SLAs are all defined and measured.

48. Change management process exists. CRM changes, process updates, and new tool rollouts go through a defined change process — not a Slack message saying "hey, I updated the picklist."

49. Regular cross-functional reviews happen. Sales, marketing, CS, and RevOps meet at least monthly to review metrics, identify friction points, and align on priorities.

50. There's a RevOps roadmap. RevOps has a documented backlog of initiatives, prioritized by impact, with timelines and owners. It's not just reacting to fire drills.

Running the Audit

Step 1: Self-assess. Have your RevOps team score each checkpoint. Be honest — inflated scores help nobody.

Step 2: Validate. Spot-check scores with data. If you scored a 2 on "CRM adoption exceeds 90%," pull the actual login and activity data to confirm.

Step 3: Prioritize. Sort by score (zeros first). Within zeros, prioritize by revenue impact — things that directly affect pipeline and conversion before things that affect efficiency.

Step 4: Build a 90-day plan. Pick the 5-7 items with the biggest gap and build a concrete project plan. Don't try to fix everything at once.

Step 5: Re-audit quarterly. Track your score over time. A 10-point improvement per quarter is a reasonable target for a team with dedicated RevOps resources.

What We See in Practice

Across our audits, the most common failure areas are:

Data quality (Category 2): Almost everyone scores low here. Data decays fast, and most teams underinvest in governance.
Process documentation (Category 3): Processes exist in people's heads, not in written docs. This kills you when people leave.
Forecasting (Category 7): Forecast accuracy is rarely tracked, and there's no feedback loop to improve it.
Tool utilization (Category 4): Companies overspend on tools and underinvest in adoption and training.

The median score for companies we audit is 47 out of 100. The best we've seen is 89. There's always room to improve.

Start the audit. Find the gaps. Fix them systematically. That's what RevOps is about.