Fewer than 25% of B2B teams hit their forecast. The miss is built into the system, gut feel, bad data, stage definitions nobody agreed on. We fix the underlying system and make revenue predictable.
The data exists. Nobody trusts it, and leadership makes decisions in the dark.
The average B2B forecast is submitted by reps who update their CRM once a week, optimistically. Stage names don't reflect how deals actually move. The result: a 25–40% miss rate that compounds into bad hiring decisions, wrong targets, and investor credibility problems at scale.
Missing contacts, duplicate accounts, deals untouched for 30+ days still appearing in the pipeline. When the input is unreliable, the forecast is fiction and leadership knows it, which is why they stop trusting the system and go back to gut feel.
Without a RevOps function, sales, marketing, and customer success operate on different data, different definitions, and different tools. Leadership can't see the real pipeline. Hiring decisions are delayed. Budget allocation is a guess. The business grows but it can't plan.
The stage definitions, health signals, and forecast logic we build are specific to your team, not borrowed from a generic playbook.
| Stage | Definition | Exit criteria |
|---|---|---|
| 01 · Qualified | ICP confirmed. Pain validated. Decision maker engaged. | Discovery call completed · BANT scored |
| 02 · Active | Proposal sent. Buying committee identified. | Business case delivered · CFO engaged |
| 03 · Committed | Verbal yes. Legal or procurement in process. | Contract sent · timeline confirmed |
| 04 · Closed Won | Signed. Onboarding started. | PO received · kickoff booked |
| Stalled | No activity in 14+ days at any stage. | Auto-flagged · action required |
| Signal | Weight | Alert threshold | Status |
|---|---|---|---|
| Days since last activity | High | > 14 days → flag | At risk |
| Stage age vs average | High | > 1.5× average → flag | Watch |
| Decision maker engaged | Critical | Not logged → block stage advance | Required |
| Next step booked | Medium | No calendar entry → alert | Watch |
| Email open / response rate | Medium | 0 opens in 7 days → re-engage | Monitor |
Select your stage to see the specific break points and exactly what gets built to fix them.
We review your CRM state, your forecast process, your stage definitions, and your data quality. We identify exactly where the revenue signal is breaking and what's making leadership distrust the numbers.
CRM architecture, pipeline health framework, forecast model, revenue dashboard. Built from your deal data, your team structure, your stage. The system reflects how your revenue actually moves, not how a generic playbook says it should.
Pipeline AI scores deal health daily. Forecast AI builds the model from closed-deal patterns. Revenue AI signals when the system is ready to absorb headcount. 90% of deal failures become detectable weeks before they happen.
CRM configured. Pipeline health live. Forecast submitted. Dashboard built. The next board meeting has a revenue slide that can withstand a question. The next hiring decision has a data point behind it.
No, it's the starting point. We audit the current state first, identify what's salvageable, and build the architecture around your actual data. A messy CRM is exactly the problem Phase 05 solves. You don't need to clean it up before we start.
A RevOps hire takes 3–6 months to ramp and typically inherits the same broken system. We build the system first, stage definitions, health framework, forecast model, dashboard, so that when you do hire, they're managing a working system, not building one from scratch.
HubSpot and Salesforce primarily, with support for Pipedrive and other common tools. The architecture principles apply to any CRM. The specific configuration is adapted to yours. We assess your current setup in the session and configure accordingly.
The forecast model depends on clean CRM architecture, a forecast built on bad data is still a bad forecast. We scope the engagement to what matters most for your stage, but the four outputs are designed to work together. Starting with just one is possible; getting the full benefit requires all four.