Sales – RevOps
Make pipeline and forecast questions fast, credible, and repeatable across Sales, Finance, and Leadership.
- Diagnose forecast misses quickly and explainably.
- Track pipeline quality (not just pipeline volume).
- Build weekly exec reporting that doesn’t break every quarter.
- Align Sales + Finance with the same definitions.
- Reusable workflows instead of ad-hoc spreadsheets.
- Auditable outputs: how each number was produced.
- Less time in “data assembly”, more time in decision-making.
- Compute deltas vs last week (new, slipped, pulled-in, lost).
- Explain the “why” by segment, stage, and owner.
- Produce an exec-ready summary + action list.
- Coverage + conversion + time-in-stage in one place.
- Detect stale opps, missing next steps, and stage anomalies.
- Make “pipeline quality” measurable and consistent.
- Spot deals that inflate commit without evidence.
- Highlight “what changed” signals: activity drops, stage regression, stalled cycles.
- Keep the logic visible so stakeholders trust the call.
It’s Monday morning. Leadership wants to know: “Are we on track? If not, what changed—and what do we do this week?” RevOps pulls a forecast update, but the real work is always the same: reconcile definitions, explain deltas, and identify actions.
- Pull pipeline + bookings + CRM activity (live queries).
- Apply shared definitions (“committed”, “best case”, “slipped”, “pulled in”).
- Compute deltas vs last week and explain the change.
- Produce an exec-ready summary and a rep/team action list.
- A single artifact that can be rerun next week (same logic, new data).
- Auditability: how each number was produced, end to end.
- Shareability: stakeholders can reference the same source of truth.
- Bookings forecast by segment and stage.
- Forecast vs actuals (error by segment / owner).
- Slippage and pull-in: what moved, and why.
- Coverage (weighted and unweighted) vs target.
- Stage conversion and time-in-stage.
- “Stale” opportunities and missing next steps.
We’ll later map these to a semantic layer so “coverage” and “slippage” mean the same thing everywhere— but this page stays dataset-agnostic for now.
- Which segments drive the biggest forecast error?
- What changed vs last week: new, slipped, pulled-in, lost?
- Where is stage conversion slowing down—and why?
- Which deals should be removed from commit—and which should be escalated?
- How much pipeline is “real” given historical conversion?
- Which reps/teams need attention this week?
- What’s the smallest set of actions that increases confidence this month?
- Are we over-relying on a single segment, region, or source channel?
A RevOps workflow is “good” when you can answer the same set of questions every week with less friction, more credibility, and less debate. 42Cells is optimized for that: keep the logic visible, keep the work reusable, and keep the results grounded in real execution.