RevOps analytics, reporting and forecasting for B2B SaaS
Last updated: 2026-10-21 · Reviewed by Noah Charak, Managing Director
Checkpoint GTM, a Berlin-based RevOps consultancy and HubSpot Platinum Partner, builds the reporting layer behind your revenue number for Seed to Series B B2B SaaS companies: one-page pipeline stage definitions, a stale-pipeline diagnostic, a weighted forecast model, board and team dashboards, and attribution from first touch to closed-won. We embed with your team and build it inside the CRM you already run. Fixed-scope projects cost €15K–€90K; ongoing retainers run €6K–€25K per month, all excl. VAT. In one 16-week Series B engagement, the first board-quality forecast ran in month two.
- 92%forecast accuracy, Series B SaaS
- 88%forecast accuracy, AppMagic
- €15K–€90Kfixed-scope project
What does an analytics and forecasting engagement deliver?
| Deliverable | What we build | What it fixes |
|---|---|---|
| Stage definitions | One shared page with four lines per pipeline stage: a one-sentence definition, entry criteria, exit criteria and an owner. Four to six active stages, configured in the CRM. | A stage that means three different things to three reps, so the conversion math is correct and useless. |
| Stale-pipeline diagnostic | Four numbers before every forecast review: deals past close date, median age per stage, active stage count, and deals with no activity in 14 days. | Coverage that looks healthy while half the open pipeline is past its close date. |
| Pipeline-to-forecast model | Weighted pipeline based on historical stage conversion rates, with a forecast category property owned by the manager, separate from the deal stage. | A board forecast built on gut feel and spreadsheet arithmetic. |
| Forecast reconciliation | A weekly cadence that maps every commit deal to finance's revenue view and preps the board roll-up off the same source of truth. | Finance, sales and the board each forecasting a different number. |
| Dashboards | A board dashboard, a deal inspection dashboard for weekly pipeline reviews, marketing contribution and closed-lost analysis. | Board reporting that takes days of manual exports and stitching. |
| Attribution | UTM capture on every form, a session-token property that stitches anonymous sessions to the known contact, and reports segmented by email type. | Two dashboards crediting two different channels for the same pipeline. |
| Expansion pipeline | A separate pipeline for upsell and cross-sell, with an open deal per customer and close dates that expire. | A forecast that cannot say how much of next quarter is new business and how much is the base. |
Why don't your finance, sales and board forecasts agree?
Most B2B SaaS companies past Series A run three forecasts in parallel. They look the same on a slide and they are not the same on a spreadsheet.
Cash and recognised revenue
Built from the deferred-revenue waterfall, the renewal book and the billing schedule. The most accurate on a six-month horizon, the least accurate on a thirty-day one.
Weighted bookings
Built from CRM pipeline, stage probabilities and a manager judgment overlay. The most accurate on a thirty-day horizon, unreliable past sixty days, and silent on recognised revenue.
The narrative
The CEO's story about next quarter, stitched together the week before the meeting. The least precise of the three and the most consequential.
The fix is structural, not a better dashboard
The three never reconcile because nobody owns the gap full-time. We lock the system of record for each piece (CRM for pipeline, the finance system for deferred revenue, product data for usage), then give one operator a weekly cadence to run the diff before the forecast call. Sales still owns bookings, finance still owns revenue, the CEO still owns the narrative. The operator makes sure the three agree.
Read: the three forecasts nobody reconciles →How do we build a forecast your board trusts?
The forecast is downstream. We fix the pipeline and the definitions underneath it first, then build the model and the reporting on top.
- 1 · Diagnose
Run the four numbers
The four stale-pipeline numbers, five minutes per pipeline in HubSpot or Salesforce, plus a CRM data audit for duplicates, inactive contacts and unrouted leads.
- 2 · Define
Rewrite the stages
A two-hour workshop with AE leads, the CRO and RevOps. Definition, entry, exit and owner for every stage, configured in the CRM before anyone leaves the room.
- 3 · Build
Model, dashboards, attribution
The weighted forecast model, the board and pipeline review dashboards, and the attribution plumbing, built in your CRM and connected to billing and product data where the forecast needs it.
- 4 · Run
Operate the cadence
We run the first forecast calls with you, then hand over a documented weekly cadence your team runs without us on the critical path.
Forecast and reporting results from our engagements
RevOps analytics and forecasting questions, answered
What does a RevOps analytics and forecasting engagement include?
Stage definitions, a pipeline health diagnostic, a weighted forecast model with a weekly cadence, dashboards, attribution and a separate expansion pipeline, all built inside your CRM; the deliverables table on this page shows what each one fixes.
How much does forecasting and reporting consulting cost?
Fixed-scope projects run €15K–€90K and ongoing retainers run €6K–€25K per month, excl. VAT. Where a project lands in that range depends on complexity, the number of integrations and data sources, and how much cleanup the CRM data needs first.
How long does it take to get a forecast the board trusts?
In a 16-week Series B engagement, the first board-quality forecast ran in month two, and accuracy reached 92%. In one DACH HubSpot review, four hours of pipeline cleanup, a one-page stage definition document and a 14-day inactivity rule brought all four diagnostic numbers into band within eight weeks, and the forecast started landing within 10%.
Why is our forecast wrong when the model looks fine?
Usually because the pipeline underneath it is stale or the stages mean different things to different reps. If more than 25% of open deals are past their close date, the forecast is unreliable and there is no point arguing about methodology. Fix the stages and the pipeline hygiene first, then the model.
Do we need a new BI or forecasting tool?
Not by default. We build in the CRM you already run, HubSpot or Salesforce, and connect billing, finance and product usage data where the forecast needs it. A forecast becomes defensible because someone runs the reconciliation every week, not because a new tool was bought.
How do you fix attribution when HubSpot and the warehouse disagree?
Most attribution gaps are session-stitching problems, not multi-touch problems. We add a session-token property to the contact, write it on every form fill, and run a nightly backfill that joins the contact to every earlier anonymous session from the same browser. Reports are segmented by business versus free email domain so the aggregate stays honest.
How is this different from your AI Finance & Forecasting Ops service?
Both start from the same pipeline-to-forecast model and stale-pipeline diagnostic. This service stays in the revenue reporting layer: stage definitions, the forecast model and its weekly reconciliation, dashboards and attribution, built in your CRM. AI Finance & Forecasting Ops is a 90-day embedded engagement that extends into the finance system: invoice-to-cash automation, a CFO reporting layer with the deferred-revenue waterfall, NRR and GRR, and AI agents for repetitive finance ops work.
Who owns the forecast after you leave?
Your team. Sales keeps owning the bookings forecast, finance keeps owning recognised revenue, and the CEO keeps owning the board narrative. We document the cadence, train whoever inherits the weekly cadence, and hand over the dashboards and runbook.
Read how we approach forecasting and reporting
The three forecasts inside every SaaS company that nobody reconciles
Finance, sales and the board each forecast a different number. The operator change that makes them agree.
Read →The stale-pipeline diagnostic to run before any forecast review
Four numbers, five minutes per pipeline, and the bands that tell you the forecast is fiction.
Read →Why your pipeline stages don't mean anything, and the one-page rewrite
Definition, entry, exit and owner for every stage, agreed in a workshop before any reporting work.
Read →UTMs to known contacts: fixing the attribution gap between warehouse and HubSpot
Why the form-fill UTM capture is not enough, and the session-token property that turns attribution into a join.
Read →Why your upsell motion needs its own pipeline
Separate expansion from new business so the forecast can tell the base from new logos.
Read →Case study: the Series B RevOps transformation behind 92% forecast accuracy
Operating model redesign, forecast rebuild and stack consolidation over a 16-week engagement.
Read →Get one forecast your board and your team both trust
Tell us where the number breaks today: the pipeline, the definitions, the dashboards or the attribution. We will tell you what we would fix first.
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