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RevOps Analytics & Forecasting

We do revenue analytics that hold up when someone checks: pipeline and stage conversion, win rate on cohorts that are actually defined, attribution across partners and channels, renewal and churn risk that's been back-tested on your own history, and forecasting. Every analysis says what was queried, what was excluded and what the denominator is. When we get one wrong, the correction is dated and goes at the top.

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This is for you if

  • Two teams gave you two different win rates, and both are confident.
  • Finance needs CRM numbers that can go in a board deck.
  • Partner and channel attribution runs on whoever argued hardest.

9.1%

the real new-business win rate at one company. The 24.7% in a deck that had been quoted for seven months had counted renewals and expansions as wins against new-business losses.

What's included

Pipeline and conversion

Stage-reach conversion computed properly, young cohorts shown separately, unmapped sources logged instead of absorbed.

Win and loss

A generated exclusion waterfall from every closed deal down to true new business, plus a gate that refuses to cut a rate by any field that's filled in differently for wins and losses.

Attribution

Campaigns, partners, channels. Confirmation logic instead of last-touch guessing. A ranked view, not a debate.

Renewal and churn risk

Renewal dates with a confidence rank on where each one came from. A risk model back-tested before anyone acts on it.

Forecasting and board reporting

Methods tested against prior quarters, an honest range, and a list of what we didn't verify.

Dashboards

In HubSpot or your BI tool, documented, with a dated correction log.

How it goes

  1. 1

    Question

    The one decision the analysis has to inform. Written down first.

  2. 2

    Basis

    Cohort, exclusions and denominators agreed before we produce a number.

  3. 3

    Analysis

    Reproducible from the data. Thin cells flagged, not hidden. Caveats travel with the numbers.

  4. 4

    Publish

    Where decisions get made, with the method, so you can re-run it next quarter without us.

From the work

RevOps analytics

24.7% → 9.1%real new-business win rate

The win-rate analysis nobody could reproduce

A 28-page win/loss deck, still being quoted seven months on, reported a 24.7% win rate on 174 deals that didn't exist in any reading of the CRM. It had counted expansion, renewal and onboarding wins against new-business losses. Rebuilt from 1,304 closed deals down to 1,006 real new-business deals, the number was 9.1%.

  • The useful output wasn't the number. It was a gate that refuses to cut a rate by any field that's filled in differently for wins and losses. Nine fields got refused.
  • Subscription ARR was filled on 96.2% of won deals and 15.3% of lost ones. The original deck's whole velocity section rested on a field like that.
Related: RevOps Analytics & Forecasting

RevOps analytics

763 company-yearsback-tested

The churn signal every CRM encodes, that had no signal

A back-test over 763 company-years and 124 churn events showed engagement recency, worth 30 points in the renewal-risk model, predicted nothing. Churning accounts had been contacted more recently, not less. We rebuilt it around the four signals that held up, with coverage and confidence stated on every response.

  • Account tier, ARR and ticket counts were each skewed by reverse causality or mapping bias.
Related: RevOps Analytics & Forecasting

Questions we get about this

Why do our win rates keep changing?

The cohort changes. Renewals, expansions and onboarding records get mixed into new business, or deals get cut by a field that's filled in for wins and empty for losses. Fix the definition and the number stops moving.

Can you build a churn or renewal risk model?

Yes, and we back-test it on your history first. At one company, engagement recency, worth 30 points in the existing model, predicted nothing across 763 company-years. Churning accounts had been contacted more recently, not less. We rebuilt it around the four signals that held up.

Do you do partner and channel attribution?

Yes. Multi-dimensional attribution across partner ecosystems with confirmation logic and coverage gaps, so you can see which alliances actually produced revenue.

What tools do you use?

SQL and Postgres, Python for back-testing, HubSpot reports, and your BI tool if you have one. Everything reproducible from a query.

Usually goes with

CRM Cleanup & Migration

Duplicates, dead fields, deals counted twice, lead sources that went nowhere. We find them, fix them, and write the rule that keeps them from coming back.

Learn more

HubSpot Consulting

Pipelines, properties, lifecycle stages, workflows, reporting. Set up so the numbers in HubSpot are the numbers leadership actually sees.

Learn more

Your Own AI GTM Platform

Your own sales platform on top of HubSpot, built with your engineer so you own it. No per-seat pricing, no vendor deciding your roadmap.

Learn more

Book a free CRM audit

30 minutes with us, looking at your HubSpot. You leave with a list of what's broken and what it'd take to fix. No deck.

Book a free CRM audit or email neel@salecopy.io