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B2B Sales

Stop wrangling sales data.
Start modeling the revenue org.

Sales people, quotas, territories, ramp, teams, forecasts, pipeline — most companies keep these in seven different tools and reconcile them by hand every quarter. DimTable turns them into one clean dimensional model.

The problem

Everyone has the same data, scattered the same way

The org chart lives in the HRIS. Quotas live in a spreadsheet the comp team guards. Territories live in the CRM — and in three people's heads. Ramp expectations live nowhere.

None of it joins. So every quarter someone rebuilds the same brittle workbook to answer questions that should be trivial: Are we covered on quota? Which reps are behind their ramp?

A sales org isn't a pile of spreadsheets. It's a dimensional model waiting to be written down.

The building blocks

The seven things every sales org has

Sales People

Every rep with role, seniority, and manager — plus the hire date that drives everything downstream.

Teams

The hierarchy. Reps roll up to managers, managers to segments, segments to the org. Model it once and every number rolls up cleanly.

Territories

Who owns what, and crucially, when. Territories change; we keep the history with effective dating.

Quotas

Overall and by product, set by period. An effective-dated target that moves with promotions, reorgs, and resets.

Ramp Schedules

A new rep shouldn't carry full quota on day one. Ramp turns a hire date into expected capacity over time.

Forecast

What each team commits and best-cases, by period. Commit and upside sit next to actuals.

Actuals vs. Pipeline

What actually closed, and what's still open behind the number. Coverage ratios by team and product.

The idea that makes all of this trustworthy is effective dating. When a rep changes territory, gets promoted, or a quota resets mid-year, we don't overwrite the old value — we close it and open a new one. Ask “what was true in Q2?” and the model answers with the Q2 org chart, not today's.

End to end

Hire to forecast, in three moves

1

Ingest

New hires from the HRIS, deals and pipeline from the CRM, and the quota and comp context that usually hides in spreadsheets.

2

Model

Conformed dimensions and revenue facts, effective-dated, with ramp-adjusted quota baked in.

3

Sync

Clean, modeled tables land in your warehouse so BI and forecasting just work.

Your data team stops being a spreadsheet janitor and starts getting beautiful, conformed tables they can actually build on.

The payoff

What you can finally answer

Ramp-adjusted coverage — quota credit scales with the ramp curve, so a team of new hires isn't judged like a team of veterans.

A forecast you can defend — commit and best-case sit next to actuals and open pipeline, with coverage ratios by team and product.

History that holds up — because everything is effective-dated, you can rerun any past quarter exactly as it was.

Instant onboarding — a rep hired today is in the model today. No waiting for someone to remember to add them.

For the data team

Beautiful data, by default

The same model that gives revenue leaders a forecast they trust gives data teams something rarer: clean, documented, conformed tables in the warehouse — not a tangle of CRM exports and quota spreadsheets to reverse-engineer every quarter.

See it on your own data

We can stand this up on your systems and show you your entire revenue org as a single model — usually faster than you'd expect.