What Is OTE in Sales? Base, Variable, and How Pay Mix Bends the Forecast

What Does OTE Actually Measure?

OTE, or on-target earnings, measures what a salesperson takes home in a year when they close exactly 100 percent of quota: base salary plus variable pay at target. A rep with a $120,000 base and $120,000 of variable at target carries a $240,000 OTE. Close the full quota and the rep earns all of it. Fall short and the base is the only part that holds.

We build forecast models for B2B SaaS teams, and I read comp plans before I read pipeline. The split inside that OTE decides how a rep works a deal, and how a rep works a deal decides what your CRM says. Pay mix is a forecasting input that most RevOps teams file under HR.

How Do Base and Variable Split Inside OTE?

The split has a name, pay mix, and it tracks how much control a role has over whether a deal closes. Write it base over variable. A 50/50 mix means half the OTE is salary and half rides on performance. The more directly a person can close revenue, the more of their pay the company is willing to put at risk.

The pay mix a company picks is a statement about leverage, and it clusters by role.

None of these are laws. They are the market's read on how much a role bends the result. When a company runs an account executive at 80/20, it has quietly decided the rep does not really control the close, whatever the title says.

Why Does Pay Mix Change How Reps Sell?

A heavier variable share turns every quota threshold into a timing decision, and timing is where forecasts break. The mechanics that sit on top of pay mix are what create the behavior. An accelerator raises the commission rate above 100 percent attainment, so a dollar closed at 110 percent pays more than a dollar closed at 90 percent. Below a floor, a decelerator does the reverse. Some plans also cap the payout at a ceiling. A rep reads all of it and works the calendar around the thresholds.

Watch what that produces near the end of a period. A rep sitting at 130 percent under a capped plan has no reason to close the next deal this quarter, so it gets parked for the next one. Another at 95 percent with a steep accelerator just past quota pulls every reachable deal into this period, discount included, to clear the line. And a rep who has already missed pushes slow deals out to seed next quarter. The pipeline did not move because the market moved. It moved because the plan told three reps to move three deals.

This is one reason the calendar compresses. Our data shows the third month of a quarter closes stronger than the first two, and quarter-heavy comp plans are part of why. The plan rewards a landing date, so reps produce one.

How Does OTE Design Bend the Forecast?

The most reliable slippage signal we track is a rep changing a deal's close date, and comp design is one of the biggest reasons that date moves. At ORM, when a deal slips from one quarter to the next it is less likely to close at all, even when it still sits in commit. Pay mix and accelerator timing manufacture those slips. A capped rep pushing deals forward and an under-quota rep pushing deals out both write the same event into the CRM: a changed close date on a deal nobody killed.

That connects to the forecasting mistake I see most. Teams treat pipeline coverage as the forecast. They see 4x coverage and feel safe. But coverage says nothing about why the close dates look the way they do, and a comp plan shapes those dates far more than buyer intent can. A better forecast decomposes the quarter into carry-over deals already in pipeline on day one, deals created and closed inside the quarter, and deals pulled forward from later periods. Aggressive pay mix inflates that third bucket, and pulled-forward deals arrive discounted, so they close for less than the CRM claimed.

The pattern under every row is the gap between the value in the CRM and the value that lands. We regularly see an average open-deal size of $80,000 collapse to a $40,000 average at closed-won, and comp-driven discounting is one of the forces that opens that gap.

What Happens to the Forecast When You Change the Plan?

Reprice the plan and you reprice behavior, which means the pipeline history your forecast trained on stops describing the future. Forecasts miss most often because an assumption changed and the model kept running on the old one. A new pay mix is that kind of change. Move a team from 60/40 to 50/50, add a cap, or shift quota timing, and the close-date behavior baked into last year's data stops predicting this year's.

Territory changes do the same thing from another angle. Redraw territories and reps get distracted, so execution dips even while coverage looks fine. A forecast that cannot see the comp plan reads the resulting slippage as a market signal and adjusts for the wrong cause.

The fix is to treat quota attainment and comp design as inputs the model can see, not context stranded in a spreadsheet nobody feeds the forecast. When the plan changes, the forecast should expect the behavior change and reconcile against it, the same way we reconcile a retention waterfall in gross versus net retention. OTE is not payroll trivia. It is one of the levers that decides what your pipeline will do before the quarter starts, which is the only time the number is still worth knowing.