Key Takeaways
- 1. The payout curve is the engine of your comp plan. It translates attainment into earnings and defines the financial consequence of every percentage point of performance.
- 2. Linear curves are simpler and avoid behavioral cliffs. Stepped curves create stronger differentiation but risk perverse timing incentives at tier boundaries.
- 3. Accelerators above target are the single most important motivational tool in your plan. The gap between 100% and 120% payout should feel meaningful. If it does not, top performers have no reason to push.
- 4. Avoid cliffs: points where a small change in attainment produces a large change in payout. Cliffs create timing manipulation, sandbagging, and deal-pulling behavior.
The payout curve is where the math meets the motivation. OTE sets the total number. Mix splits it between fixed and variable. Measures determine direction. But the payout curve determines the shape: at what point does variable pay start? How does it grow? When does it accelerate? Where (if anywhere) does it stop? The curve is the machine that converts performance into earnings, and its design has more impact on rep behavior than any other plan element.
Most plan designers think of the curve as a table of rates. It is more useful to think of it as a set of behavioral signals. The threshold says "below this, you are not carrying your weight." The target rate says "this is what 'good' earns." The accelerator says "this is what 'great' earns, and we want you to get there." Every bend in the curve sends a message. This chapter teaches you how to design those messages intentionally.
Linear vs stepped curves
Linear curves
In a linear curve, the payout rate is constant within each zone. From threshold to target, every percentage point of attainment earns the same dollar amount. From target to cap (or uncapped), the accelerator rate applies uniformly. Linear curves are simple, predictable, and produce no behavioral cliffs. A rep at 99% earns almost exactly the same as a rep at 100%. There is no incentive to manipulate timing.
The trade-off: linear curves do not create as much "wow" factor at specific milestones. There is no moment where a rep thinks "if I close one more deal, I jump to the next tier." Whether that matters depends on your sales culture. For analytical teams that value predictability, linear is ideal. For competitive cultures that thrive on targets and tiers, it may feel flat.
Stepped curves (tiered)
In a stepped curve, the payout rate changes at defined breakpoints (often 80%, 100%, and 120%). Below 80%, one rate. Between 80-100%, a higher rate. Above 100%, an even higher rate. This creates clear tiers that reps can aim for: "I need 3 more deals to hit the next tier."
The risk: behavioral cliffs. If the rate jumps significantly at 100%, a rep at 98% has a strong incentive to delay a deal until next period when it might push them over the cliff on the fresh attainment count. Or worse, they pull a deal from next period into this one if they are already above the cliff. Stepped curves create timing manipulation opportunities at every tier boundary.
I have seen a stepped curve where the rate doubled at 100% attainment. A rep at 99% earned $62K variable. A rep at 101% earned $75K. A two-percentage-point difference in attainment produced a $13K difference in pay. Every quarter, 3-4 reps were within 5 points of the cliff and started playing timing games. The fix was simple: replace the step with a smooth acceleration. The curve still rewarded overperformance, but the $13K cliff disappeared. Deals flowed normally.
Setting the threshold: where does payout begin?
The threshold (or "floor") is the minimum attainment level at which variable pay starts. Below the threshold, the rep earns zero variable pay. The threshold creates a consequence for underperformance and prevents the plan from paying out on minimal results.
Typical threshold ranges: Transactional/high-velocity roles: 40-60%. Mid-market: 60-80%. Enterprise: 70-85%. Startups and new teams: sometimes no threshold at all.
There are two approaches to what happens once the threshold is crossed. In retroactive models, once the rep passes the threshold, they earn payout from 0% attainment upward. Crossing the threshold "unlocks" the entire range. In cumulative models, payout begins at the threshold point and accumulates from there. The retroactive model is simpler to explain but can create a different kind of cliff at the threshold itself.
The motivational window is the attainment range where performance has a meaningful impact on earnings. Below the threshold: zero payout (no motivation to improve). Above the cap: maximum payout (no motivation to sell more). The motivational window is everything in between. If your threshold is 80% and your cap is 120%, the motivational window is only 40 percentage points wide. If 70% of your reps fall within this window, the plan is working. If only 30% do, most of your team is either earning nothing (demotivating) or capped (also demotivating).
Accelerators: the upside engine
Accelerators are higher payout rates that apply above a certain attainment level, typically 100%. They are the single most important motivational tool in your plan because they determine the financial reward for outperformance. Without accelerators, the difference between 100% and 130% attainment is only 30% more variable pay. With a 2x accelerator, the difference is 60% more. That gap is what makes a rep close one more deal before quarter-end.
Typical accelerator ranges: Moderate: 1.25-1.5x the base rate. Aggressive: 1.5-2.0x. Very aggressive: 2.0-3.0x. Enterprise roles with fewer, larger deals tend to have steeper accelerators because each incremental deal has a larger impact.
Here is the math. An AE with $80K target variable and a 1.5x accelerator above 100%:
At 100% attainment: earns $80K variable. At 110%: earns $80K + (10% x $80K x 1.5) = $92K. At 120%: earns $80K + (20% x $80K x 1.5) = $104K. At 130%: earns $80K + (30% x $80K x 1.5) = $116K. The jump from 100% to 130% produces $36K in additional earnings. That is meaningful money. A rep can feel it.
Compare with no accelerator (1.0x): 130% attainment earns $104K. The overperformance premium is only $24K. The accelerator adds $12K of incremental motivation for the same performance. That $12K is the cost of funding your top performers' drive to outperform. It is almost always worth it.
An enterprise AE hit 99% of her quarterly quota. Because the accelerator kicked in at 100%, she earned the base rate on her variable. The rep in the next territory, with a slightly easier book, hit 101% and earned the accelerated rate. The 2-percentage-point difference produced a $4,500 payout gap for the quarter. The 99% rep felt cheated and started questioning quota fairness. The fix: a gradual acceleration that starts ramping at 90% instead of a hard jump at 100%. The cliff disappears, and the curve still rewards overperformance generously.
Decelerators: the downside conversation
Decelerators apply below the threshold (or below target, depending on design). They reduce the payout rate for underperformance. A 0.5x decelerator below 80% means every percentage point of attainment in that zone earns half the target rate.
Decelerators are less common than accelerators and more politically sensitive. They signal "we expect a minimum level of performance, and falling below it has a financial consequence beyond just earning less." Some companies prefer zero payout below threshold (a binary decelerator). Others prefer a reduced rate that acknowledges some effort was made.
When presenting the payout curve to your team, lead with the accelerator, not the decelerator. "Here is how much more you earn above target" is a positive, motivational message. "Here is what happens if you underperform" is a defensive, threatening message. Both are part of the plan, but the order and emphasis in communication shape how reps perceive the plan's intent. Show them the upside first.
The accelerator is the most expensive component of your comp plan in a bull scenario. Model the total cost at 110%, 120%, and 130% average team attainment. If a 2x accelerator at 130% team attainment blows your budget, consider a tiered accelerator: 1.5x from 100-120%, then 2x above 120%. This concentrates the premium on true outlier performance while keeping costs manageable at moderately above-target performance.
See how your curve compares
Upload your comp data to SalesComp Edge and see your actual payout distribution against the curve you designed. Many plans look good on paper but produce unexpected results in practice.
Try SalesComp Edge (free) Build your curveAvoiding behavioral cliffs
Cliffs are the single most common payout curve design problem. They occur wherever a small change in attainment produces a disproportionately large change in payout. Common cliff locations include the threshold (zero to non-zero), the target (base rate to accelerated rate), and tier boundaries in stepped curves.
Three techniques to eliminate cliffs:
1. Smooth transitions. Instead of a hard jump from 1.0x to 1.5x at 100%, ramp the rate gradually from 90% to 110%. At 90%, the rate is 1.0x. At 100%, it is 1.25x. At 110%, it is 1.5x. No single point creates a dramatic jump.
2. Retroactive application. When the threshold is crossed, apply the payout from 0% upward rather than from the threshold point. This eliminates the cliff at the threshold itself because crossing it does not create a sudden windfall.
3. Eliminate steps entirely. Use a continuous mathematical function (linear or polynomial) rather than a stepped table. The formula produces a smooth curve with no discontinuities. This is computationally more complex but eliminates all cliff risk.
The easiest way to test for cliffs in your plan: calculate the payout at every 1% increment from 0% to 150% attainment. Then look for any two adjacent points where the dollar difference is more than 2x the average increment. If it exists, you have a cliff. Reps will find it, and they will game it. The Commission Modeler above does this visualization automatically.
🤖 Try This Prompt
You are a sales compensation designer helping me build a payout curve. Here are my plan parameters: Target variable pay: [Amount, e.g., $80,000] Current threshold: [e.g., 70% attainment] Current accelerator: [e.g., 1.5x above 100%] Cap (if any): [e.g., 200% of target variable] Curve type: [Linear / Stepped / Not sure] Average team attainment: [e.g., 95%] Attainment distribution: [e.g., "most reps between 80-120%"] Please: 1. Calculate the payout at 50%, 70%, 80%, 90%, 100%, 110%, 120%, 130%, 150% attainment 2. Identify any behavioral cliffs (points where a 1-2% change in attainment creates a disproportionate payout change) 3. Calculate the motivational window (the attainment range where most of my team has meaningful incentive to improve) 4. Recommend specific adjustments to eliminate cliffs and widen the motivational window 5. Model the total cost at 80%, 100%, and 120% average team attainment
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Common Practitioner Questions
Linear for simplicity and cliff avoidance. Stepped when your sales culture thrives on clear milestones and you have the operational maturity to handle the timing incentives steps create. If in doubt, default to linear. You can always add steps later if the team wants more defined tiers. Removing steps (simplifying) is politically easier than adding complexity.
1.5x is the market standard for most mid-market AE roles. Enterprise roles with fewer, larger deals benefit from steeper accelerators (2-3x) because each incremental deal represents significant revenue. Transactional roles with many small deals can use more moderate accelerators (1.25-1.5x) because the volume naturally smooths attainment. The test: if your top performer at 130% does not earn meaningfully more than your median performer at 100%, your accelerator is too flat.
Not necessarily. Starting the accelerator at exactly 100% creates a cliff at the most psychologically significant point in the plan. Consider starting a mild acceleration at 90% (1.1-1.2x) and ramping to full acceleration by 110-120%. This smooth ramp eliminates the cliff at target while still rewarding overperformance generously. The rep feels the acceleration building rather than hitting a sudden gear change.
For the first two quarters, consider no threshold at all. You do not yet know what realistic attainment looks like with your product, market, and team. Setting a threshold based on assumptions penalizes reps for something outside their control (ramp time, product maturity). After two quarters of data, set the threshold at the 10th-15th percentile of observed attainment. This ensures only true underperformers fall below it.
Yes, and this is a sophisticated approach used by many mature organizations. Example: 1.0x from threshold to 100%, 1.5x from 100% to 120%, 2.0x above 120%. This creates an increasing reward curve that gets steeper as performance gets more exceptional. It also naturally contains cost because the 2x rate only applies to a small number of top performers. The operational trade-off is slightly more complex calculation logic.