---
title: KPI Benchmarks, Targets & Payout Curves | Bentega
description: Learn how to turn KPI benchmarks into incentive targets, thresholds and payout curves, with worked examples for KPI-based bonus and variable pay.
image: https://www.bentega.io/hubfs/Setting%20KPI%20benchmarks.png
---

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 Jun 16, 2025

# How to set KPI targets, thresholds and payout curves for incentives

[Andreas S](https://www.bentega.io/blog/author/andreas-s)

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A KPI benchmark and an incentive target are not the same thing.

A benchmark tells you something about performance in the past, across a peer group or against another reference point. A target defines the result a participant is expected to achieve. Once that KPI affects variable pay, the plan also needs to define what happens below target, above target and at the boundaries between them.

That means a KPI-based incentive usually needs more than one number.

You may need a **benchmark, target, threshold, payout curve, maximum performance level, cap or gate**, depending on how the plan is designed.

The important part is that each element has a clear job.

For the broader question of which metrics should be used for variable pay, start with the [KPI-based incentives guide](https://www.bentega.io/kpis-and-metrics). This article focuses specifically on what happens after the KPI has been selected.

 

![Setting KPI benchmarks](https://www.bentega.io/hs-fs/hubfs/Setting%20KPI%20benchmarks.png?width=2240&height=1260&name=Setting%20KPI%20benchmarks.png)

## Benchmark, target, threshold and payout curve: what is the difference?

These terms are often mixed together even though they answer different questions.

| Term | What it means | Role in an incentive plan |
| --- | --- | --- |
| Benchmark | A reference point used to understand performance | Helps inform target setting |
| Target | The performance level expected for the period | Often corresponds to target variable pay |
| Threshold | The minimum result required before payout begins or changes | Defines the lower boundary of the payout model |
| Payout curve | The relationship between KPI performance and payout | Determines how results between defined points are rewarded |
| Maximum performance point | The KPI result at which the highest defined payout is reached | Defines the upper performance boundary |
| Payout cap | The maximum variable-pay amount or payout factor | Limits the final payout |
| Gate | A separate condition that must be satisfied for some or all payout to apply | Can reduce or block an otherwise calculated payout |

A benchmark may influence the target, but **the benchmark should not automatically become the target**.

The same applies to thresholds. A threshold is a plan-design decision, not simply an industry average with a different label.

## Start with the KPI definition

Before setting any target, make sure the KPI itself is defined well enough to calculate.

For example, “customer retention” is not yet a complete incentive metric.

You still need to define:

- which customers are included;
- when the measurement period begins and ends;
- whether new customers enter the population;
- how contractions are treated;
- how cancellations are dated;
- which source data determines the result;
- who owns the metric;
- how changes in the underlying data are handled.

The same applies to revenue, gross margin, pipeline, customer health, project delivery and other KPIs.

A precise target applied to an imprecise metric does not make the incentive plan more precise.

## Use benchmarks as context

Benchmarks can come from several places.

An **internal benchmark** might be last year's result, the average from previous quarters or the performance of comparable teams.

A **business-plan benchmark** might come from the budget, operating plan or another forward-looking company objective.

An **external benchmark** might come from industry research or comparable businesses.

Each can provide context, but they answer different questions.

Historical performance tells you what the organization has achieved before.

The business plan tells you what the company needs or expects going forward.

External data tells you how a result compares with another population.

None of those automatically determines what an employee should be paid for achieving.

That decision requires another layer: **what result should represent target performance for this role under this plan?**

## Set the target from the business objective and the role

Suppose a Customer Success team achieved 92% retention last year. That gives you historical context.

It does not tell you whether this year's target should be 92%, 95% or another number.

The target should also reflect what has changed.

- Has the customer mix changed?
- Has pricing changed?
- Has the product improved?
- Has responsibility moved between Sales and Customer Success?
- Has the company changed its retention assumptions in the annual plan?
- Is the participant actually responsible for the customer population being measured?

The objective is to choose a target that represents **the performance expected from the role during the defined period**, rather than copying last year's result or an external benchmark.

If compensation is attached to the KPI, controllability matters as well.

An employee should understand what result is expected and have a meaningful ability to influence it.

## Decide what target performance should pay

Once the target is defined, decide what it means for compensation.

Suppose:

**Annual target bonus:** €10,000  
**Retention target:** 95%

A simple arrangement might state that achieving the 95% target earns 100% of the target [bonus](https://www.bentega.io/bonus):

**€10,000 × 100% payout factor = €10,000**

But that still leaves several questions unanswered.

- What happens at 94%?
- What happens at 90%?
- Does 96% earn more than target?
- What happens at 100%?
- Does payout continue increasing indefinitely?

Those questions are answered by the threshold and payout curve.

## Set a threshold deliberately

A threshold defines a lower point in the incentive model.

For example:

**Below 90% retention:** no payout  
**90% retention:** 50% of target bonus  
**95% retention:** 100% of target bonus

This structure says that some payout begins at 90% and reaches target payout at 95%.

The threshold should have a reason.

It might represent the minimum level of performance the company considers rewardable. It might reflect the economics of the plan. It might distinguish acceptable performance from performance that should not create an incentive payment.

What it should not be is an arbitrary percentage added because the plan “needs a threshold.”

## Define the payout curve between threshold and target

The payout curve determines what happens between defined performance points.

Suppose the plan uses this illustrative structure:

| Retention result | Payout factor | Bonus payout |
| --- | --- | --- |
| Below 90% | 0% | €0 |
| 90% | 50% | €5,000 |
| 95% | 100% | €10,000 |
| 100% | 150% | €15,000 |

These numbers are **illustrative plan assumptions, not retention benchmarks or recommendations**.

The plan might use straight-line interpolation between each point.

If retention is 93%, the result sits three percentage points above the 90% threshold across a five-percentage-point range from 90% to 95%.

The payout factor would be:

**50% + (3 ÷ 5 × 50%) = 80%**

With a €10,000 target bonus:

**€10,000 × 80% = €8,000**

At 97% retention, using the same approach between 95% and 100%:

**100% + (2 ÷ 5 × 50%) = 120%**

The payout would therefore be:

**€10,000 × 120% = €12,000**

Now the participant can see exactly how KPI performance translates into variable pay.

## Attainment and payout are not always the same percentage

This distinction is easy to miss.

An employee might achieve 105% of a KPI target without receiving 105% of the target bonus.

The payout curve may be deliberately different.

For example:

**KPI attainment:** 105%  
**Payout factor:** 120%

Or:

**KPI attainment:** 90%  
**Payout factor:** 50%

The plan therefore needs to distinguish between:

**KPI achievement**  
How actual performance compares with the target.

and

**Payout factor**  
How the plan converts that performance into variable pay.

In a simple proportional plan, the two can be identical.

In a plan with thresholds, accelerators, decelerators or other curves, they are not.

## Be careful with KPIs where lower is better

Not every KPI improves when the number increases.

For revenue, margin or retention, higher performance may generally represent stronger achievement.

For metrics such as error rate, churn, response time or cost, a lower number may represent better performance.

That means a generic formula such as:

**Actual result ÷ target**

cannot be applied blindly across every KPI.

The plan needs to define:

- which direction represents improvement;
- how achievement is calculated;
- what happens when performance is better than target;
- what happens when the denominator is zero or otherwise unsuitable;
- how rounding works.

The employee should not have to infer the direction of the calculation from the KPI name.

## Decide what happens above target

If the incentive is intended to reward overperformance, define that explicitly.

There are several possible structures.

### Proportional upside

Payout continues increasing at the same rate above target.

### Accelerator

The payout rate increases once a defined performance point is reached.

### Maximum payout level

The curve continues upward until a defined maximum performance result.

### Cap

The employee can continue outperforming the KPI, but incentive payout stops increasing after the defined cap.

### No upside above target

The plan pays 100% of the target bonus once the KPI target is achieved and does not increase further.

None of these is universally correct.

The appropriate structure depends on the purpose of the incentive, the role and the economics the company is willing to support.

The important part is to model the outcome before the plan begins.

## Model several performance scenarios before launch

Looking only at target performance can hide the most important consequences of a payout curve.

Run the plan through several scenarios.

For example:

- clearly below threshold;
- exactly at threshold;
- between threshold and target;
- exactly at target;
- moderately above target;
- at maximum payout;
- beyond the maximum.

Then calculate the resulting variable pay.

This makes it easier to spot a curve that behaves strangely.

You may discover that a tiny improvement creates a very large payout jump.

Or that performance just below target receives almost nothing while performance just above target receives far more.

Or that strong overperformance creates a payout exposure the company did not intend.

Scenario modelling should happen before participants begin performing against the plan.

## Avoid cliffs unless they are intentional

A cliff occurs when a small change in performance produces a large change in payout.

Suppose:

**94.9% performance = €5,000**

but:

**95.0% performance = €10,000**

That may be intentional.

But if it is not, the design can create disproportionate attention around one measurement point and make source-data disputes more consequential.

A smoother payout curve can reduce those jumps.

In other cases, a hard gate is exactly what the company wants.

For example, a company-level profitability condition might deliberately block a bonus component unless a minimum result is achieved.

The point is to know whether the cliff is part of the design rather than discovering it during payout review.

## Use gates for separate conditions

A gate is different from a threshold.

A threshold normally belongs to the KPI being rewarded.

A gate introduces another condition.

For example:

**Individual KPI payout before gate:** €10,000  
**Company gate:** 100%  
**Final payout:** €10,000

If the company gate instead reduces the payout to 50%:

**€10,000 × 50% = €5,000**

Or a plan may specify that no payout occurs if the gate is not met.

If a gate is used, employees should understand:

- which metric controls the gate;
- when it is measured;
- whether it affects the entire bonus or only one component;
- whether it scales payout or works as an on/off condition.

The [**bonus guide**](https://www.bentega.io/bonus) covers weighted bonus plans, gates and broader bonus-plan design in more detail.

## Multiple KPIs need their own targets and rules

A plan may include several KPIs.

For example:

- Revenue: 40%
- Customer retention: 30%
- Operational quality: 30%

Each metric may need its own:

- definition;
- target;
- threshold;
- payout curve;
- maximum;
- source data;
- calculation logic.

The weighted result can then be combined according to the plan rules. A 40% weighting does not mean that the revenue target itself should be 40%.

It means the result from that KPI contributes 40% of the weighted incentive calculation.

Keeping the **metric calculation**, **achievement calculation**, **payout curve** and **weighting** separate makes multi-KPI plans much easier to explain.

## Do not change targets casually during the performance period

Targets sometimes need to change.

A territory may be reassigned. A role may change. The business may make a significant acquisition. A product launch may be postponed. A customer portfolio may move between employees.

But changing an incentive target after performance has already begun creates a different governance question from setting the target before the period.

If a change is necessary, document:

- what changed;
- why the original assumption no longer applies;
- which participants are affected;
- the effective date;
- whether previous performance remains under the old target;
- who approved the change;
- how it was communicated.

Avoid silently changing historical targets so the final calculation appears as though the new target had always applied.

## What should be documented for every KPI-based incentive?

For each KPI, record:

- KPI definition;
- participant or team;
- performance period;
- source data;
- calculation method;
- target;
- threshold;
- payout at threshold;
- payout at target;
- above-target treatment;
- maximum performance point;
- payout cap, if any;
- gate, if any;
- weighting, if applicable;
- rounding rules;
- review owner;
- approval process;
- effective dates;
- exception handling;
- payout timing.

If the plan cannot explain those elements clearly, the payout cycle is likely to depend on interpretation later.

## How Bentega manages KPI-based incentive logic

Bentega supports KPI-based payout logic as part of a broader [incentive compensation](https://www.bentega.io/incentive-compensation) workflow, including thresholds, automated calculations, approval workflows, employee and manager visibility, and calculation history.

Depending on the incentive model, the KPI itself can be calculated in Bentega from underlying performance inputs before the result is used in the variable-pay calculation.

That means the workflow can distinguish between:

**the underlying performance inputs → the calculated KPI result → KPI achievement → payout logic → review and approval**

Rather than treating the final bonus amount as a standalone number, the calculation can remain connected to the rules and performance information behind it.

This becomes particularly important when plans include several KPI components, thresholds or other conditional logic.

[Explore Bentega](https://www.bentega.io/product) →

## Frequently asked questions

### What is a KPI benchmark?

A KPI benchmark is a reference point used to put performance in context.

It might come from historical company performance, a business plan or external market data.

A benchmark does not automatically determine an incentive target.

### What is a KPI target in an incentive plan?

A KPI target is the defined performance result associated with target achievement.

In many plans, reaching the KPI target corresponds to earning 100% of the target variable-pay amount for that component.

The plan should state this relationship explicitly.

### What is a threshold in a KPI bonus?

A threshold is the minimum defined performance point at which payout begins or changes.

For example, a plan may pay nothing below 80% achievement and begin paying at 80%.

The exact threshold is a plan-design decision.

### What is a payout curve?

A payout curve defines how performance results translate into payout.

It can be proportional, stepped, accelerated, decelerated or built around several defined performance points.

### Should an industry benchmark become the KPI target?

Not automatically.

External benchmarks provide context, but your target should also reflect the role, company strategy, internal performance, resources, customer base and business assumptions.

### Should KPI payout increase above target?

That depends on the incentive design.

Some plans reward overperformance with additional upside. Others cap payout at target or at another defined level.

The company should decide this before the performance period starts and model the resulting cost.

### Can a KPI have both a threshold and a gate?

Yes.

A threshold normally defines the minimum performance level for the KPI itself.

A gate can introduce a separate condition that modifies or blocks the resulting payout.

### What happens if the KPI target changes during the year?

Treat it as a plan change rather than simply overwriting the old target.

Document the reason, affected participants, effective date and treatment of performance before and after the change.

## A benchmark is only the starting point

Choosing a KPI does not finish the incentive design.

And finding an industry benchmark does not finish the target-setting process.

The plan still needs to answer:

**What result represents target performance?**

**At what point does payout begin?**

**How does payout change between threshold and target?**

**What happens above target?**

**Is there a maximum, cap or gate?**

**Can every result be reproduced from defined data and rules?**

Once those decisions are explicit, the KPI becomes more than a number on a dashboard. It becomes a defined part of the variable-pay calculation that employees, managers and Finance can understand before the payout period arrives.

[Read the KPI-based incentives guide](https://www.bentega.io/kpis-and-metrics) →

[KPIs & Metrics](https://www.bentega.io/blog/tag/kpis-metrics)

## Related posts

[![Comp metrics](https://www.bentega.io/hs-fs/hubfs/You%20Get%20What%20You%20Pay%20For%20(2).png?height=200&name=You%20Get%20What%20You%20Pay%20For%20(2).png)](https://www.bentega.io/blog/integrating-kpis-into-compensation-plans-for-better-results)

## [How to integrate KPIs into compensation plans](https://www.bentega.io/blog/integrating-kpis-into-compensation-plans-for-better-results)

[![sales KPIs and incentives](https://www.bentega.io/hs-fs/hubfs/Bloggbanner%20-%20Driving%20sales%20success%20(Bloggbanner).png?height=200&name=Bloggbanner%20-%20Driving%20sales%20success%20(Bloggbanner).png)](https://www.bentega.io/blog/driving-sales-success-harnessing-sales-kpis-and-incentives-for-optimal-performance)

## [Sales KPIs: which metrics should affect compensation?](https://www.bentega.io/blog/driving-sales-success-harnessing-sales-kpis-and-incentives-for-optimal-performance)

[![Variable Pay Structures](https://www.bentega.io/hs-fs/hubfs/Variable%20Pay%20Structures.png?height=200&name=Variable%20Pay%20Structures.png)](https://www.bentega.io/blog/designing-variable-compensation-plans-that-motivate-performance)

## [Variable pay: definition, examples, and plan design](https://www.bentega.io/blog/designing-variable-compensation-plans-that-motivate-performance)

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