KPI uses cases

The following outlines how to design KPI incentive campaigns to more effectively achieve your project goals and objectives. Feel free to contact the team to discuss any of these use cases.

For a closer look at how KPI-based incentivization works and the benefits it brings, check out our in-depth article here. We break down how Metrom simplifies reward structures and optimizes distribution through various KPI use cases.

Quick reference glossary

  • KPI: TVL goal that the project would like to reach.

  • Upper bound: Upper limit value above which no more rewards are distributed.

  • Lower bound: Lower limit value below which no rewards are distributed.

  • Minimum payout: Amount of rewards paid out regardless of whether a KPI is met or not.

Linear incentivization

Scenario: Target KPI of $100k total value locked (TVL), with $10k allocated as rewards.

Linear KPI simulation

Mechanism: Rewards are distributed proportionally based on how much of the KPI is achieved. If the pool reaches 60% of the target ($60k in TVL), then $6k (60% of the reward pool) is distributed to the liquidity providers.

Takeaway: Linear incentivization offers flexibility, allowing LPs to still earn rewards even if the full KPI isn’t met.

Minimum payout

Scenario: Target KPI of $100k total value locked (TVL), with $10k allocated as rewards, and a minimum payout percentage of 80%.

KPI with minimum payout

Mechanism: 80% of the rewards, so $8k, is distributed regardless of the KPI outcome, while the remaining 20% is unlocked only if the target KPI is met. The remaining 20% is unlocked and distributed proportionally with the KPI target being met between 80–100%, and not just if the 100k TVL upper bound is reached. If the pool reaches $90k in TVL, $8k is distributed as the minimum payout, while the full $10k is only unlocked if the TVL reaches $100k.

Takeaway: This structure guarantees a baseline reward, reducing the risk for LPs and ensuring liquidity, even if the target is slightly missed.

Bonus-driven incentives

Scenario: Target KPI of $100k total value locked (TVL), with $10k allocated as rewards, where $10k is the minimum payout and an additional $1k bonus distribution based on the KPI met.

KPI bonus driven simulation

Mechanism: Rewards are distributed proportionally based on KPI achievement, with the bonus activated if the target is exceeded. If the pool reaches $100k+ in TVL, LPs receive the full $10k plus an additional $1k as a bonus.

Takeaway: This structure encourages LPs to push beyond the target, rewarding higher performance with extra incentives.

Lower bound and upper bound

Scenario: Target KPI of $100k total value locked (TVL), with $10k allocated as rewards, and a lower limit set at $20k TVL.

KPI lower bound and upper bound simulation

Mechanism: Rewards are only unlocked if the TVL exceeds the lower bound of $20k. From there, the rewards are distributed linearly based on the KPI achievement. If the pool reaches $60k in TVL, then $6k is distributed, but if the TVL remains below $20k, no rewards are unlocked.

Takeaway: This structure protects projects from over-incentivizing in situations where liquidity levels fall too low to be effective.

Minimum payout with control limits

Scenario: Target KPI of $100k total value locked (TVL), with $10k allocated as rewards, with a minimum payout percentage of 80%, and 20% prorated between $20k and $100k TVL.

KPI minimum payout with control limits simulation

Mechanism: 80% of the reward pool, so $8k, is distributed regardless of KPI outcomes. The remaining 20% is distributed based on the range between $20k and $100k TVL. If the pool reaches $75k in TVL, LPs receive the $8k minimum payout, plus a proportional part of the remaining $2k.

Takeaway: This structure balances baseline rewards with a dynamic incentive that scales with performance.