Guidelines from the Monad Foundation Quant team to help design effective campaigns and avoid common pitfalls.

Part 1: Proposal Design Considerations

Monad Momentum's goal is to facilitate your growth. Everything else is downstream from that principle.

You will trivially succeed at increasing usage in the presence of incentives, and it's tempting to think of it as a success metric in itself. It's not. Your goal is growth that will be persistent in the absence of incentives. This growth is more difficult to measure than just monitoring the raw user numbers.

This document will provide guidelines that might be helpful to finding non-incentivized growth. Guidelines are not rules however. And if a guideline contradicts your common sense, err on the side of common sense.

1. Specificity

There is a core, polished, differentiated, repeatable action that defines your application. The incentives should typically apply to only that core action which will help form a persistent habit.

Incentives may also be effective in bootstrapping initial in-app liquidity that's difficult to attract early on, but likely to become self-sustaining.

2. Adversarial Mindedness

All incentives bear very high risk of being abused, especially if the effort or cost is strictly rewarded.

Expected value is the difference between the incentives gained by taking an action, and the cost of taking said action: EV = incentives(action) - cost(action)

• If your design allows it, farmers—either bots or humans—will drain all incentives reserves by automating and/or scaling any zero-cost action with a positive EV (even if nominal).
• If your design allows it, mercenary capital will dominate even non-zero cost action for attractive risk-adjusted returns and disappear completely once incentives are gone. So long as the action yields positive EV, however nominal, expect value extractors.

To that extent, the cost of the incentivized action should be at or greater than the incentives gained: cost(action) ≥ incentives(action)

Cost is mentioned in a broad sense: fees, risk, time investment, opportunity, etc. You can be more liberal with this factor if there is a costly barrier of entry to qualify for incentives in the first place (e.g. X Premium or holding a particular NFT).

Note: There is also a Specificity upside in the barrier-of-entry approach, at the expense of limiting reach.

3. Ex-Post Distribution

It is strongly advised to distribute rewards after actions are completed (ex-post). This means users perform actions first without immediate incentives settlement.

At a later time, usage data is reviewed and incentives are distributed. Distributions should happen on a regular cadence (daily / weekly etc). This allows for the discovery and quick remediation of design mistakes, and to exclude obvious bad actors. In defending a worst case scenario, the ex-post approach can prevent a full depletion of an incentives budget by filtering out bots.

You should clearly communicate in the UI what is being incentivized. But the more freedom you maintain on the actual distribution, the better.