Great to see community discussion to align objectives, thanks for posting and setting up the approach Getty! The questions you pose are all important to ensuring funded programs are structured properly. We faced similar challenges and decisions for the ARB LM program that we are currently working on with the DAO, and we have found valuable insights that could benefit this initiative.
As we understand it and similar to above community sentiments, three key questions to think about when considering leveraging liquidity mining for this purpose are:
- Which Optimization Metrics should the DAO focus on? :
- Should the DAO’s focus be on capturing market share, increasing volume, or enhancing LP revenue?
- Which Chains or Ecosystems should the DAO target? :
- What makes a chain a more or less promising candidate? How should these “scores” of suitability affect their corresponding budgets? We need criteria to identify suitable chains for liquidity mining initiatives.
- It is valuable to see Wintermute’s comment around TVL and market share ranking to inform this decision.
- How should the Selection of Pools for Incentivization be decided? :
- How should rewards be allocated within chain deployments among the selection of pools? Strategically, it’s wise to incentivize “blue-chip” pools, as they can be considered to have a higher likelihood of sustainability over time, but what about native token pools to the chains selected for deployment? Blue chip pools typically require more substantial incentive allocations for meaningful and sustained growth, as they have more competition and a naturally higher liquidity depth.
From our experience, without alignment on definitions of success, due diligence on the environment where funds are deployed, and constant monitoring and optimization of the rewards allocations, liquidity mining programs can incur significant decreases in spend efficiency. Blue chip pools have higher variations in elasticity to rewards, requiring special attention and data insights per deployment. Is the community willing to spend more on these pools to capture market share? This could also be included in the vote.
Gauntlet’s Findings
In our latest liquidity mining work on Uniswap Arbitrum, we found that liquidity incentives are especially useful in bootstrapping liquidity and/or reviving pools with previously little to no activity, whereas large, blue-chip pools require more incentive capital to order for meaningful effects on market share, volume and LP revenue to be observed. Liquidity mining seems more effective on chains where Uniswap is still gaining a foothold, as shown by the stronger results on Arbitrum compared to Ethereum. This insight is particularly relevant to your plan of expanding Uniswap on emerging chains.
It’s important to strategically distribute these incentives. The goal should be to enhance the baseline activity of a pool sustainably, rather than merely creating a temporary spike in market share that dissipates once the incentives are withdrawn. The key is to ensure that improvements in price execution (as a result of increased liquidity) are maintained even after the removal of these incentives, thereby supporting a lasting increase in market share as more traders will be drawn to the destination with the best price execution.
We’ve detailed the performance of our liquidity mining program on Arbitrum in our midpoint retro report, which will be published on Monday. This report also includes insights on our methodology for future pool selection and other strategic considerations. For those interested in learning more on the key findings and how it relates to optimal allocation decisions, we will post it to the forums and follow up on this thread. For this current ARB program, it is too early to confidently assert the lasting impact (‘stickiness’) of the incentives, however, once these rewards are diminished or ceased, we are eager to share these findings with the community.
Incentive Budgets and Ongoing Optimization
When it comes to allocating the budget for incentives, it’s crucial to base our decisions on the projected ROI (with respect to the primary objective function of this initiative). If the DAO agrees to extend rewards across various emerging chains, we should thoughtfully consider how to distribute the budget. For instance, should we allocate $300K for a Base rewards program and $200K for Binance Smart Chain? The key factors driving these decisions should include potential growth, chain-specific dynamics, and community engagement levels. Furthermore, what is the community’s approach to ongoing optimization efforts? We have observed that incentivized pools respond in a variety of ways, and require detailed monitoring to institute possible pivots in funding.
All to say there’s a trade off between speed via standards and efficacy enabled by optimization. We are keen to hear community feedback on the above thoughts and questions!