In the long evolution of the cryptocurrency industry, economic models built on decentralized consensus have offered countless users a glimpse of the “Holy Grail” of crypto. However, as the industry advances, project teams are increasingly focused on balancing long-term protocol development with user retention amidst the fluctuating tides of the crypto market. Points-based incentive models, seen as a relatively “neutral” approach between news-driven and token-based rewards, have been adopted by an increasing number of projects. Many believe that the attention generated through point-based incentives can create organic growth points for protocol metrics, driving project growth in a sustainable way.

Yet, recent developments, such as the TGE allocations of projects like Blast, have triggered a wave of public outrage, particularly around dissatisfaction with extended reward periods that result in low returns. Some prominent investors have criticized these airdrops as manipulative strategies, designed to keep participants engaged with promises of rewards that ultimately fall short. This article aims to examine the pros and cons of points-based incentive models from various angles and seeks to identify potential solutions.

Early Incentive Models

In the earliest wave of the crypto boom, during the height of the Ethereum ICO frenzy, airdrops were relatively straightforward and direct. Simply providing a 0x address could result in receiving a considerable amount of tokens. Since projects during the ICO era were largely centered on speculative concepts, with minimal on-chain interactions, the simple act of holding a wallet address could serve as an incentive criterion for everyone.

As the DeFi Summer began, projects like Balancer and Compound adopted liquidity mining as a way to incentivize users. At the time, it was clear that the growth of DeFi protocols depended heavily on the scale of on-chain liquidity. Given the urgency of attracting liquidity in the market, these projects used direct token incentives. Although this approach significantly boosted Total Value Locked (TVL), it also led to the issue of “farm-and-dump,” where users would quickly sell off their rewards.

Then came Uniswap’s airdrop, which made a huge splash and truly introduced the paradigm of interactive airdrops into the crypto space, giving rise to a new group of “airdrop hunters.” Many DeFi projects followed suit, and as various Layer 2 (L2) solutions and public chains reached technical maturity, the focus shifted to building governance models within these ecosystems. Since the governance of many protocols is intrinsically tied to their tokenomics, this naturally led participants to anticipate airdrops. Thus, incentive models centered around tokens and user interactions began to be integrated into the broader crypto economy.

To summarize, the key characteristics of early incentive models in the crypto space were:

1. Direct Token Incentives: Early projects enjoyed a less saturated competitive environment, which provided ample room for growth. They could achieve scale while sharing value with users through token incentives.
2. Low Interaction Barriers: Given the nascent state of on-chain ecosystems at the time, protocols had relatively simple product models, making the interaction process straightforward for users.
3. Instant Rewards (Synchronous): Prior to Uniswap, many projects used liquidity mining to provide users with immediate token rewards for their deposits—rewards were earned as soon as actions were performed.

The Origins of Points-Based Incentives

Before the rise of points-based incentives, as the crypto ecosystem flourished, projects faced a dilemma between retaining users and offering effective incentives. Platforms like Galxe and similar task-based platforms provided a potential solution. These platforms allowed projects to spread out the incentive process over specific user interactions, offering rewards in the form of NFTs rather than directly distributing tokens. This approach introduced a degree of incentive delay, as there was a longer period between user interactions and the actual distribution of token rewards. Points-based incentives, like task platforms, emerged as one of the ways to refine user engagement within the crypto space.

One of the first projects to widely adopt a points-based model was Blur. Pacman, the founder, innovatively used points to calculate incentives for NFT trading, and these measures significantly boosted Blur’s protocol growth, particularly in terms of liquidity and trading volume. Analyzing the data in Figure 1 on Blur’s growth, we can see that points served three primary functions:

1. Boosting Confidence: Through points-based incentives, users could gain a sense of potential rewards early on, increasing their confidence in future airdrops and positively impacting the initial token price.
2. Extending the Reward Cycle: Points can help manage users’ expectations of future airdrops, effectively extending the overall reward cycle. A clear example is Blur, which continued to offer points incentives even after launching its token, reducing sell pressure while providing users with a sustainable incentive environment, as reflected in sustained trading volume and TVL.
3. Tangible Value: Compared to NFTs awarded after completing interactive tasks, points give users a sense of having a claim to future tokens, rather than just earning symbolic badges. This sense of value is evident in the correlation between early mining activities, trading volume, and token prices.

Figure 1: Data on Blur (DefiLlama)

Based on these functions, several advantages of points-based incentives emerge:

1. Improving Retention Rates: Under the previous “farm-and-dump” conditions, users often displayed low loyalty to protocols. Points-based incentives can guide users to generate continuous cash flows and on-chain interactions.
2. Reducing Token Costs: Points-based incentives can lower the costs of token market-making and operational expenses for projects, and sometimes even reduce compliance risks.
3. Greater Flexibility: The organic adaptability of points-based incentives gives projects more flexibility, as they are not directly affected by token price fluctuations. This allows projects to focus more on product development.

Confidence Created by Points

In the operating cycle of crypto projects that use points as their main incentive model, the cycle can generally be divided into three phases, with two key milestones: the adoption of points-based incentives and the TGE (Token Generation Event). Figure 2 illustrates the changes in user confidence throughout the project’s lifecycle.

Figure 2: Changes in User Confidence Throughout the Project Lifecycle

Before the introduction of points-based incentives, overall confidence tends to grow linearly, as users are generally optimistic about the project’s potential during its early stages, often buoyed by positive news. Once points-based incentives are introduced, there is a temporary boost in user confidence due to the sense of reward that points provide. However, as the incentive period progresses, users’ expectations for a potential airdrop become more evenly spread out over time, and the market begins to price in the value of these incentives externally. As a result, overall confidence tends to fall back to levels seen before the points-based incentives were introduced.

After the TGE, users who have experienced the points-based incentive process may see their confidence drop further. This is because the long duration of the points incentive cycle makes it difficult for users to continue bearing the costs associated with the cycle, especially when their post-TGE gains remain uncertain. Many may opt to sell their holdings, leading to increased sell pressure.

In summary, the boost in confidence brought by points is most evident in the initial stages of the points-based incentive period, as it essentially provides users with a way to engage with the project’s ecosystem. However, for long-term user retention, the most critical factor remains the actions of the project team. Points-based incentives, meanwhile, offer the team a wide range of options for managing user expectations.

The Manipulability of Points

Today’s points-based incentive models have fundamentally become tools for project teams to manage user expectations. Because points-based incentives typically have a long duration, users develop a sense of “sunk cost,” which can lead to passive retention. As long as the project team extends the incentive period and maintains a basic level of rewards throughout, they can sustain the project’s key metrics. Over time, the team’s flexibility in how they allocate incentives increases.

When it comes to distribution, the manipulability of points mainly manifests in two aspects: off-chain issuance and the clarity of rules. Unlike token incentives, points-based rewards often remain off-chain, offering project teams greater room for maneuver. In terms of rule clarity, project teams control the distribution of incentives within the protocol. For instance, in Blast’s incentive program, the long duration of the reward cycle allows the team to moderate users’ reactions throughout, minimizing loss of confidence. However, in Blast’s second phase of distribution, they effectively diluted the points of early large-scale depositors, shifting the benefits to those who interacted more on-chain. For large depositors, this redistribution meant that the potential airdrop could not cover the initial capital costs, and it increased the cost of subsequent on-chain interactions. Yet, if they withdrew their deposits, they would face the issue of sunk costs. In the final airdrop distribution, the gradual linear release to large holders showed that the project team had chosen to shift the benefits from large holders to smaller participants.

In terms of market pricing, platforms like Whales Market, which facilitate the trading of points OTC (over-the-counter), provide project teams with a valuable source of data. These platforms enable market-based pricing of points, allowing project teams to make informed adjustments through market makers before the TGE. The low liquidity environment before the TGE also reduces the complexity of market making. However, such trading can also contribute to the premature exhaustion of a project’s perceived value.

Disadvantages of Points-Based Incentives Derived from Manipulability

From the manipulative potential of points, we can identify several drawbacks of points-based incentives:

1. High Manipulability: Whether in terms of distribution or market pricing, project teams have significant leeway to make adjustments and influence outcomes.
2. Expectation Depletion: The long duration of points-based incentives, combined with speculative activity in secondary markets, can wear down users’ expectations for future airdrops.
3. Benefit Dilution: Due to the extended release period of points, the value generated by early participants and later participants is spread out, potentially harming the interests of those who engaged earlier.

How to Maximize Strengths and Minimize Weaknesses

After analyzing the strengths and weaknesses of points-based incentive models, we can explore how to leverage their advantages and mitigate their drawbacks to create a more effective incentive structure in the crypto space.

Distribution Design

In a points-based model, which often has a long incentive cycle, the way points are distributed is crucial for the development of the protocol. Unlike interactions on task platforms, most projects lack transparency in the relationship between interaction metrics and point allocation, creating a “black box” effect where users have no knowledge of how their actions translate into rewards. However, making the rules fully transparent can also be problematic, as it allows automated systems (or “farms”) to exploit these rules, raising the cost of defending against Sybil attacks on the blockchain.

One potential solution is to decentralize the incentive process to control the visibility of rules to users. For example, points could be organically distributed through various protocols within the ecosystem, which would spread out distribution costs and further refine the incentive structure based on users’ on-chain behaviors. This decentralized allocation approach provides project teams with greater flexibility for dynamic adjustments and allows users to maximize their rewards by engaging in multiple ecosystem interactions (often called “composability”).

Balancing Stakeholder Interests

Many protocols face the challenge of balancing TVL (Total Value Locked) and on-chain interaction metrics, and this is reflected in how they weight point allocations. For projects like Blur that focus on trading, or DeFi protocols that prioritize TVL, these metrics can create a flywheel effect that mutually reinforces growth, where points are used to incentivize a single key metric.

However, when this logic is applied to Layer 2 (L2) solutions, the dynamics become more complex. Participants often diverge in their behaviors and needs, and project teams shift their focus from single metrics to diversified growth. This shift demands a more sophisticated points allocation mechanism. For example, Blast’s attempt with “Golden Points” sought to address these complexities, but its effectiveness was hampered by issues in the allocation ratio, leading to suboptimal results. As of now, there are no widely adopted mechanisms that address this challenge directly.

Looking forward, future protocol designs for points-based incentives could consider refining incentives specifically for both interactions and deposits. This would allow the model to better balance multiple aspects of growth, offering tailored incentives that align more closely with the evolving goals of Layer 2 projects and other protocols that require a nuanced approach to user engagement and liquidity.

Demand Space vs. Incentive Space

Today, many projects use points-based incentives with the primary goal of delaying their TGE (Token Generation Event) while maintaining ongoing incentive activities. Unlike traditional use cases for point-based incentives, these projects often fail to provide any inherent utility for the points themselves. This lack of practical application is a key reason why users perceive points as just another form of tokens. To address this gap, projects can develop effective use cases for points. For instance, in cross-chain bridges or on-chain derivatives, points could be used to offset transaction fees. This would allow users to immediately benefit from the utility of the points, encouraging continued protocol use while also creating more space for points allocation. This approach helps reduce inflationary pressures and manages user expectations. However, it is crucial to precisely balance the relationship between user interactions and fee reductions.

Additionally, whether in traditional markets or the crypto space, demand must always exceed incentives, and a significant portion of that demand comes from the protocol itself. For example, many meme-related projects do not offer points-based incentives because they naturally hold an advantage on the demand side, with users deriving value from the protocol beyond direct rewards. Thus, project teams should focus on developing their product model to ensure a strong Product-Market Fit (PMF), where user engagement is driven by genuine value rather than the allure of speculative token rewards.

Consensus-Based Incentives

For users, consensus-based incentives create a clear and transparent environment, allowing them to participate as independent actors in building consensus. For example, project teams can create decentralized environments within their communities, enabling users to engage in open competition with rewards distributed based on results, similar to Proof-of-Work (PoW) mechanisms. Such competition can mitigate the impact of delayed airdrop distributions within the consensus framework and increase user loyalty and retention. However, consensus mechanisms tend to change slowly and offer limited flexibility, making them less suitable for rapidly growing ecosystems.

On-Chain Points

Storing points on-chain differs from directly issuing tokens in that it removes liquidity while adding the benefits of on-chain immutability and composability. Linea’s LXP provides a strong example of this. When every address and point balance can be traced on-chain, the room for manipulation is visibly reduced. Furthermore, smart contracts enhance the composability of these points on-chain, significantly increasing their relevance within the ecosystem. This allows protocols within the ecosystem to adjust incentives based on on-chain metrics, creating a more dynamic and responsive incentive structure.

statement:

1. This article is reproduced from [Foresight News], the copyright belongs to the original author [Pzai], if you have any objection to the reprint, please contact the Gate Learn team, and the team will handle it as soon as possible according to relevant procedures.

2. Disclaimer: The views and opinions expressed in this article represent only the author’s personal views and do not constitute any investment advice.

3. Other language versions of the article are translated by the Gate Learn team and are not mentioned in Gate.io), the translated article may not be reproduced, distributed or plagiarized.