What are the advantages and disadvantages of the "organic growth point" or "top PUA" in the points incentive model?

Author: Pzai, Foresight News

In the long river of development in the cryptocurrency field, the economic model built on decentralized consensus has brought the dawn of the crypto holy grail to countless users. However, as the industry progresses, project teams are beginning to consider how to balance the long-term development of protocols with user retention in the tide of cryptocurrency. Points, as a relatively "moderate" incentive model between news and tokens, are being adopted by more and more project teams. Many viewpoints suggest that the attention aggregation brought by point incentives can form organic growth points for protocol metrics and strongly drive project growth.

Recently, the TGE distribution of projects like Blast has sparked a wave of anger, reflecting dissatisfaction with the low returns brought about by prolonged incentive cycles. Large holders have lamented that similar airdrops have now evolved into "top-tier PUA" for all participants. Therefore, this article explores the advantages and disadvantages of the points model from multiple perspectives and attempts to find corresponding solutions.

Early Incentive Models

In the earliest days of the wave, when Ethereum ICOs were in full swing, airdrops could be described as relatively simple and crude; one only needed to submit a simple 0x address to receive a considerable amount of tokens. Due to the main characteristic of ICO projects being concept speculation, with almost no construction of on-chain interactions, the (holding) address itself could serve as an incentive metric for everyone.

At the beginning of DeFi Summer, both Balancer and Compound adopted liquidity mining as a means of incentive. It is not difficult to see that for DeFi projects at that time, the scale of on-chain liquidity determined the development of the protocol, and given the market situation at the time, the demand for liquidity was also quite urgent, so they all adopted direct token incentives. Although this contributed significantly to the growth of TVL, it also led to the drawbacks of "mine-sell-withdraw."

Subsequently, Uniswap's airdrop stirred up a significant wave, truly bringing the interaction airdrop paradigm into the crypto field and giving rise to a professional group of airdrop hunters. Many DeFi projects followed suit, and with the technological implementation of many L2 and public chains, the construction of governance models for ecosystems was also put on the agenda. Since the governance of many protocols is essentially a subset of their token economy, it inevitably creates expectations for related airdrops among participants. Thus, an incentive model centered on tokens and interactions began to merge into the crypto economy.

In summary, we can summarize the characteristics of early incentive models in the cryptocurrency field:

• Direct token incentives: For early projects, the growth space provided by an unsaturated competitive environment gave them enough freedom, allowing them to benefit users through token incentives while achieving scale growth.
• Low interaction threshold: Since the on-chain ecosystem was not mature at that time, the product models of protocols were relatively simple, making the interaction process very convenient for users.
• Instant rewards (synchronization): Before Uniswap, many projects adopted mining methods to provide users with immediate token rewards for their deposits, achieving a "what you do is what you get" model.

Origin of Point Incentives

Before point incentives, with the flourishing development of ecosystems, project teams faced a dilemma between user retention and incentives. Platforms like Galxe provided a solution; specifically, task platforms allowed projects to spread the incentive process across specific tasks of user interaction and used NFTs instead of tokens for a certain degree of incentive (marking). Overall, this incentive method began to produce asynchronous incentives, meaning the cycle between token incentives and users' actual interactions was extended. Point incentives, like task platforms, are one of the products of refined interactions in the crypto field.

The first widely adopted project using the points model was Blur, which innovatively used points for NFT trading incentive calculations. The related measures significantly contributed to the growth of the Blur protocol, particularly reflected in liquidity and trading volume. Analyzing the scale development of Blur from the data in Figure 1, we can see that points mainly play the following three roles:

• Boosting confidence: Through point incentives, users gain a sense of acquisition in advance, enhancing their confidence in subsequent airdrops and influencing the initial launch of the token price.
• Extending the cycle: Points can spread users' expectations for protocol airdrops, extending the overall incentive cycle. A clear example is that after Blur implemented its token launch, it still maintained the existence of point incentives, creating a sustainable incentive environment for users while reducing selling pressure, reflected in the continuity of trading volume and TVL.
• Tangible value: Compared to NFTs received after completing interaction tasks, points can provide users with a sense of token mapping, making them feel they have already obtained tokens rather than just receiving symbolic badges, as reflected in the correlation between early mining trading volume and token prices.

Figure 1: Relevant Data of Blur (DefiLlama)

Based on the above roles, several advantages of point incentives can be derived:

• Improved retention rate: In the past, under the backdrop of "mine-sell-withdraw," users typically had low loyalty to protocols. However, through point incentives, project teams can guide users to generate continuous cash flow and on-chain interactions.
• Avoiding token costs: Incentives based on points can reduce the costs for project teams in token market-making and corresponding operations, and sometimes even lower compliance risks.
• Higher flexibility: The organic adjustment of point incentives grants project teams greater flexibility, unaffected by the trends of related tokens, allowing more focus on product development.

Confidence Created by Points

In the operational cycle of crypto projects primarily using points as an incentive model, we can roughly divide it into three stages, with two key nodes being the adoption of point incentives and TGE (Token Generation Event). Figure 2 shows the changes in user confidence throughout the project cycle.

Figure 2: Changes in User Confidence Throughout the Project Cycle

Before point incentives, we can see that overall confidence exhibited a linear growth trend because, in the early stages of the project, users typically maintained an optimistic attitude toward the project's development, and there were many favorable news items corresponding to the early stage. After implementing point incentives, compared to the absence of point incentives, the sense of acquisition generated by points led to a temporary boost in confidence. However, the cycle of point incentives began to spread users' expectations for project airdrops, while the market began to price the project's incentives, causing overall confidence to fall back to the level without point incentives. After TGE, users who experienced point incentives would see their confidence levels drop even more because the overall cycle of point incentives was long, leading users to be unable to bear the costs generated by the cycle after TGE, resulting in a choice to sell, reflected in greater selling pressure.

In summary, we can see that the confidence brought by points mainly manifests in the early stages of point incentives, essentially providing users with an opportunity to enter the ecosystem. However, for user retention, the core aspect must be the actions of the project team. Point incentives themselves provide project teams with diverse manipulation space.

Manipulation Space of Points

Today's point incentive model has fundamentally become a tool for project teams to manage expectations. Since point incentives are a long-term process, users will have corresponding sunk costs, which can bring some passive retention to the project based on these sunk costs. Therefore, as long as project teams extend the incentive cycle and maintain basic incentives within the cycle, they can sustain the basic performance of project metrics. Moreover, the distribution space for project teams is gradually increasing beyond basic incentives.

In terms of distribution, the manipulation space of points mainly lies in off-chain and clarity of rules. Compared to token incentives, point incentives typically do not go on-chain, thus providing project teams with greater manipulation space. Regarding rule clarity, project teams control the incentive distribution rights for various parts within the protocol. As seen from Blast's incentives, the long cycle of incentives represents that the strong flexibility of rules can maximize the neutralization of most users' emotional responses within the cycle, reducing confidence loss. However, the distribution in Blast's second phase diluted the deposit points of large holders before the launch and transferred this portion of benefits to on-chain participants. For large holders, such spreading means that airdrops may not cover the capital costs incurred in the early stages, increasing the subsequent on-chain interaction costs. However, if they withdraw their deposits, they face the problem of sunk costs. Furthermore, during the final distribution of airdrops, the passive linear release of large holders has proven that project teams chose to transfer the benefits of large holders to retail investors in their distribution.

In market pricing, off-chain point trading platforms like Whales Market also provide project teams with a measurable data source. Specifically, they have conducted considerable market pricing for OTC trading of points in the market, allowing project teams to make appropriate adjustments to the expected pricing of points through market makers. Moreover, the low liquidity environment before TGE reduces the difficulty of market-making. Of course, such trading also exacerbates the potential overdraft of project expectations.

In summary, from the manipulation space of points, several disadvantages of point incentives can be derived:

• Large manipulation space: Whether in distribution or market pricing, project teams can perform sufficient operations.
• Overdraft of expectations: The long cycle of point incentives and excessive speculation in the secondary market lead to the consumption of users' expectations for airdrops.
• Spreading benefits: Due to the long release cycle of points, the value generated by early and late participants is spread out, which can harm the interests of participants.

How to Leverage Strengths and Avoid Weaknesses

After analyzing the advantages and disadvantages of point incentives, we can explore how to leverage strengths and avoid weaknesses based on the points model to better construct incentive models in the crypto field.

Distribution Design

In the long cycle of point incentives, the distribution of points is crucial for the development of the protocol. Unlike interactions on task platforms, most projects have not clarified the correspondence between interaction metrics and points, creating a kind of black box where users have no right to know. However, completely transparent rules can also facilitate targeted strategies by studios, leading to increased anti-witch costs on-chain. A possible solution is to decentralize the incentive process to control the visibility of rules to users, for example, by organically distributing points through protocols within the ecosystem, which can further refine incentives based on users' on-chain behaviors while spreading distribution costs. Additionally, decentralized distribution rights give specific project teams greater dynamic adjustment space, making it easier for users to benefit from strong composability.

Balancing Interests

Many protocols now face the trade-off between TVL and on-chain interaction data, which is reflected in how to allocate corresponding weights in the points mechanism. For projects like Blur, which are transaction-driven, or DeFi projects dominated by TVL, the two can essentially form a mutually reinforcing flywheel effect, so the role of points is to incentivize a single metric. However, when this logic shifts to Layer 2, participants begin to split, and the demands of project teams shift from single metrics to diversified growth, thus raising higher requirements for the points distribution mechanism. Blast's golden points attempted to address this split, but ultimately, due to distribution ratio issues, the overall effect was still unsatisfactory. In other projects, there are currently no similar mechanism designs, so future protocol point mechanism designs could consider corresponding refinements for interaction and deposit incentives.

Demand Space for Incentive Space

Nowadays, many projects use point incentives primarily to delay TGE while maintaining incentive activities, lacking the inherent utility of points compared to traditional point incentive use cases. This demand gap is also the fundamental reason why points exist in users' eyes merely as another form of tokens. Therefore, effective development can be conducted for this demand, such as using points to offset related fees for cross-chain bridges or on-chain derivatives, which can allow users to immediately gain the utility generated by points, attracting them to continue using the protocol while also releasing space for point distribution, reducing inflation pressure while controlling expectations. However, effective and precise measurement between users' actual interactions and transaction fees is required in this regard.

Moreover, whether in traditional fields or the crypto space, demand will always need to exceed incentives, and a significant portion of the demand space is generated by the protocol itself. Just as many MEME-related projects do not have point incentives because they naturally occupy an advantage on the demand side, users derive more value from these projects externally. Therefore, for project teams, it is essential to consider whether their product model construction has corresponding PMF, ensuring that users' participation is not solely for elusive tokens.

Consensus-Based Incentives

For users, consensus-based incentives create a clearly defined environment for them and allow them to participate as independent individuals in consensus building. For example, within a community, project teams can create decentralized environments where users can engage in free competition and conduct organic distribution similar to PoW based on results. This kind of competition can, on one hand, mitigate the impact of airdrop distribution cycles within the consensus, and on the other hand, enhance user loyalty and retention. However, changes in consensus are relatively slow and less flexible, which may not be suitable for rapidly growing ecosystems.

On-Chain Points

Putting points on-chain differs from directly issuing tokens; it removes liquidity compared to tokens while increasing immutability and composability on-chain. Linea LXP presents a good example for us; when all addresses and points can be traced on-chain, the operational space visibly shrinks, and smart contracts provide on-chain composability, significantly enhancing the metric significance of points within the ecosystem, allowing protocols within the ecosystem to adjust incentives based on relevant metrics.