"Organic growth points" or "top PUA", how to interpret the advantages and disadvantages of the points incentive model?

In the long river of development in the Cryptocurrency field, the economic model built on Decentralization Consensus has brought the dawn of the encryption Holy Grail to countless users. However, as the industry continues to evolve, project parties are also beginning to consider how to balance the long-term development of the protocol with user retention in the tide of encryption. As a relatively ‘neutral’ incentive model between news and Tokens, points are being adopted by more and more project parties. Moreover, many believe that the attention brought by point incentives can form organic rise points for protocol indicators and strongly promote project rise.

However, recently, the distribution of TGE in projects such as Blast has triggered a wave of anger, manifested in dissatisfaction with the extended incentive period leading to low returns. Some Large Investors have called the current similar Airdrop a ‘top-level PUA’ for all participants, so this article starts from a multi-dimensional perspective to explore the advantages and disadvantages of the points model, and attempts to find corresponding solutions.

Early Incentive Mode

In the early days of the Ethereum ICO frenzy, Airdrops were relatively straightforward. All you needed to do was submit a simple 0x Address to receive a substantial amount of Tokens. During the ICO era, where projects were primarily driven by speculative concepts and on-chain interactions were almost non-existent, the (holding) Address itself served as an incentive indicator for everyone.

At the beginning of Decentralized Finance Summer, both Balancer and Compound adopted Liquidity Mining as a means of incentive. It is not difficult to see that for the Decentralized Finance projects at that time, the scale of on-chain Liquidity determined the development of the protocol, and the demand for Liquidity was relatively urgent in the market situation at that time, so they both adopted direct Token incentives. Although they made significant contributions to the rise of TVL, it also gave rise to the drawbacks of ‘mining for arbitrage’.

Afterwards, Uniswap’s Airdrop can be considered as a catalyst, truly bringing the interactive Airdrop paradigm into the field of encryption, and thereby giving birth to a professional Airdrop hunter community. Subsequently, many Decentralized Finance projects followed suit, accompanied by the technical implementation of many L2 and public chain technologies. The construction of ecological governance models has also been put on the agenda. Since the governance of many protocols is essentially a subset of their Token economy, it inevitably generates related Airdrop expectations for participants. Thus, the incentive model centered on Token and interaction begins to integrate into the field of encryption economy.

In summary, we can conclude the characteristics of the early incentive models in the cryptocurrency field.

• Direct Token incentives: For early projects, the space for rise brought by the unsaturated competitive environment gives them enough freedom, and enables them to benefit users through Token incentives while achieving scale rise.
• Low entry barrier for interaction: as the on-chain ecosystem was not mature at the time, the product model of the protocol was relatively simple, making the interaction process very simple for users.
• Instant Rewards (Synchronicity): Before Uniswap, many projects adopted the Mining method to provide instant Token rewards to users for their deposits, allowing users to receive rewards in real-time.

The Origin of Incentive Points

Before the incentive points, with the vigorous development of the ecosystem, the project faces a dilemma of user retention and incentives. Platforms such as Galxe provide a solution, specifically, the task platform allows projects to distribute incentives to specific tasks through user interactions, and adopts Non-fungible Tokens instead of Tokens for incentives to some extent (marking). Overall, this incentive method has already started to generate asynchronous incentives, where the period between distributing Token incentives and actual user interactions is extended. And incentive points, like the task platform, are one of the products of fine-grained interactions in the encryption field.

The earliest project widely adopting the points model is BLUR. Pacman innovatively uses points for incentive calculation in Non-fungible Token transactions, and the corresponding measures have significantly impacted BLUR’s protocol rise, specifically reflected in Liquidity and volume. From the data analysis of Figure 1 on the scale development of BLUR, we can see that points mainly serve the following three functions:

• Boosting confidence: By incentivizing points, allowing users to have a certain sense of achievement in advance, and increasing their confidence in Airdrop, it affects the initial launch of the coin price.
• Extended Cycle: Points can spread users’ expectations for protocolAirdrop and extend the overall incentive period. A clear example is that after the implementation of Blur Token Launch, the incentive of points is still maintained, creating a sustainable incentive environment for users while reducing selling pressure, which is reflected in the continuity of volume and TVL.
• Realness: Compared to the Non-fungible Tokens after the interactive tasks are completed, the points can give users a sense of mapping corresponding to a certain Token, making users feel that they have obtained the Token rather than just a symbolic badge, reflected in the correlation of volume and Token price in the early Mining.

Figure 1 BLUR related data (DefiLlama)

Based on the above functions, several advantages of incentive points can be derived:

• Improve retention rate: In the past, under the context of ‘mining and selling’, users usually have low loyalty to the protocol. However, through point incentives, the project party can guide users to generate sustainable cash flow and on-chain interactions.
• Avoiding Token costs: Incentives based on points can reduce the costs of the project party in Token market making and related operations, and sometimes even drop Compliance risks.
• Greater flexibility: Organic adjustment of incentive points gives the project party greater flexibility and is not affected by the trend of related tokens, allowing more attention to be focused on product development.

Confidence Created by Points

In the operation cycle of the encryption project with points as the main incentive mode, we can roughly divide it into three stages, with two important Nodes being points incentive and TGE (Token Generation Event). Figure 2 shows the change in user confidence during the project cycle.

Figure 2 Confidence Level Changes of Users Throughout the Project Life Cycle

Before the implementation of incentives, we can see that the overall confidence shows a linear rise. In the early stages of the project, users usually maintain an optimistic attitude towards the development of the project, and there is also a lot of favorable information corresponding to the early stages. After the implementation of incentives, compared to no incentives, users have a temporary increase in confidence due to the sense of achievement generated by the incentives. However, the incentive cycle begins to spread the user’s expectations of Airdrop, and the market begins to price the incentives off the market, so the overall confidence level drops to the level without incentives. After the TGE, users who have experienced incentives will have a greater drop in confidence because the overall incentive cycle is longer, which makes it difficult for users to continue to bear the costs generated by the cycle without a clear overall profit, and they choose to dump, resulting in greater selling pressure.

In summary, we can see that the level of confidence brought by points is mainly reflected in the initial stage of point incentives, which essentially provides an opportunity for users to enter the ecosystem. But for user retention, the most crucial part must be the role of the project party. The point incentive itself provides project parties with diversified manipulation space.

Manipulation Space of Points

The current incentive model has fundamentally become a tool for the project party to manage expectations. As incentive is a long-term process, users will have corresponding sunk costs, which will bring some passive retention to the project. Therefore, as long as the project party extends the incentive period and maintains basic incentives during the period, they can maintain the performance of the project’s basic indicators. In addition to the basic incentives, the project party’s allocation space is also gradually increasing.

In terms of distribution, the manipulation space of points is mainly reflected in the non-on-chain and clear rules. Compared with token incentives, point incentives usually do not go on-chain, which gives the project party more room for manipulation. In terms of clear rules, the project party has control over the incentive distribution of each part within the protocol. From the incentive of Blast, it can be seen that a long incentive cycle represents the strong flexibility of the rules, which can effectively neutralize the emotional reactions of most users within the cycle and reduce confidence loss. However, the distribution of Blast in the second phase actually diluted the deposit points of Large Investors before going online and transferred this portion of benefits to on-chain participants. For Large Investors, such sharing may result in the Airdrop not covering the initial cost of funds and increasing the later on-chain interaction cost. However, if they withdraw the deposit, they will face the problem of sunk costs. Moreover, in the final distribution of the Airdrop, the passive linear release of Large Investors has proven that the project party chose to transfer the benefits of Large Investors to retail investors in the distribution process.

In terms of market pricing, off-exchange points trading platforms such as Whales Market provide a measurable data source for the project party. Specifically, they have conducted significant market-based pricing for points OTC transactions in the market, and the project party can make appropriate adjustments to the expected pricing of points through market makers, and the low liquidity environment before TGE reduces the difficulty of market making. Of course, such transactions also exacerbate the potential overcommitment of project expectations.

In conclusion, the manipulation space of points can lead to the disadvantages of point incentives:

• Great manipulation space: project party can have enough manipulation in both issuance and market pricing.
• Overdraft expectation: the long cycle of point incentives and the excessive speculation in the Secondary Market consume the user’s expectation of Airdrop.
• Shared revenue: Due to the long release cycle of points, the value generated by early and late participants is shared, which will correspondingly harm the interests of participants.

How to play to one’s strengths and avoid weaknesses

After analyzing the advantages and disadvantages of incentive points, we can explore how to leverage the strengths and avoid the weaknesses based on the point system, and build a better incentive model in the encryption field.

Allocation Design

In the long-term cycle of point incentives, point distribution is crucial to the development of the protocol. Unlike the interaction on task platforms, most projects have not clarified the correspondence between interaction indicators and points, forming some kind of black box, where users do not have the right to know. However, completely transparent rules can also provide convenience for the studio’s targeted play and increase the cost of anti-witch attacks on-chain. One possible solution is to control the visibility of the rules to users by dispersing the incentive process, for example, distributing points through organic allocation within the ecosystem protocol, further refining user on-chain behavior while sharing distribution costs, and giving specific project parties greater dynamic adjustment space in decentralized distribution, which also facilitates users to achieve multi-tasking based on strong composability.

Weighing the interests of all parties

Now many protocols need to balance between TVL and on-chain interaction data, which is reflected in the scoring mechanism on how to allocate the corresponding weights. For projects like Blur, which are transaction-driven, or Decentralized Finance, which is TVL-driven, the two can essentially form a mutually reinforcing flywheel effect. Therefore, the role of scoring is to incentivize a single indicator. However, when this trap logic is transferred to Layer 2, participants begin to split, and the demands of project parties also shift from a single indicator to diversified rises, thereby posing higher requirements on the scoring allocation mechanism. Blast’s gold scoring attempts to solve such division, but due to allocation ratio issues, the overall effect is still unsatisfactory. In other projects, there is currently no similar mechanism design, so the future protocol’s scoring mechanism design can consider refining the incentives for interaction and deposits accordingly.

Space for demand exchange space for incentive

Today, the original intention of many projects using point incentives is just to perform latency on TGE while maintaining incentive activities. Compared to traditional point incentive use cases, they lack the purpose of points themselves, and this gap in demand is also the fundamental reason why points are seen by users as just another form of token. Therefore, effective development can be carried out for this part of the demand. For example, for cross-chain bridges or on-chain derivatives, using points to offset related costs can not only enable users to immediately obtain the utility generated by points, attract users to continuously use the protocol, but also release the space allocated for points and reduce inflationary pressure while controlling expectations. However, in this part, it is necessary to make an effective and accurate measurement between users’ actual interaction and transaction fees.

In addition, whether it is in the traditional field or the encryption field, the demand is always greater than the incentives, and a large part of the demand space is generated by the protocol itself. Just like many MEME-related projects do not have point incentives, because they naturally occupy the advantage of the demand side, and users obtain more value from outside the protocol when using these projects. Therefore, for project parties, they need to consider whether their product model construction has the corresponding product-market fit, so that the purpose of user participation is no longer just for elusive tokens.

Consensus Incentives

For users, the incentive of Consensus creates a well-defined environment for them and allows them to participate as independent individuals in the construction of Consensus. For example, in the community, the project party can create a decentralized environment for users to participate in free competition and distribute organically similar to PoW based on the results. Such competition can not only mitigate the impact of Airdrop distribution cycle in Consensus, but also increase user loyalty and retention. However, the change of Consensus itself is relatively slow and less flexible, which may not be suitable for the rapidly rising ecosystem.

on-chain Points

The practice of putting points on-chain is different from directly issuing tokens. Compared to tokens, on-chain removes liquidity while increasing immutability and composability. Linea LXP provides us with a good example. When all addresses and points can be traced on-chain, the operational space visibly decreases. Moreover, smart contracts provide on-chain composability, greatly improving the significance of points within the ecosystem, allowing protocols within the ecosystem to incentivize and adjust based on relevant metrics.

Statement:

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

2. Disclaimer: The views and opinions expressed in this article are solely those of the author and do not constitute any investment advice.

3. The other language versions of the article are translated by the Gate Learn team. Copying, disseminating, or plagiarizing translated articles is not allowed without mentioning Gate.io.