"Organic growth point" or "top PUA", what are the advantages and disadvantages of the points incentive model?

Written by: Pzai, Foresight News

existcryptocurrencyIn the long history of the development of the field, the economic model based on decentralized consensus has brought the dawn of the holy grail of cryptocurrencies to countless users. However, as the industry continues to grow, project owners have also begun to think about how to balance the relationship between the long-term development of the protocol and user retention in the crypto tide.TokenThe relatively "moderate" incentive model is being adopted by more and more project parties. And many people believe that the attention brought by the point incentive can form an organic growth point for the protocol indicators and strongly promote the growth of the project.

However, recently, the TGE distribution of projects such as Blast has triggered a wave of anger among people, which is reflected in the dissatisfaction with the low returns brought by the extended incentive cycle. Some big investors have called out that similar airdrops have now evolved into "top PUA" for all participants. Therefore, this article explores the advantages and disadvantages of the points model from a multi-dimensional perspective and tries to find corresponding solutions.

Early incentive model

In the early days of the wave, when Ethereum ICO was in full swing, airdrops were relatively simple and crude. You only needed to submit a simple 0x address to get a considerable amount of money.TokenSince the main feature of ICO era projects is that they are based on concept speculation, and the construction of on-chain interaction is almost blank, the (coin holding) address itself can become an incentive indicator for everyone.

而在 DeFi Summer 伊始，Balancer 和 Compound 都采用了流动性挖矿的方式进行激励。不难看出对于当时的 DeFi 项目而言，链上流动性的规模决定协议的发展，并且就当时的市场形势而言流动性的需求也比较紧迫，所以他们都采用了直接的Token激励。虽说对 TVL 的增长贡献颇丰，但也衍生出了「挖卖提」的弊病。

After that, Uniswap’s airdrop was a big success, bringing the interactive airdrop paradigm into the crypto space and giving rise to a group of professional airdrop hunters. Many DeFi projects followed suit, and many L2 With the implementation of public chain technology, 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 is inevitable that participants will have related airdrop expectations. From then on, the incentive model centered on tokens and interactions began to merge into the crypto economy.

In summary, we can conclude that the earlycryptocurrencyFeatures of the field incentive model:

• Direct token incentives：For early-stage projects, the growth space brought by the unsaturated competitive environment gives them sufficient freedom and enables them to pass on the benefits to users through token incentives while achieving scale growth.

• Low interaction threshold: Since the on-chain ecosystem was not mature at the time, the product model of the protocol was relatively simple, and the interaction process was also easy for users.

• Immediate returns (synchronicity): Before Uniswap, many projects adopted mining to provide instant token returns for users’ deposits, and what you do is what you get.

The origin of points incentive

Before the point incentive, with the vigorous development of the ecosystem, the project was faced with the dilemma of user retention and incentives. Galxe and other task platforms provide a solution. Specifically, the task platform allows the project to spread the incentive process to the specific tasks of user interaction, and use NFTs instead of tokens for a certain degree of incentives (marking). Overall, this incentive method has begun to produce incentive asynchrony, that is, the period between the issuance of token incentives and the actual interaction of users has been lengthened. Point incentives, like task platforms, are actually one of the products of the refinement of interactions in the crypto field.

The earliest project to widely adopt the points model was Blur. Pacman innovatively used points to calculate incentives for NFT transactions, and related measures have significantly increased the growth of Blur's protocol, specifically in terms of liquidity and transaction volume. Analyzing the scale development of Blur from the data in Figure 1, we can see that points mainly play the following three roles:

• Raise your confidence：Through point incentives, users can have a certain sense of gain in advance, increase their confidence in subsequent airdrops, and affect the initial start of the coin price.

• Extended cycle: Points can spread users' expectations for protocol airdrops and extend the overall incentive cycle. An obvious example is that after Blur implemented the token launch, it still maintained the existence of point incentives, reducing selling pressure while creating a sustainable incentive environment for users, which is reflected in the continuity of trading volume and TVL.

• Reality: Compared with NFT after the interactive task is completed, points can give users a sense of corresponding token mapping, making users feel that they have obtained tokens rather than just symbolic badges, which is reflected in the correlation between the transaction volume of early mining and token prices.

Figure 1 Blur related data (DefiLlama)

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

• Improve retention：In the past, under the background of "mining, selling and withdrawing", users were usually not very loyal to the protocol. However, through point incentives, project parties can guide users to generate continuous cash flow and on-chain interaction.

• Avoiding Token Costs：Points-based incentives can reduce the project party’s costs in token market making and corresponding operations, and sometimes can also reduce compliance risks.

• Greater flexibility：The organic adjustment of point incentives gives project parties greater flexibility and is not affected by the trend of related tokens, allowing them to focus more on product construction.

Points create confidence

In the operation cycle of crypto projects with points as the main incentive model, we can roughly divide it into three stages. The two important nodes are the use of points incentives and TGE (token generation event). Figure 2 shows the changes in user confidence during the project cycle.

Figure 2 Changes in user confidence throughout the project lifecycle

Before the point incentive, we can see that the overall confidence showed a linear growth trend, because in the early stages of the project, users are usually optimistic about the development of the project, and there are more favorable news in the early stages. After the implementation of the point incentive, compared with the no point incentive, the user's confidence was temporarily enhanced because of the sense of gain generated by the points themselves. But then the cycle of the point incentive began to spread the user's expectations for the project airdrop, and at the same time, the market began to price the project's incentives off-site, so the overall confidence fell back to the level without the point incentive. After TGE, the confidence of users who have experienced the point incentive will be reduced even more, because the overall cycle of the point incentive is longer, which makes it impossible for users to continue to bear the costs generated by the cycle when the overall benefits are clear after TGE, and then choose to sell, which is reflected in greater selling pressure.

In summary, we can see thatThe confidence level 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 important part must be the actions of the project owners. The point incentive itself provides project owners with a variety of manipulating space.

Integral Manipulation Space

The current point incentive model has essentially become a tool for project owners to manage expectations, and because point incentives are a long process, users will have corresponding sunk costs, and these sunk costs will bring some passive retention to the project, so as long as the project owner extends the incentive cycle and maintains the basic incentives within the cycle, the performance of the basic indicators of the project can be maintained. In addition to the basic incentives, the allocation space of the project owner is gradually increasing.

In terms of issuance, the manipulation space of points is mainly reflected in not being on the chain and the clarity of rules. Compared with token incentives, point incentives are usually not on the chain, which gives the project party more room for manipulation. In terms of rule clarity, the project party has the right to allocate incentives to each part of the protocol, and from the incentives of Blast, it can be seen that the long cycle of incentives represents the strong flexibility of the rules, which can neutralize the emotional reactions of most users to the greatest extent within the cycle and reduce the loss of confidence. However, the distribution of the second phase of Blast actually diluted the deposit points of large households before the launch, and transferred this part of the benefits to the on-chain interactors. For large households, such a flat spread may result in airdrops that may not cover the capital costs incurred in the early stage, and increase the interaction costs on the chain in the later stage, but if they withdraw their deposits, they will face the problem of sunk costs. And when the airdrops are finally distributed, the linear release of the passivity of large households has proved that the project party has chosen to transfer the benefits of large households to retail households in the distribution.

In terms of market pricing, over-the-counter points trading platforms such as Whales Market also provide a measurable data source for project owners. Specifically, they have made considerable market-based pricing for points OTC transactions in the market, and project owners can make appropriate adjustments to the expected pricing brought by points through market makers, and the low liquidity environment before TGE reduces the difficulty of market making. Of course, such transactions also exacerbate the overdraft of potential project expectations.

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

• Large operating space: Whether in terms of issuance or market pricing, the project party can perform sufficient operations.

• Overdraft Expectation：The long cycle of point incentives and excessive speculation in the secondary market have led to a consumption of users' airdrop expectations.

• Spread the income：Due to the long release cycle of points, the value generated by early participants and late participants is evenly distributed, which will correspondingly harm the interests of the participants.

How to play to your strengths and avoid your weaknesses

After analyzing the advantages and disadvantages of point incentives, we can explore how to build a better incentive model in the encryption field by leveraging the strengths and avoiding the weaknesses of the point model.

Allocation Design

In the long cycle of point incentives, point allocation is crucial to the development of the protocol. Unlike the interaction on the task platform, most projects do not clarify the correspondence between interaction indicators and points, forming a kind of black box. Users have no right to know in this case. However, completely clear rules will also facilitate the studio's targeted play, leading to higher feedback on the chain.WitchCost. A possible solution is to control the visibility of rules to users by decentralizing the incentive process. For example, points can be distributed organically through the internal agreement of the ecosystem. While spreading the distribution cost, the incentives for users’ on-chain behaviors can be further refined. The decentralized distribution rights give specific project parties greater dynamic adjustment space, and also make it easier for users to kill two birds with one stone based on strong composability.

Weighing the interests of all parties

Now many agreements requireXiaobai NavigationThe trade-off between TVL and on-chain interaction data is reflected in the points mechanism as how to allocate corresponding weights. For projects such as Blur that are dominated by transactions or DeFi that are dominated by TVL, the two can essentially form a flywheel effect that promotes each other, so the role of points is to incentivize a single indicator. But when this logic is transferred to Layer 2, participants begin to split, and the demands of the project parties also shift from a single indicator to diversified growth, which in turn puts higher demands on the points allocation mechanism. Blast's gold points attempt to solve this split, but in the end, due to the problem of distribution ratio, the overall effect is still unsatisfactory. In other projects, there is currently no similar mechanism design, so the point mechanism design of future protocols can consider corresponding refinements of interaction and deposit incentives.

Demand space for incentive space

Nowadays, the original intention of many projects to use points incentives is just to delay TGE while maintaining incentive activities. Compared with traditional point incentive use cases, the purpose of points themselves is missing, and the lack of this part of the demand is also the fundamental reason why points only exist as another token in the eyes of users. Therefore, this part of the demand can be effectively developed. For example, for cross-chain bridges or on-chain derivatives, using points to offset related fees can not only enable users to immediately obtain the utility generated by points, attract users to continue to use the protocol, but also free up space for point allocation, reduce inflationary pressure and control expectations. However, in this part, it is necessary to effectively and accurately measure the actual interaction between users and handling fees.

In addition, whether in the traditional field or the encryption field, demand will always be greater than incentives, and a large part of the demand space is generated by the protocol itself. Just as many MEME-related projects do not have point incentives, because they naturally have an advantage on the demand side, and users get more value from outside the protocol when using these projects. Therefore, for the project party, it is necessary to consider whether the construction of their product model has the corresponding PMF, so that the purpose of users participating is no longer for the illusory tokens.

Consensus Incentives

For users, consensus incentives create an environment with clear rules for them and allow them to participate in consensus building as independent individuals.CommunityIn the process, project owners can build some decentralized environments to allow users to participate in free competition and make organic distribution similar to PoW according to the results. On the one hand, such competition can eliminate the impact of the airdrop distribution cycle in the consensus, and on the other hand, it can also improve user loyalty and retention. However, the consensus itself changes relatively slowly and has low flexibility, which may not be suitable for a fast-growing ecosystem.

On-chain points

Putting points on the chain is different from issuing tokens directly. Compared with tokens, it removes liquidity while increasing the immutability and composability of the chain. Linea LXP presents us with a good example. When all addresses and points can be traced on the chain, the operating space is visibly reduced, and the smartcontractIt provides chain-based composability, greatly improving the index of points within the ecosystem, and enabling protocols within the ecosystem to adjust incentives based on relevant indicators.

The article comes from the Internet:"Organic growth point" or "top PUA", what are the advantages and disadvantages of the points incentive model?

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