空投三难困境：数据分析怎样做才是项目方空投正确姿势

The author, founder and translator of Bitcoin Trading Network recently started their highly anticipated airdrop, which, like most airdrops, has also caused a lot of controversy. Sadly, this is no longer a surprising thing, so why does this happen again and again? You may hear some views that insiders just want to cash in billions of dollars and leave. The team doesn't know what to do and there is no suitable consultant. Whales should be given more priority because they bring them. Because airdrops are related to the democratization of cryptocurrency, there will be no agreement on the use or inconsistent airdrop incentives in stress tests will continue to have strange side effects. These views are not wrong, but they are not completely correct. Let's analyze them to ensure that we have a comprehensive understanding of the problem at hand. There is a basic tension in airdrops. You need to choose between the following three factors: capital efficiency, decentralization and retention rate. You will often encounter this. The situation of airdrops works well in one dimension, but it is difficult to achieve a good balance between two dimensions or all three dimensions. The retention rate is the most difficult one. The retention rate above one dimension is unheard of. Capital efficiency is defined as the standard of how many tokens you give to participants. The more effectively you allocate your airdrops, the easier it will become mobile mining. Every dollar you deposit, one token will help whale users to decentralize. The definition is who will get your tokens and under what standards. The recent airdrop of your tokens has adopted any standard practice in order to maximize the number of users to get tokens, which is usually a good thing because it saves you from legal troubles and brings you greater influence because you make people rich. The definition of retention rate is how many users will continue to hold airdropped tokens after airdrop. In a sense, this is a way to measure whether users are consistent with your intentions. The lower the retention rate, the more inconsistent your users are with your intentions. The industry benchmark means that only the addresses appear here for the right reasons. Let's not talk about the retention rate. Let's study the first two factors in more detail: capital efficiency and decentralized capital efficiency. In order to understand capital efficiency, let's know a new term called coefficient, which can basically calculate the benefits brought by allocating one dollar of funds to a certain number of accounts. Your coefficient ultimately determines the waste of airdrops. If your coefficient is technically speaking, it means that you are. Running a mobile mining scheme will anger many users. However, when you reach such a level, that is, when the coefficient expands, you will see extreme waste and rampant mining decentralization, which brings us to the second factor decentralization. You finally want to help the little people, who are the real users, and hope that they will seize the opportunity to use your products as soon as possible, even though they are not rich. If your coefficient is too close, then you will not be able to give anything to the little people. It can benefit whales. This is where the debate on airdrop becomes fierce. There are three types of users who make quick money here and then turn away. Small people who like your products may use multiple wallets in the process. Small people who like your products will continue to stay. Industry miners will definitely take most of your incentive tokens at this stage and sell them before moving on to the next target. The third type is the worst user. The first type is acceptable. The second type is the best quality. How to distinguish these three types of users is a great challenge for airdrop, so how to solve this problem? Although I don't have a specific solution, I have an idea on how to solve this problem. I have spent several years thinking and observing the project breakdown at first hand, and I will explain what I mean in detail. Now, please think about a fundamental problem first. You have all users, and you need to be able to divide them into different groups based on a certain value judgment. The value here is specific to observers. Therefore, it will vary from project to project. It is never enough to try to blame some magical airdrop filters. By studying the data, you can start to understand what your users really look like and start to make decisions based on data science to subdivide your airdrops. Why doesn't anyone do this? I will talk about this in my future article, but this is a hard data problem, which requires data expertise, time and money. Not many teams are willing or able to do this. The last dimension is the retention rate. Before we discuss the retention rate, we'd better define the meaning of retention rate. I summarize it as follows: the number of people who get airdrops, the number of people who hold airdrops, and most of the typical mistakes made by airdrops are to treat them as one-off. To prove this point, I think some data may be helpful. Fortunately, I have actually carried out several rounds of airdrops. I hope to find some simple dashboards to get the retention rate data I want, but unfortunately I was wrong, so I decided to roll up my sleeves and collect the data myself. I don't want to complicate things too much. I want to understand a simple thing: how the percentage of users who hold the balance changes during the continuous airdrops. I went to the website and found a list of all the addresses that participated in the airdrops. Then I built a small manual grab of the balance of each address in the list and sorted out some data. Before we continue, I need to remind you that each airdrop is independent of the previous airdrops. There are no rewards or links for the airdrops before the reservation. I know why. Let's continue. In the first round of airdrop, a total of users obtained airdrop tokens. The tokens obtained by users can do the following operations: main network users with 10,000 addresses, repeated main network users with 10,000 addresses, voters with 10,000 addresses, multi-signers with 10,000 addresses, donors with 10,000 addresses being squeezed out of Ethereum, and users with 10,000 addresses. After analyzing all these users and their balances, I got the following distribution balance, which indicates that users discarded tokens because unclaimed tokens were sent directly to qualified users at the end of airdrop. In any case, compared with the previous airdrops I observed, the balance of the first airdrop was unexpectedly good, and the result was very good. Then I want to know how various standards play a role in determining whether users may keep tokens. The only problem with this method is that the addresses may belong to multiple categories, which will distort the data. I will not just look at it on the surface. This is a rough indicator. Users once had the highest proportion of balance, followed by those who were squeezed out of Ethereum. Obviously, these are not the most suitable market segments for allocating users. I think this is the lowest percentage of multi-signers. 比特币今日价格行情网_okx交易所app_永续合约_比特币怎么买卖交易_虚拟币交易所平台

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