a16z: There are 220 million active Addresses on the blockchain, how many of them are real users?

According to the 2024 encryption industry report, despite the 220 million monthly active addresses, the actual monthly active transaction users are only between 30 million and 60 million, and most addresses are still passive holders. This article originated from an article written by Daren Matsuoka Eddy Lazzarin, and was compiled by Vernacular Block Chain. (Synopsis: "a16z is biased against EVMs!") Where does the dissatisfaction of Lily Liu, president of the Solana Foundation, come from? (Background added: a16z Report: How Does Crypto Solve the Pressing Challenges of AI?) As part of our 2024 Encryption Industry Report, the team spent a lot of time assessing the current state of the Encryption industry. As the industry matures and more and more apps come online, we want to understand how many people are actually using cryptocurrency. This is a complex problem because the most obvious and easily quantifiable usage metric, the active address, is easily manipulated. Let's share some insights. In the traditional software world, the concept of "user" is widely understood. Of course, there are many ways to measure user quality, and in fact, the field of user rise analysis specializes in this topic. But at the most basic level, users can be categorized as "daily active users" (DAU), "monthly active users" (MAU), etc. In the field of encryption, the situation is more complicated. This is because in Blockon-chain, user identities are pseudo-anonymous. A person can easily establish and control what is known as a "Sybil Attack" (i.e. a set of different identities called a "Public KeyAddress") operating on a Blockon-chain. (There are many legitimate reasons for this behavior, such as for privacy, security, or other purposes.) So it's hard to know exactly how many addresses a person uses. (Conversely, multiple people can use the same address through multiple signatures, total accounts, and various account abstract protocols.) Until recently, the most popular Block chain had very limited capacity, resulting in high Money Laundering. This creates a natural barrier that prevents people from building and using hundreds or even k addresses in bulk, as this can cost a lot of money. But as the scalability of the encryption infrastructure has increased — through L2 Rollup and the emerging high-throughput L1 — the transaction cost of many block chains has dropped significantly, close to zero. But isn't the cost of establishing multiple identities close to zero in traditional Internet applications? This is basically true. For example, one person can easily create and use multiple email addresses. But the key difference is that there is a strong incentive in the encryption industry for people to do so. The encryption industry has long rewarded early adopters by issuing tokens. Today, new protocols often activate their token circulation through "Airdrop" — the activity of offering token rewards to a pre-set set set of addresses. Typically, these address lists are generated retrospectively based on historical on-chain transactions. Some may try to manipulate the system by creating multiple identities and making transactions. Within the industry, this strategy is known as "Airdrop farming." Given these actions, it is clear to us that the 220 million monthly active addresses we measured in September 2024 do not equate to 220 million people or users. (It's important to note that addresses active across multiple EVM chains are only counted once into the 220 million total.) So, how many active users are there? 1 k thousand? 5 k thousand? 100 million? This is the question we are trying to answer. Next is our methodology. Method One: Screening Active Addresses One approach we take is to filter out addresses that may be controlled by a bot or part of Sybil Attack. There are multiple ways to achieve this through on-chain analysis and forensics, here are some of the ways we've explored: 1 Filter out addresses that receive funding from distribution contracts – the sole purpose of distribution contracts is to receive funds and automatically distribute them to multiple different addresses. While there may be some miscalculations, this kind of activity suggests that these target addresses are all from the same source and therefore interrelated to some extent. 2. Filter out addresses with balances close to zero in a specific time period. For example, if you're looking for actual monthly active users in September 2024, try excluding addresses with balances close to zero on September 1 and September 30. This criterion indicates that these addresses are temporary. While bots and Sybil Attackers may clean up balances after performing an action, real users often keep some balance in Wallet to pay for future Money Laundering. 3. Analyze the distribution of addresses that make one, two, three, four, five, or more transactions over a specific time period. Addresses that only make one or two transactions are low-quality users at best, and bots or sybil attackers at worst. This approach works best for long-term data aggregation. 4. Filter out addresses that have made a large number of transactions in a short period of time. When humans use Wallet or the application interface, they can only reasonably process a certain number of transactions in a given time, while robots can make more frequent transactions in a shorter period of time. 5. Selectively include addresses tied to identity protocols, which usually require a certain setup cost. For example, an Address with an ENS name, Farcaster ID, and other social identity links is likely to be the actual user. These are just some of the patterns that on-chain may indicate bot behavior, and are by no means exhaustive. We welcome suggestions for improvement on that basis. Method Two: Inferring from Wallet Users Another way to estimate monthly active users is to look at off-chain sources. The most obvious point of inspection is Wallet users. In February 2024, the popular encryptionWallet MetaMask reported 30 million monthly active users. They define a monthly active user as "a user who loads a MetaMask extension page or opens a mobile app at least once in any 30-day row." Suppose we want to estimate the users who actually made the transaction, the next step is to determine how many of the MetaMask users ended up making the transaction. In 2019, MetaMask reported that on a given day, about 30% of active users confirmed an on-chain transaction. (This is the latest estimate available.) If we apply this ratio to monthly active users (MAUs), about 9 million users transact through the MetaMask Wallet product every month. Next, we need to understand MetaMask's total Wallet market share across all Block chains. While this exact information is not readily available, some reasonable assumptions can be made based on the information available. For example, we can estimate MetaMask's share of the mobile wallet market based on data from mobile analytics company Sensor Tower. (Due to the Commercial Services Protocol, we are unable to disclose specific numbers here.) Once we estimate MetaMask's market share, we can simply extrapolate the total number of Cryptocurrency users from the 9 million monthly active trading users profile we derived earlier. We can then compare this result with the result in Method One to see if it is in the same range. We can also further refine our estimates by analyzing proprietary data that other wallets and infrastructure providers are willing to share,...