The True Number of Cryptocurrency Users

As part of our 2024 Crypto State of the Industry report, our team has spent a lot of time trying to assess the crypto industry. With the industry's growth and more applications coming online, we want to understand how many people are actually using cryptocurrencies. This is a complex question, as the most obvious and quantifiable usage metric - active addresses - is easily manipulable. So here are our thoughts. In traditional software, the concept of "users" is clear. Of course, there are many ways to measure the quality of users - in fact, the entire growth analytics field is dedicated to this topic - but at the most basic level, users can be boiled down to "daily active users" (DAU), "monthly active users" (MAU), and so on. In cryptocurrencies, the situation is more complex. This is because on the blockchain, user identity is pseudonymous. A person can easily create and control what is called a "Sybil" - a set of distinct identities, called "public addresses" - on the blockchain. (There are many completely legitimate reasons to do this, such as for privacy, security, or other purposes.) So it's hard to know how many addresses a person might be using. (The reverse is also true, as multiple users can use a single address through multisig, shared accounts, and various account abstraction protocols.) Until recently, the capacity of the most popular blockchains was very limited, resulting in high transaction fees. This naturally formed a barrier to creating and using hundreds or thousands of addresses, as that would cost a lot of money. But recently, crypto infrastructure has become more scalable - through L2 aggregation and new high-throughput L1s - which has reduced the cost of many transactions on blockchains to near-zero. But is the cost of creating multiple identities as close to zero in traditional internet applications? In most cases, it is. For example, it is quite easy for a person to create and use multiple email addresses. But the key difference is that in cryptocurrencies, this behavior is strongly incentivized. The crypto industry has a long history of rewarding early users of protocols with tokens. Nowadays, new protocols often launch their circulating token supply through "airdrops" - a reward activity that provides token incentives to a predefined set of addresses. Typically, these address lists are derived by backtracking historical on-chain transaction records. Some may try to game the system by creating many different identities and transacting with them. In the industry, this strategy is often referred to as "airdrop farming". Given these behaviors, it's clear that the 2.2 million unique monthly active addresses we measured in September 2024 do not directly translate to 2.2 million users. (Note that addresses active on multiple EVM chains are only counted once in the 2.2 million total.) So how many active users are there? 10 million? 50 million? 100 million? This is the question we set out to answer. Here is our research approach. Method #1: Filtering Active Addresses One approach we took was to filter out addresses that are suspected to be controlled by bots or Sybils. Through on-chain analysis and forensics, we explored various methods:

1. Filtering out addresses that received funds from decentralized contracts - decentralized contracts are a type of smart contract whose sole purpose is to receive funds and automatically distribute them to many different addresses. While there may be some false positives, this activity suggests the target addresses all received funds from a single source, and are therefore somewhat related.
2. Filtering out addresses with a near-zero balance at the start and end of a given time period. For example, if you're looking for real monthly active users in September 2024, you could try excluding addresses with near-zero balances on September 1st and September 30th. This criterion suggests these addresses are of a transient nature. While bots and Sybils may "clean up" their balances after taking action, real human users typically want to keep some balance in their wallets to pay for future transaction fees.
3. Analyzing the distribution of addresses with one, two, three, four, five or more transactions during that period. Addresses with only one or two transactions during that period can at most be considered low-quality users, with the worst case being that they are bots or Sybils. This method works best when aggregating over longer time periods.
4. Filtering out addresses with a very high number of transactions in a very short time. Humans using a wallet or app interface can reasonably only handle a certain number of transactions in a given time period, while bots can transact at a much higher frequency.
5. Optimistically including addresses associated with identity protocols that require a certain setup cost. For example, addresses with ENS names, Farcaster IDs, and other linked social identities may be real human users.

These are just some patterns that may indicate bot-like behavior on-chain. This is by no means an exhaustive list, and we welcome suggestions built upon the above. Method #2: Inferring from Wallet Users Another way to estimate monthly active users is to look at off-chain data sources. The most obvious starting point is wallet users. In February 2024, the popular crypto wallet MetaMask reported having 30 million monthly active users. They define monthly active users as "people who have loaded the MetaMask extension on a page or opened the mobile app at least once in any rolling 30-day period." Assuming we want to estimate transacting users, the next step is to determine what proportion of MetaMask's users actually perform on-chain transactions. In 2019, MetaMask reported that around 30% of their active users confirmed an on-chain transaction on a given day. (This is the latest available estimate.) Applying this ratio to the MAU, we would get around 9 million users transacting monthly through the MetaMask wallet product. Next, we need to understand MetaMask's total wallet market share across all blockchains. While the exact data on this is not easily available, we can make some reasonable guesses based on existing knowledge. For example, we can make a decent estimate of MetaMask's market share in mobile wallets based on data from mobile analytics firm Sensor Tower. (We cannot disclose specific numbers here due to business service agreements.) Once we have an estimate of MetaMask's market share, we can simply derive a total crypto user estimate from the previous 9 million monthly active transacting users figure. We can then compare this to the results from Method #1 to see if they at least fall within the same range. We can further refine our estimates by analyzing data from other wallets and infrastructure providers who are willing to share their proprietary metrics with us, and cross-validate against the above numbers. Other Considerations It's important to consider that some people use and transact through multiple addresses and wallets. This is unlikely to significantly inflate the user count (as opposed to bots and Sybils, the number of wallets a real individual can reasonably use is limited), but further deduplication based on some reasonable assumptions may be worthwhile. On the other hand, there are also cases where a single address can be associated with multiple real users. Exchange pooled accounts are one example. Incidentally, as account abstraction protocols and smart contract wallets become more prevalent, this will all become even more complex. We have not accounted for these factors in our analysis. Estimated Result: 30 million to 60 million real monthly transacting users Based on the analysis we've conducted using the various methods above, we estimate there are currently 30 million to 60 million real monthly active crypto users. This is clearly a wide range, but it's the best estimate we can make based on the available data. Note that this only accounts for 14% to 27% of the 220 million monthly active addresses we measured in September. It also only accounts for 5% to 10% of the 617 million global crypto holders reported by Crypto.com in June. (Global crypto holders refer to people who hold crypto but may not necessarily be active on-chain.) This disparity suggests a huge opportunity to convert the existing largely passive crypto holders into active on-chain users. As major infrastructure improves, enabling new and engaging applications and user experiences, the dormant crypto holders may re-emerge as active on-chain users.