On The Limitations of Web 3 Data
Data is the new oil and right now there is an arms race in Web 3 to build the best marketing tech stack that leverages the information on the blockchain. There are several players competing in this space already. Dune Analytics, Helika, and Sesame Labs are some of the names that come to mind. In fact, we see new Web 3 data brokers emerge regularly each with its own unique way of analyzing and presenting quantifiable metrics. However, there is a fundamental problem with Web 3 data that will prove to be a hurdle for even the most seasoned marketers.
The reason there are so many emerging data analytics companies is simple, the blockchain offers open access to data. By analyzing wallet activity, we can understand a lot of things about a user.
For example:
✅ We can tell who the whales are.
✅ We can determine who are the day traders.
✅ We can even distinguish true believers from the ROIBOI.
While this information can tell us a lot about the audience we want to target, there is a limitation to this dataset. Even with nuanced wallet information, we still lack some of the most fundamental data points about a given user.
This includes:
✅ Age
✅ Gender
✅ Location
(AGL)
Although (AGL) data points are practically a given in Web 2, a lot of this information is non-existent in Web 3 by design and poses a serious challenge for marketers.
After all, how are you going to craft a compelling marketing strategy when you don’t know how old your audience is or what language they speak?
If you are creating an NFT collection directed at female buyers, how are you going to determine your total addressable market?
There are two potential solutions here:
The first solution involves scraping Twitter to associate ENS domains to specific wallets in order to ascertain some data points about users that could include (AGL). However, this solution would only account for the small subset of users with ENS domains and the data is incomplete at best.
The second solution involves some kind of an opt-in system where users are asked to sign up and link their wallets with Twitter or Discord. This is usually effective when there is a reward incentive for the user to link said platforms to their wallet.
Think allow list campaigns or redemptions for being part of a Web3 community.
By linking a wallet with Twitter, and Discord, we have a more complete picture of the potential user in question however, since this solution is opt-in, there are inherent limitations to this information outside the already engaged userbase.
Blockchain was designed from the outset with the aim to preserve anonymity and sensitive user data. However, the open nature of the blockchain makes it a potential goldmine. That said, we will have a truly complete user profile once we are able to adequately combine traditional Web 2 (AGL) data with Web 3 wallet activity.
The first Web 3 data analytics platform to achieve this will be the dominant data broker for our industry.
As always, thank you for reading.
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