Public blockchains – distributed, decentralized databases that anyone can access – are a key building block of Web3. Unlike the guarded databases of Web2 platforms, transactions recorded on-chain can be read forever, by anyone. Wallets, the conduit for that data, represent a user’s Web3 identity. They safeguard a user’s digital asset holdings and transaction history, maintaining a perfect record of their owners’ on-chain activities.
Web2 cookies are short-term records of user behavior, stored on a user’s device, that are typically accessed by the site that left the cookie (and sometimes partners). Web3 wallet data, on the other hand, is left permanently on-chain and can be accessed by anyone. Wallets offer two unique benefits that greatly expand what’s possible from an analytics perspective – on-chain data is publicly available to everyone, rather than confined to the parties involved in a given transaction, and it’s forever tied to a unique wallet identifier.
This open data ecosystem that wallets make possible gives Web3 builders a more comprehensive line-of-sight into user preferences and behavior. It also presents them with novel opportunities for benchmarking against competitors and pursuing hyper-targeted growth.
In explaining the Web2 → Web3 data comparison, Tomasz Tunguz writes that “when the cookie does crumble, it will be replaced by a wallet.” Let’s discuss how on-chain data is transforming the analytics landscape.
On-chain data can be used to target and acquire new users based on wallet holdings and transaction histories.
Transaction data and asset holdings can directly indicate a user’s Web3 community memberships, interests, experience level, and more. Builders can analyze this data to identify the subset of wallets most likely to adopt their product.
Building a fantasy sports game? Target wallets that have been active on Sorare, purchased items from NBA Top Shot, or own NFTs from athlete-affiliated collections. Bonus points if they bought into WAGMI United, the Web3 community that acquired an English Soccer team.
In general, on-chain data can answer the following questions about users:
Once identified, wallets can be targeted through airdrops, marketing campaigns, and partnerships. Partnerships and cross-community collaborations are a particularly effective user acquisition strategy in Web3. Pre-mint, companies can pursue partnerships to cultivate their initial user base; post-mint, they can use these targeted collaborations to drive utility for existing holders. On-chain data makes it much easier for builders to identify communities with the most overlap amongst their existing user base and pursue partnerships accordingly.
On-chain data can be used to tailor experiences towards users’ demonstrated preferences.
In Web2, companies must launch their products and collect usage data before they can begin tailoring experiences to their users’ preferences. In Web3, companies can acquire users through an initial airdrop or NFT sale and study their wallet data to begin tailoring the experience for users before writing a single line of code.
Builders can use this on-chain, off-platform data to recognize their users’ engagement patterns and inform their optimal strategy for retention. This can help answer questions, such as:
In Web2, it’s typically impossible to track a user’s engagement history across independently-owned entities. In Web3, on-chain data reveals which wallets are engaging with which products, and when. Projects can use this to see when their users are active on-chain, or interacting with competitors, and use this to know when to nudge users back to their product.
On-chain data can be used for R&D and benchmarking.
On-chain data reveals which other communities have traction with a target audience, and researching those communities can reveal what has effectively engaged a specific set of users. Builders can research these successful communities to:
Builders can also utilize on-chain data to benchmark their activity against related communities. This practice can help companies contextualize their success while suggesting areas that need improvement. For example, builders can look at transactions per user, social media engagement, and the percentage of a user base that participates in DAO votes.
On-chain data is clearly a novel resource for crafting target audiences – but reaching those audiences can be difficult. Many experienced users have multiple wallets for different purposes, making it harder to consolidate their complete transaction history into a single pipeline. Further, connecting wallets to audiences that can be reached via outreach or marketing can be impossible without sophisticated data analysis.
However, it’s clear that on-chain data creates new opportunities for user and audience identification, in addition to helping builders recognize overlapping networks and benchmark their traction against related communities. This information exists for all wallets, and tools like Kazm make it accessible to Web3 projects across the ecosystem.
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