In the traditional Web2 world, startups rely on tools like Segment, GA, Mixpanel, Amplitude, and June to make data-driven product decisions. Typically you would connect an app to these APIs, set up events, and can make detailed analysis of users and user behavior. From these Web2 events configured on your platform, you can learn plenty of interesting things about your users, such as DAUs/WAUs/MAUs, retention, engagement time, and more.
Imagine for a second that you could track your Web2 users across Facebook, Instagram, TikTok, etc. What if you could monitor their bank balance, see their transactions, and track who they send money to? Surely this would be incredibly helpful in making product decisions, but in Web2, this would require an impossible level of communication between platforms, not to mention it would violate hundreds of security and privacy laws.
Decentralized apps have the unprecendented opportunity to track users with an extraordinary level of detail.
Web3 Analytics vs. Web2 Analytics
In Web3, users connect their crypto wallets to platforms for anonymity and privacy. Even some Web2 companies like Nansen have enabled SIWE (Sign in with Ethereum). However, because these users are connecting on-chain wallets, and blockchain is a public ledger, it is possible to monitor a user’s balance, transactions, and interactions with other on-chain contracts, among hundreds of other detailed metrics.
In other words, Web3 companies or Web3-enabled have an unheard-of ability to analyze users even when they aren’t directly interacting with their platform. These metrics can provide an unparalleled level of insight into user behavior, offering companies a valuable tool for making informed product decisions.
How can you use Web3 product analytics?
Web3 companies can use this data to create smart strategies, such as dynamic pricing or tailored promotions, to increase user engagement and retention. Additionally, you can use this data to create more accurate user segmentation and target specific user groups. This will enable you to create more effective and tailored user experiences. These are just two of many ways you can utilize Web3 product analytics for making product decisions. We’ve included a full list down below of other popular ideas:
- Dynamic pricing based on user-cohorts
- Competitive analysis of other on-chain platforms
- Micro-targeted campaigns and promotions
- A/B and multivariate testing based on on-chain properties
- Advanced cohort analysis
- Cross-platform user behavior analysis
- Accurate user segmentation and personalization
- Optimizing user journeys and flows
- Measuring user loyalty and retention
- Analyses of long-term user properties, such as aggregate balance over time
How can Multibase help?
While the data available on-chain is incredibly detailed, it can be very difficult to query. We have built an easy-to-use blockchain querying platform oriented around dapp analytics. Here are some ways you can use Multibase to make product decisions:
Time-based Queries
Our simplest method of querying is time-based queries. Pick any on-chain metric you’d like (tx count, balance in USD, balance in some token), and visualize that metric over time. Below is an example of a balance USD query over the last 3 days.
Wallet Property Queries
Our wallet-property queries allow you to query any property associated with a wallet. This includes properties from the wallet itself (e.g. balance) or any property associated with the wallet's transactions (e.g. transaction fees, ETH sent).
Cohort Analysis
Our cohort analysis is used to compare user behavior across various groups, or cohorts. In Web3, cohort analysis can be used to segment users by balance, transaction volume, transaction count, and more. You can specify time ranges with very detailed parameters. For example, give me wallets with more than 100 transactions with at least $100 value per transaction. Below, we’ve included a screenshot querying users with Balance of USDC coin above $100 since Jan 17, 2023.
