For Web3 projects, user acquisition costs are high and retention is low. Too many teams are lost in the dark, unable to answer basic questions like "Where do my users come from?" or "Why do they leave?" To build a product that lasts, you need to understand your users. This is where product analytics and Web3 cohort analysis come in.
This post will show you how to analyze key user groups—new, retained, dormant, and resurrected—using Web3 cohort analysis. With a tool like Formo, you can turn these insights into growth.
Understanding User Groups with Web3 Cohort Analysis
You can't treat all users the same. By segmenting them into groups, you can understand their unique behaviors and needs.
New Users
New users are interacting with your dApp for the first time. It's critical to track their first actions and onboarding completion rate.
What to analyze: Which acquisition channels bring in the most valuable new users? Use onchain attribution to see which campaigns drive the most onchain activity and deliver the best ROI.
Retained Users
Retained users consistently return to your app. These are your most valuable users, and understanding what keeps them engaged is the key to growth.
What to analyze: What are the "sticky" features that keep users coming back? Use user segmentation in Formo to analyze the behavior of these power users and identify the onchain actions that correlate with long-term retention.
Dormant Users
Dormant users were once active but have stopped interacting with your dApp. Identifying why they left is the first step to winning them back.
What to analyze: Where do users drop off? Analyze the user journey to find common friction points that cause users to go inactive.
Resurrected Users
Resurrected users are previously dormant users who have returned. Their comeback offers a valuable learning opportunity.
What to analyze: What brought them back? Was it a new feature, a re-engagement campaign, or something else? Use user segmentation to identify what works and create targeted campaigns to reactivate more dormant users.
Why Product Analytics in Web3 Matters
Traditional analytics tools like Google Analytics can't see onchain data, leaving you with an incomplete picture of the user journey. High user acquisition costs and low retention rates are major challenges, and without the right data, marketing spend is often wasted.
Product analytics helps you connect the dots. By unifying offchain and onchain data, Web3 cohort analysis allows you to map the entire user journey, from the first ad click to the final onchain transaction. This is how you find out what makes users stick around. Formo is built for this, unifying your data to give you a complete view of user behavior.
How to Simplify Cohort Analysis with Formo
Formo is a product analytics platform built for onchain teams. It makes Web3 cohort analysis simple, so you can focus on growing your user base.
Here's how Formo helps:
Onchain Attribution: See which marketing efforts bring in high-value users and measure the ROI of your campaigns.
Wallet Intelligence: Turn anonymous wallets into user profiles. Understand who your users are by unifying offchain and onchain data.
Unified Data: Get a complete view of the user journey by combining data from all your sources.
User Segmentation: Easily create and analyze cohorts like "new," "retained," and "dormant" to understand their behavior.
To build a successful Web3 product, you need to know your users. Web3 analytics gives you the insights to do just that. Analyzing new, retained, resurrected, and dormant users is the key to improving retention and achieving sustainable growth.
Ready to get started? Use Formo to begin your own Web3 cohort analysis and see what your data is telling you.
FAQs
What is Web3 cohort analysis and how does it differ from Web2?
Web3 cohort analysis groups users by when they first interacted with your app. You can then track their behavior over time. This helps you understand how product changes or marketing efforts affect user actions. The main difference from Web2 is the data source. Instead of relying on cookies or device IDs, Web3 cohort analysis uses wallet addresses as the primary user identifier. This approach uses on-chain analytics to measure user activity, providing a direct view of how users engage with your protocol and its smart contracts. This allows product analytics to be grounded in actual on-chain events.
How do you define user segments like new, retained, and dormant users with wallet activity?
Defining user segments with on-chain data relies on tracking wallet interactions over specific time periods. These definitions help you measure growth and retention accurately.
New Users: Wallets interacting with your dApp for the very first time within a defined period (e.g., this week).
Retained Users: Wallets that were active in a previous period and are still active in the current one.
Resurrected Users: Wallets that were previously active, became dormant, and then returned to interact with your app in the current period.
Dormant Users: Wallets that were active in a previous period but have not shown any activity in the current one.
What are the best practices for conducting Web3 cohort analysis?
For effective Web3 cohort analysis, it's best to combine on-chain and off-chain signals. Start by identifying the key on-chain actions that define an "active" user for your dApp, such as a swap, stake, or vote. Use product analytics tools that can pull this on-chain data. Then, enrich this with off-chain data from sources like your website, social channels, or community platforms. This gives you a full picture of the user journey. The goal is to see how off-chain engagement converts to on-chain value. This unified view helps you understand user behavior and measure the true impact of your product decisions.
