Product analytics helps teams optimize digital products by tracking how users interact with them. Key metrics such as conversion, activation, and churn provide insights that drive better product decisions. Unfortunately, traditional product analytics cannot see onchain data, so you miss key insights around user acquisition, drop-off, and retention from the large chunk of a user's journey.
Web3 product analytics consolidates both onchain and offchain data to provide a complete picture of user behavior on onchain apps. In this article, you'll learn about Web3 product analytics, explore real-world use cases, and uncover best practices.
What is Web3 product analytics?
Web3 product analytics reveals how users interact with a dApp, providing more granular insights than traditional analytics tools such as Google Analytics. By tracking user actions (events) such as wallet connections and transactions within a dApp, Web3 teams can identify friction points, optimize user flows, and convert valuable users.
Analyzing Web3 user behavior helps product teams boost engagement and increase conversion rates — ultimately driving growth through a better user experience.
Key Metrics to Track with Product Analytics for Web3
Understanding user behavior helps you build a better product. Key metrics include:
Web3 Activation
Activation and conversion rates indicate how effectively users onboard and engage with key features. In Web3, it's important to track wallet events to understand how many of your users activate. Critical wallet events include connecting their wallets and executing their first onchain transaction.
Web3 Engagement
Session duration, number of sessions within a period, and bounce rate measures how engaged users are with your dapp. Monitor the number and value of transactions users perform, providing insights into user engagement.
Web3 Retention
Track the number of unique wallets interacting with your platform over specific periods (DAU, WAU, MAU) to assess user retention and churn. Identify areas for improvement while tracking positive and negative changes over time.
Web3 Customer LTV
Lifetime Value (LTV) measures your users' long-term revenue potential. The average value of tokens held or fees spent by users over time reflects their long-term value and engagement with your project.
Web3 Adoption
Feature adoption rates show how quickly users adopt new features and whether they find them valuable. Track adoption rates as your user base grows to make sure users consistently find value in your product. Qualitative feedback and customer sentiment across community platforms such as Discord and Telegram also reflects broader adoption and interest.
How Different Roles Use Web3 Product Analytics
Web3 Product Managers
Web3 product managers leverage product analytics to make informed, data-driven decisions on feature prioritization and roadmapping. Which features are popular and why?
Key metrics like feature adoption rate and conversion rate provide insights into user engagement, enabling managers to refine the product for accelerated adoption and improved user experience.
Web3 Product Marketers
Web3 marketers use retention rates, daily active users (DAU), and monthly active users (MAU) to measure the effectiveness of their marketing campaigns. Track the impact of marketing campaigns on onchain user activity. With data, you can ensure campaigns drive long-term repeat engagement instead of one-time interactions.
Web3 Developers and Engineers
Web3 developers and engineers can use funnel drop-off and cohort analysis to identify potential technical issues, such as bugs or performance bottlenecks, that may affect the user experience. When drop-off rates increase, something is usually wrong. By monitoring these metrics, you can fix technical flaws and enhance product performance.
Web3 UX/UI Designers
Web3 UX/UI and product designers track metrics such as onboarding completion rate and task completion rates to understand where users are struggling within your product. Improve the onboarding experience by addressing drop-off points, especially during wallet connection and transaction signing stages. Real-time data helps guide design improvements that create a more intuitive and seamless user experience.
Web3 Data Analysts
Web3 data and business analysts focus on business metrics such as customer LTV, average revenue per user, and conversion rate to assess overall dapp performance. You can use product analytics to make data-driven decisions for increasing revenue. You can also identify which user segments are the most valuable and identify the red-hot center of your target audience.
Web3 Customer Success
Web3 customer success teams track churn rate and renewal rate to understand customer satisfaction and identify at-risk users. These metrics guide proactive efforts to improve user retention and provide personalized support that activate dormant users. Identifying users at risk of leaving based on onchain activity (e.g., unbonding, unstaking, selling tokens) is an underrated retention strategy.
Web3 Growth Managers
Web3 growth managers track the activation rate and site bounce rate to gauge the effectiveness of user acquisition strategies. Monitoring these metrics helps you optimize the user journey and increase platform growth by reducing friction and improving conversion rates. Optimize Web3 growth loops by analyzing which incentives (KOLs, airdrops, referral rewards) lead to sustained platform usage.
Best Practices for Product Analytics in Web3
To integrate product analytics into your Web3 product strategy, follow these best practices:
1. Choose the Right Data Platform
Select a flexible, scalable product analytics platform that integrates seamlessly with your Web3 stack. It should track onchain events, user behavior, and engagement metrics out of the box. Formo enables non-technical teams to analyze web3 user flows, map journeys, and monitor end-user interactions onchain in real-time.
2. Build a Cross-Functional Team
Product analytics is a team effort. Ensure that product managers, developers, engineers, marketers, designers, and leadership are all aligned. This ensures everyone can access the data and collaborate on enhancing the entire product experience.
3. Define Key Metrics
Identify key metrics that align with Web3 goals, such as active users, retention, user activation, and feature adoption. Track your key metrics over time to make data-driven decisions on feature prioritization and improvements. Continuously analyze these metrics to identify trends, uncover pain points, and optimize user experiences. Leverage insights from the data to iterate on your product strategy, ensuring alignment with Web3 principles like decentralization, transparency, and community-driven growth.
4. Ensure Data Availability and Governance
As your product grows, manage your data catalog well. Maintain clean, documented, and accessible data. Break down data silos and ensure teams are using the same definitions and metrics for cross-functional alignment. Ensure your Web3 product data is accurate, secure, and compliant. Appoint a data governance owner to oversee data quality and integrity.
8 Web3 Product Analytics Use Cases
Traditional product analytics has been instrumental in tracking product launches, growth, and market fit in web2 apps. These same principles apply uniquely to Web3, helping founders and teams building onchain turn data into action. Here’s how product analytics empowers Web3 projects:
Web3 Product Launch Analytics
1. Defining Success Beyond Launch
Web3 projects, such as NFT marketplaces, often emphasize minting events or user acquisition at launch. However, focusing solely on these metrics can overlook long-term engagement and retention. Product analytics enables tracking of wallet interactions, repeat purchases, and activity frequency at all stages of a product, ensuring sustainable growth.
2. Optimizing the Web3 Launch Experience
For a DeFi protocol, tracking key steps in a user's journey such as staking, lending, and swapping is critical. Web3 analytics tools help identify friction points, such as failed wallet connections or reverting transactions, enabling teams to fix the user journey before scaling to more users.
Web3 Product Growth Analytics
3. Powering Product-Led Growth in Web3
Adopting a product-led growth strategy requires leveraging analytics to identify bottlenecks in decentralized applications (dApps). For example, if users face challenges with wallet connections or transaction execution, real-time data enables teams to refine onboarding processes and enhance user engagement.
4. Tracking Early Growth Signals
A Web3 dapp can utilize analytics to pinpoint popular features and key value moments for users. Understanding early growth signals helps teams prioritize resources, marketing efforts, and new feature development, accelerating adoption.
Turning Data into Actionable Insights
5. From Intuition-Driven to Data-Driven Decisions
Consider a dApp that launched its minimum viable product (MVP) based on a little market research and vague intuition. Despite high engagement at launch, you start to observe a decline in user engagement and activity. Product analytics revealed that a problematic onboarding step was the issue, allowing you to apply a targeted change to improve conversion rates to your desired level.
Web3 Product-Market Fit Analytics
6. Identifying Regional Adoption Trends
A project tracking user engagement by region may find that Southeast Asian users have higher retention and activity. With these insights, the company can tailor marketing efforts to maximize traction in high-performing segments.
7. Validating Fit in a Competitive Web3 Landscape
A dapp that rewards users for achievements can analyze task completion rates. If user engagement is low, the team can experiment with gamification and reward mechanisms to boost user adoption.
Maximizing Marketing ROI with Data Insights
8. Refining Market Strategies with Analytics:
A Web3 Network used product analytics to determine that their services were more appealing to game users than NFT users. By adjusting their marketing strategies, they were able to double their ROI.
Get Started with Web3 Product Analytics
Web3 Product analytics goes beyond simply tracking data; it focuses on gaining a deep understanding of user behavior, including what they enjoy and what they choose to avoid. By connecting insights throughout the entire user journey, Formo empowers Web3 teams to make data-driven decisions. With real-time analytics and no-code tools, both technical and non-technical teams can test, iterate, and optimize for product-led growth without compromising performance.
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