Web3 Product Analytics: A Guide for Product Managers
Building a successful Web3 product is a challenge. Building products without understanding user behaviour is like navigating a dark forest; you might feel like you’re moving, but the path is unclear. With product analytics, you illuminate that path, helping you reach your destination faster.
For Web3 product managers, traditional analytics tools often fall short. The decentralized and pseudonymous nature of Web3 necessitates a new approach to understanding user journeys, spanning from off-chain website visits to on-chain transactions. Flying blind isn’t an option when resources are at stake.
This guide provides a fundamental framework for Web3 product analytics. We'll explore how to define value, understand your users, analyse engagement, improve retention, and drive growth using onchain analytics. We will also cover the unique challenges and tools available for dapp analytics, equipping you to make data-driven decisions for your onchain app.
What is Web3 Product Analytics?
Web3 product analytics is the process of collecting and analysing behavioural data to understand how users interact with decentralised applications (dapps) and protocols. It moves beyond traditional web analytics by unifying off-chain data (like website visits and clicks) with on-chain data (such as wallet connections, transactions, and smart contract interactions). This unified view is critical for building a complete picture of the user journey.
Web3 product analytics helps teams answer critical questions about user behavior and optimize their dapps and protocols effectively. By leveraging Funnels, you can answer pressing questions about the state of your app:
What percentage of users completed a transaction flow on my protocol within 7 days?
At what step in the staking or swapping process do most users drop off?
How did my smart contract update impact conversions in the token swap process?
How has the deposit funnel conversion rate for European users changed over time?
How long does it take most users to complete the lending or borrowing process on the platform?
What user segments (e.g., NFT traders or DeFi investors) are most likely to complete the desired actions?
What paths do users typically take between connecting their wallet and executing a transaction?
What paths do users take when they abandon the process entirely? How do these patterns differ?
What specific actions should be encouraged (e.g., staking, bridging) or discouraged to improve conversions?
What alternative actions do users take after they drop off from a critical flow?
By answering these types of questions, teams can refine user journeys, enhance feature adoption, and ensure their onchain applications drive measurable growth.
While Web2 analytics tools can track website interactions, they miss the crucial wallet activity that defines Web3. On the other hand, on-chain explorers lack the context of the user's journey leading up to a transaction. Platforms like Formo are designed to bridge this gap, offering a single platform to see how off-chain marketing efforts translate into on-chain actions.
Challenges in Web3 Product Analytics
Product teams seeking to set up product analytics in Web3 face a unique set of challenges:
Pseudonymity: Wallet addresses are not tied to real-world identities, making it difficult to build a holistic user profile. Tools like Formo's Wallet Profiles help turn pseudonymous wallets into actionable on-chain personas.
Data Silos: Data is often split between off-chain web servers and on-chain blockchains. Unifying this data is essential for a complete picture.
Complexity: Understanding smart contract interactions requires technical expertise. Platforms that decode and present this data in a readable format are invaluable.
How to Collect Product Analytics
Before you can analyse data, you need a system to collect it. The most common approach is to use an event analytics tool by installing an event tracking SDK in your application. Tools like the Formo automatically capture events, interactions, and attribution data once installed.
When a user performs an action—like a click, page view, or transaction—a trigger collects event data, including the action type, timestamp, and user environment. This data is sent to an analytics database for analysis. Before you start, define your goals. Are you trying to increase conversions, improve feature adoption, or reduce churn? Clear objectives will help you focus on tracking the right metrics.
Measuring Product Value
At the core of every successful product is the value it provides. As the team at Mixpanel puts it, if customers find value, they use your product; if they don’t, they leave. Your first job in product analytics is to define and measure that value.
What is a "Value Moment"?
A "value moment" is the key action a user takes that shows they've experienced your product's core benefit. It’s the "aha!" moment where your product's purpose clicks for them. Identifying this is key to building a lasting product.
Examples of value moments in Web3 include:
Completing a swap on a decentralised exchange (DEX).
Minting an NFT from a new collection.
Staking tokens in a DeFi protocol.
To pinpoint your value moment, ask yourself: what problem are users trying to solve with my product? What action best represents the solution?
Which Metrics Should I Pick?
Once you’ve identified your value moment, you can define a "North Star Metric"—a single metric that captures the core value your product delivers to customers. This metric becomes your team's objective barometer for success, aligning everyone on a common goal. Instead of asking "what should I build next?", you can ask, "what feature is most likely to move this metric?"
Key metrics for Web3 dapps often include:
Transaction Volume: The total value of transactions processed by your protocol.
Total Value Locked (TVL): The total value of assets deposited in your protocol smart contracts.
Number of Unique Active Wallets: The number of distinct wallets interacting with your dapp.
Smart Contract Calls: The frequency of calls to your key smart contracts.
Protocol Fees Generated: The total fees paid by users interacting with your protocol.
Getting to Know Your Users
Understanding who your users are is the next step. In Web3, this means looking at both off-chain behaviour and on-chain identities.
What is User Segmentation?
User segmentation is the practice of grouping users based on shared attributes to better understand their behaviour. As noted in a Hightouch blog on audience analysis, this allows for more targeted analysis and personalised experiences. In Web3, you can segment users by:
On-chain data: Wallet balance, tokens held, transaction history, or DeFi positions.
Off-chain data: Geographic location, device type, or referral source.
What are DAU/WAU/MAU?
Daily Active Users (DAU), Weekly Active Users (WAU), and Monthly Active Users (MAU) are standard metrics for measuring user activity. However, in Web3, defining "active" is critical. Is an active user someone who simply visits your site, connects their wallet, or must they complete an on-chain transaction?
As Mixpanel's guide suggests, the best definition of "active" is tied to your value moment. An active user is someone who experiences your product's core value. Tools like Formo allow you to define this key event and automatically track your DAU, WAU, and MAU based on meaningful interactions.
Analysing User Engagement
Once you know who your users are, you need to understand how they engage with your product.
What is my Product Usage Interval?
Your product's usage interval is the natural frequency at which users interact with it. A Web3 game might expect daily engagement, while a portfolio management tool might see weekly or monthly use. Determining this interval helps you set realistic engagement targets.
Who are my Power, Core, and Casual Users?
You can segment users by their level of engagement to identify different user types:
Power Users (90th percentile): Your most active and engaged users. They might be the top 10% in terms of transaction volume or frequency.
Core Users (50th percentile): The median users who engage regularly.
Casual Users (25th percentile): Users who interact with your product infrequently.
Platforms like Formo automate this by applying labels like "Power User" or "DeFi Degen," helping you quickly identify your most important user segments.
Tracking the User Lifecycle
It's also essential to track where users are in their journey. Using cohort analysis, you can group users into four main lifecycle stages:
New: Users who interacted with your product for the first time within a specific period.
Retained: Users who were active in a previous period and returned in the current one.
Resurrected: Users who were dormant for a period but have now returned.
Dormant: Users who were previously active but have not returned in the current period.
Tracking the flow of users between these states provides deep insights into your product's health and stickiness.
Retaining Your Users
High user retention is a clear sign of a successful and valuable product. It's often more important for long-term growth than pure user acquisition.
Where are my Users Dropping Off?
Funnel analysis is a powerful technique for mapping the user journey and identifying where users are dropping off and abandoning your product. A typical Web3 funnel might look like this:
Visit landing page.
Connect wallet.
Initiate transaction.
Confirm transaction in wallet.
Transaction successful.
By visualising this flow, you can pinpoint the biggest drop-off points and focus your efforts on improving those steps. Features like Funnels and User Flows in Formo are designed specifically for Web3 product teams.
How do I Measure Retention?
There are two common methods for measuring retention:
N-Day Retention: Calculates the percentage of users who return on a specific day after their first interaction.
Unbounded Retention: Calculates the percentage of users who return on a specific day or any day after.
For example, you might ask, "What percentage of users who made their first transaction in week 1 returned to make another transaction in week 2?" This data shows which customer cohorts are most likely to stay, helping you understand what drives long-term value.
Driving Growth and Scale
True growth isn't just about acquiring new users; it's about acquiring and retaining valuable users.
Where are my Most Valuable Users Coming From?
On-chain attribution is key to understanding which marketing channels are most effective. By using UTM parameters and tracking referrer data, tools like Formo can show you whether your most valuable users are coming from a specific Twitter campaign, a partner link, or an organic search. This allows you to double down on what works and optimise your marketing spend.
How can a Product Manager Drive Growth?
The key to sustainable growth is retention. Understand what your retained users do and then guide new users to form those same habits. Identify the actions that correlate with long-term retention and build onboarding flows or features that encourage new users to perform those actions early in their journey.
Use Cases of Web3 Product Analytics
Product analytics allows teams building onchain apps and DeFi protocols to deeply understand user behavior. By leveraging these insights, teams can perform various analyses to optimize their product offerings, enhance user engagement, and drive growth.
A/B Testing
A/B testing enables you to experiment with two variations of a feature, element, or user flow to determine which delivers the best results. For web3 teams, this could mean testing different onboarding processes to reduce friction for first-time wallet connections. For instance, simplifying a cross-chain bridging UX could be tested to see which option results in higher transaction completion rates and user satisfaction.
Feature Usage
Tracking feature usage helps uncover which tools or functionalities are most valuable to your users. For example, a DeFi protocol might focus on analyzing the usage of advanced trading features, such as limit orders or automated strategies, to determine where to prioritize development efforts. Understanding this enables teams to refine the key elements that drive transaction volume and user retention.
Feature Adoption
Feature adoption analysis helps identify patterns that encourage users to engage with and stay loyal to a new feature. Say your platform introduces a staking feature – monitoring how users adopt this feature can inform targeted campaigns or educational content to drive engagement, ensuring users see the value of newly implemented utilities.
Conversion Analysis
Conversion analysis allows you to pinpoint where users drop off during critical actions, such as connecting a wallet or initiating a swap. For instance, if users are abandoning the process due to complex gas fee calibration, simplifying these pain points can improve conversions and ensure users seamlessly complete transactions.
Churn Analysis
Churn analysis examines why users might stop interacting with your product or protocol. If your analytics highlight a drop in retaining liquidity providers, you can proactively address the issue by offering improved reward structures or implementing better educational tools for new users.
Audience Analysis
Audience analysis enables segmentation of users based on criteria such as transaction behaviors or preferred blockchains. For example, identifying that most of your high-value users are favoring one EVM-compatible chain could help tailor your marketing efforts and product focus toward that specific chain for enhanced growth.
Attribution Analysis
Understanding how users discover and engage with your protocol is crucial for growth. Attribution analysis allows you to track the effectiveness of your acquisition channels, such as DeFi partnerships, ecosystem campaigns, or token incentives. For instance, measuring whether user acquisition spikes are driven by direct wallet integrations versus community events can help optimize marketing spending and partnerships.
By leveraging product analytics, onchain builders can unlock valuable insights and drive growth in less time with data.
Web3 Product Analytics Tools
Effectively analyzing product data in web3 requires a combination of specialized tools tailored to the unique needs of onchain builders. Here are some key tools that can empower web3 product and marketing teams to measure, analyze, and grow effectively:
Formo
Formo is a data platform designed onchain apps and crypto teams. It unifies web, product, and on-chain analytics into a single dashboard, enabling teams to gain clarity through wallet intelligence and attribution. By combining onchain data with product analytics, Formo provides a holistic view of user behavior, enabling you to build products users want without guesswork.
Mixpanel/Amplitude
These popular Web2 analytics tools excel at off-chain product analysis, helping teams measure user engagement, retention, and conversions. However, they require additional upfront investment from engineering and data tems for it to work for Web3 apps and protocols. When integrated with onchain data sources, Mixpanel and Amplitude can play a complementary role in providing deeper insights into how users interact with interfaces before moving on-chain.
Google Analytics
Though primarily a Web2 tool, Google Analytics remains a valuable resource for tracking website interactions leading up to the on-chain user journey. It allows teams to understand traffic sources, user demographics, and behavior on landing pages, which can inform web3 marketing teams responsible for Top-of-the-Funnel growth.
By leveraging these tools in combination, web3 teams can achieve a more holistic view of their products, marrying on-chain and off-chain insights for informed decision-making.
Summary
Web3 product analytics is essential for any product team aiming for sustainable growth. The key is to unify off-chain and on-chain data to understand the complete user journey, from the first click to the final transaction.
Start by defining your product's value moment and identifying the North Star Metric that will guide your team. Then, begin tracking it. By segmenting users, analysing engagement funnels, and focusing on retention, you can build a product that users truly value.
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Frequently Asked Questions
What is the difference between Web2 and Web3 product analytics?
Web2 analytics primarily focus on user interactions within a traditional website or app, tracking metrics like page views, clicks, and session duration. Web3 product analytics extends this by integrating on-chain data, such as wallet transactions, token holdings, and smart contract interactions, to provide a complete view of the user journey across both off-chain and on-chain environments.
How do you track user retention in a DeFi protocol?
To track retention in a DeFi protocol, you first define a key retention event, which is typically tied to your value moment (e.g., making a swap, providing liquidity, or staking). You then use cohort analysis to measure what percentage of users who perform this action in a given period (e.g., week 1) return to perform it again in a subsequent period (e.g., week 2, week 3, etc.).
What are the most important web3 product metrics for a new dapp?
For a new dapp, the most important metrics are those that validate your core value proposition and product-market fit. These often include:
Number of Unique Active Wallets: Measures how well you are attracting and acquiring users.
Value Moment Conversion Rate: Measures how many users are reaching your "aha!" moment.
User Retention Rate (Week on Week): Indicates if users find enough value to return.
Revenue and Volume: Validates that users are ready and willing to use your DeFi protocol.
What are the best ways to improve user retention for a dapp?
Improving user retention starts with understanding why users disengage. Begin by analyzing user behavior through analytics tools to identify drop-off points. Focus on creating a seamless and engaging onboarding process, simplifying transaction steps, and providing regular value through personalized notifications or rewards. Additionally, user segmentation allows for targeting specific groups with tailored features or offers that resonate with their needs and usage patterns.
How can I measure the success of my marketing campaigns for a dapp?
To measure marketing success, track metrics such as user acquisition cost (CAC), conversion rates from campaigns, and the growth in Unique Active Wallets (DAU, WAU, MAU) driven by those campaigns. Employ A/B testing to refine messaging and test calls to action. A web3 marketing analytics platform can also provide insights into user behavior post-acquisition, such as retention rates and transaction volume, linking campaign success to actual engagement and usage.
