Web3 user behavior doesn’t follow the clean funnels we know from Web2. Instead, journeys are messy multi-step flows that span both offchain and onchain. Path Analytics helps you visualize and analyze the exact paths users take through your product or dApp — step by step, click by click, transaction by transaction. Instead of assuming what power users do differently, you can track it. This article will break down what Path Analytics is, why it matters for Web3, and how to use it to unlock growth.
Key Takeaways
Path Analytics maps out the real journeys wallets take in your dApp — across clicks, transactions, and onchain actions.
Path Analytics helps you spot drop-offs, loops, and hidden friction points that basic metrics can’t show.
By analyzing top-performing user paths, you can design better onboarding and retention strategies that guide more users toward becoming power users.
Formo makes Path Analytics simple by unifying frontend and onchain data into one clear view.
What is Path Analytics?
Path Analytics is the process of tracking and analyzing the sequences of actions users take inside your product. Instead of looking at isolated metrics, it shows you the exact journey users follow step by step. Think of it as a map of user behavior. Every action is recorded in order, so you can discover common paths, hidden drop-offs, and unexpected flows.
Example paths:
60% of users: connect wallet → explore → drop off
20% of users: connect wallet → explore → transactions
5% of users: connect wallet → explore → transactions → share on social media
By visualizing these journeys, teams can identify which flows drive the most engagement and where users abandon the process.
Why Path Analytics Matters in Web3
A wallet connection does not always mean commitment, and a single transaction does not guarantee long-term engagement. One user may connect their wallet but never sign a transaction. Another may mint an NFT but fail to return for staking. Others may loop through your dApp multiple times before finally committing to an action.
This complexity makes it difficult to understand behavior using vanity metrics alone. Path Analytics solves this problem by revealing the exact journeys wallets take across both your frontend and onchain environments.
Key benefits of Path Analytics in Web3 include:
Finding drop-off points: Path Analytics highlights where most users stop, such as connecting a wallet but failing to proceed to signing or abandoning the process after a swap.
Identifying top user journeys: Teams can uncover which flows lead to meaningful actions like staking, governance participation, or repeat transactions, and use those insights to optimize product design.
Comparing new and power users: By mapping differences in behavior, you can see how casual users interact versus how loyal or high-value wallets engage.
Testing feature adoption: When new features such as staking, bridging, or governance are introduced, Path Analytics shows whether these steps naturally integrate into user journeys or create friction.
The real advantage of Path Analytics is that it shows the sequence of behaviors that drive either growth or abandonment, giving product and growth teams a more actionable view of user intent.
How Path Analytics Works
Path Analytics is built on the principle of sequencing user actions. Instead of analyzing events in isolation, it examines the order in which they occur to reveal patterns and behaviors.
The process typically involves four stages:
Defining events
Teams first determine the critical actions to track. In Web3, these may include wallet connections, swaps, NFT mints, staking, transactions, or claims.Tracking event sequences
Once defined, these actions are tracked in the exact order they occur for each wallet or user session. This builds a complete record of how individual users navigate through the product.Visualizing paths
The recorded sequences are then displayed in visual formats such as trees, funnels, or Sankey diagrams. This makes it easier to identify common flows, abandoned processes, or alternative user journeys.Analyzing drop-offs and loops
Finally, teams analyze where users exit, repeat, or stall in their journeys. For example, you may find a large percentage of users loop between connecting and disconnecting wallets before ever signing a transaction.
In the Web3 context, Path Analytics requires combining two data sources:
Frontend event tracking: Actions within the interface, such as button clicks, screen navigation, or form completions.
Onchain event data: onchain activities such as contract interactions, token swaps, NFT mints, staking transactions, and DAO votes.
When these are integrated, the result is a full picture of the user journey, showing both offchain interactions and onchain commitments. This unified view allows teams to connect product experience with blockchain activity, a critical capability for growth in Web3.
Example: Path Analytics in an NFT Minting dApp
Imagine you are running an NFT minting dApp. At first glance, your analytics might only tell you how many wallets connected or how many NFTs were minted. But with Path Analytics, you can see the entire journey that wallets take.
For example:
40% of users: Connect wallet → Browse NFTs → Drop off
30% of users: Connect wallet → Mint NFT → Stake NFT
5% of users: Connect wallet → Mint NFT → Stake NFT → Vote in DAO → Buy more NFTs
The last group represents your power users. Even though they make up a small percentage, they are the wallets most engaged with your ecosystem. By identifying this path, you can design your product to encourage more users toward it. For instance:
Add clearer calls-to-action that guide users from minting to staking.
Highlight the benefits of staking or governance to motivate action.
Key Path Analytics Metrics to Track
When running Path Analytics, some of the most valuable metrics include:
Top paths: The most common sequences of actions taken by users.
Average steps per session: A measure of how deeply users explore versus how quickly they exit.
Loops and repeats: Patterns where users circle back to the same action multiple times before progressing.
Drop-off rate per step: Identifies where the highest percentage of users leave the flow.
Conversion paths: Shows which paths lead to your core success metric, such as a completed mint, a staking action, or a DAO vote.
By combining these metrics, you gain both a macro and micro view of user journeys—what’s popular, what’s failing, and what drives true value.
Path Analytics vs. Funnel Analytics
Path Analytics is important to distinguish between these two related approaches:
Funnel Analytics: Best for structured, linear flows. For example:
Wallet Connect → Sign → Mint → Stake. This method works well when you want to test a predefined journey or measure performance against a known conversion flow.Path Analytics: Best for open-ended discovery. Instead of assuming a linear process, you let users show you their paths. This often reveals unexpected behaviors or hidden friction points.
In Web3, the most effective teams use both approaches together. Funnels are used to test hypotheses and measure improvements in well-defined flows, while paths are used to uncover organic behaviors that teams might never have anticipated.
Best Practices for Path Analytics in Web3
To get the most value from Path Analytics, teams should go beyond vanity tracking and focus on building a complete picture of wallet behavior. Here are some proven best practices:
1. Unify onchain and offchain events
Do not just track button clicks or page views. In Web3, real intent is often shown onchain. That means you need to capture both sides: interface actions (wallet connect, browse, sign attempt) and smart contract interactions (mints, swaps, staking transactions, etc).
2. Segment by wallet cohorts
By segmenting into cohorts such as whales, new wallets, and active contributors, you can uncover meaningful differences in behavior and tailor your product strategies accordingly.
3. Look beyond the first session
User journeys in Web3 often stretch over days or even weeks. A wallet may connect today, mint tomorrow, and stake next week. Path Analytics should account for these longer timelines instead of focusing only on single-session flows.
4. Highlight power-user paths
Your most valuable wallets are the ones that stake, vote, and return regularly. By identifying the paths they take, you can design onboarding and engagement strategies that guide more casual users toward these behaviors.
5. Experiment with nudges
Insights from Path Analytics should translate into action. Use reminders, in-app notifications, or contextual calls-to-action to encourage users to take the next step in their journey and reduce drop-offs.
How Formo Makes Path Analytics Easy
Most analytics tools were designed to track clicks and screens well, but they were never built for wallets, contracts, or cross-chain activity. Formo is a Web3-native analytics platform designed to unlock Path Analytics for dApps.
With Formo, you can:
Track both frontend events and smart contract interactions in one place.
Visualize complete user journeys across dApps and chains.
Segment wallets by profile, balances, and onchain activity.
Discover drop-offs, loops, and top-performing flows in a single dashboard.
Formo gives you the clarity to finally see:
How wallets move through your product.
Where they stop or churn.
What your best users do differently—and how to nudge others to follow the same path.
Path analytics turns complex user journeys into clear maps, giving your team the visibility to refine onboarding, optimize retention, and scale impact. With the right web3 analytics in place, you can transform blind spots into growth levers — spotting friction before it costs you users and doubling down on what drives conversions.
At Formo, we make it simple to bring this clarity into your product. Whether it’s tracking wallet connections, dApp interactions, or full user flows, you get the insights you need to grow with confidence.
Read more:
Web3 Funnel Analytics: Optimize Your User Journeys for Growth
Customer Journey Analytics: the ultimate guide for beginners
Follow Formo on LinkedIn and Twitter, and join our community to learn how you can turbocharge growth onchain!
Additional FAQs
1. What is Path Analytics in Web3?
Path Analytics in Web3 is the process of mapping and analyzing the exact sequence of actions a user (wallet) takes inside your dApp. This could include connecting a wallet, signing transactions, minting NFTs, staking tokens, or participating in governance votes. Unlike single-event tracking, Path Analytics gives you a step-by-step view of the entire journey, helping you identify smooth user flows as well as friction points that cause drop-offs.
2. How is Path Analytics different from Funnel Analytics?
Funnel Analytics assumes a fixed, linear journey (e.g., connect wallet → mint → stake). It’s best for measuring how well-structured processes convert.
Path Analytics is more open-ended. It uncovers the real journeys users take — including loops, skipped steps, drop-offs, and unexpected paths.
In Web3, both matter: funnels are great for validation (testing if a flow works), while paths are crucial for discovery (revealing how users behave).
3. Why does Path Analytics matter for Web3 teams?
Web3 user behavior is unpredictable:
A wallet connection doesn’t guarantee commitment.
A single transaction doesn’t ensure long-term engagement.
Path Analytics helps teams:
Spot drop-off points where users churn.
Identify high-value journeys that lead to staking, governance, or repeat activity.
Compare wallet cohorts (new wallets vs. whales vs. contributors).
Measure adoption of new features like bridging, staking, or DAO voting.
This visibility allows growth, product, and community teams to refine onboarding, improve retention, and drive adoption more effectively.
4. What metrics should I track with Path Analytics?
Key metrics include:
Top paths → Most common user journeys.
Drop-off rate per step → Where users abandon flows
Loops & repeats → Signs of confusion or stuck users.
Average steps per session → Depth of engagement.
Conversion paths → Sequences that drive your success metric (mint, stake, governance, etc.).
Tracking these metrics helps you understand both friction points and winning behaviors.
5. How does Formo make Path Analytics easier for Web3 teams?
Most analytics tools were designed for Web2 clicks, not Web3 wallets. Formo is purpose-built for Web3 and provides:
Unified tracking of frontend actions and onchain transactions.
Clear visualizations of wallet journeys across multiple chains.
Segmentation based on wallet profiles, balances, and behaviors.
Insights into where users drop off and what power users do differently.
With Formo, growth teams get the full picture they need to refine onboarding, boost retention, and scale sustainably — without wrestling with complex data.
