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The first 5 minutes decide everything for new users. User flows reveal exactly how people navigate your dapp after they land. With Formo’s flow visualization, you can see where users drop off, which paths convert to transactions, and how to optimize onboarding.

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Part 1: Navigate to Dashboards and Create a Flow

In the Formo dashboard, click Dashboards in the sidebar. Click Create Chart in the top right. From the chart type selector, choose User Path. This creates a Sankey diagram that visualizes how users move between pages and events.
Sankey flow diagram showing user paths from landing to wallet connection to transaction

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Part 2: Configure Your Starting Event

In the flow builder, select your starting event. Common starting points for onboarding analysis:
  • First page view (shows the complete user journey from landing)
  • Connect wallet (shows post-connection paths)
  • Account Signup (tracks authentication flow)
For onboarding analysis, start with the connect wallet event to see what happens immediately after users authenticate. Click the event dropdown and select the event. The flow automatically generates.

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Part 3: Read the Sankey Diagram

The diagram shows:
  • Nodes (circles): Pages or events in your flow (e.g., “Swap Page”, “Portfolio”)
  • Paths (arrows): Lines connecting nodes, thickness represents user volume
  • Drop-off (gray paths exiting right): Users who left without continuing
Width of paths = number of users. Thicker paths mean more users took that route. For example: If a connect wallet event flows to “Swap Page” with 500 users, but only 200 complete a swap, you have a 60% conversion rate on swaps.

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Part 4: Analyze Forward Paths

Forward paths answer: “What did users do after this step?” Example questions:
  • After connecting their wallet, how many users visited the portfolio page?
  • Of those who visited the portfolio, how many completed a transaction?
  • What’s the most common second step after landing?
Click any node to highlight all paths flowing from it. The sidebar shows exact conversion percentages.

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Part 5: Analyze Backward Paths

Backward paths answer: “What did users do before this step?” This is critical for understanding onboarding friction. Example:
  • Users who completed a swap typically visited the “How It Works” page 2x first
  • Users who bounced typically skipped the tutorial
Click any node and toggle to Inbound Paths to see what happened before users reached that step. Insight: If most successful users read your docs first, improve doc visibility on landing.

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Part 6: Filter by User Properties

Click Filter to narrow the flow to specific user segments. Filter options:
  • New Users Only (lifecycle = New, sessions = 1)
  • By Referrer (organic vs paid, specific campaigns)
  • By Device (mobile vs desktop dropoff patterns)
  • By Wallet Label (verified, high-net-worth wallets)
  • By Chain (Ethereum users vs Polygon users)
Example: Compare flows for mobile users vs desktop. If mobile has 40% dropoff at wallet connect but desktop has 10%, your mobile UX needs work.

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Part 7: Identify Bottlenecks and Optimization Opportunities

Look for:
  1. Hard Stops: Nodes where 50%+ users exit (red flag for UX friction)
  2. Unexpected Paths: Routes most users don’t take (may indicate confusion)
  3. Long Paths: Users going 5+ steps before conversion (simplify)
  4. Device Disparity: Different conversion rates on mobile vs desktop
For each bottleneck, ask: “What’s the friction here? Is it unclear UI? Missing docs? Technical issue?” Document findings. Prioritize fixes by impact (filter to estimate user volume affected).

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Part 8: Save Flow Chart to Your Dashboard

Once your flow analysis is complete, click Save to Dashboard. Choose an existing dashboard or create a new one. Name the chart clearly: “New User Onboarding Flow” or “Post-Swap User Paths”. Saved flows update in real time, so you can track onboarding improvements over time as you ship fixes.

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Real-World Analysis Walkthrough

Imagine your new user onboarding flow shows:
  • 100 users land on your app (starting event: first page view)
  • 80 connect a wallet (80% conversion)
  • 60 visit swap page (75% of wallets)
  • 20 complete first swap (33% of swap visitors)
Analysis:
  • Wallet connect: Strong (80% is good)
  • Swap page visit: Good (75%)
  • Swap completion: Weak (33%)
Action: Investigate swap friction. Is the UI confusing? Are gas fees discouraging swaps? A/B test clearer CTA buttons. After shipping improvements, check the same flow 1 week later. Did swap completion improve to 40%? If yes, rollout the change.

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Measuring Onboarding Success

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Create onboarding segments

Use segments to track users at different onboarding stages: Segment 1: Landed but didn’t connect
  • Visited page in last 7 days
  • Did NOT connect wallet
Segment 2: Connected but didn’t transact
  • Connected wallet in last 7 days
  • Did NOT complete transaction
Segment 3: Completed onboarding
  • Completed transaction in last 7 days
  • Is a New User (lifecycle)

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Measure with the onboarding rate formula

Onboarding rate = (Completed onboarding / Landed) × 100
Monitor this metric daily to track onboarding health.

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The “aha moment” drives retention

Compare retention for different first-session actions:
First session actionWeek 1 retention
Only connected wallet15%
Viewed 3+ pages25%
Completed transaction45%
Insight: Driving users to complete a transaction dramatically improves retention.

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Query onboarding rate with SQL

SELECT
  toDate(timestamp) AS date,
  countDistinct(CASE WHEN type = 'page' THEN anonymous_id END) AS landed,
  countDistinct(CASE WHEN type = 'connect' THEN address END) AS connected,
  countDistinct(CASE WHEN type = 'transaction' THEN address END) AS transacted,
  round(connected / landed * 100, 1) AS connect_rate,
  round(transacted / connected * 100, 1) AS transaction_rate
FROM events
WHERE timestamp >= now() - INTERVAL 30 DAY
GROUP BY date
ORDER BY date

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Common onboarding improvements

IssueSolutionHow to measure
Low landing to app conversionClearer CTA, better messagingFunnel step 1→2 rate
Wallet connect drop-offSimplify options, add trust signalsFunnel step 2→3 rate
High bounce on app pageImprove loading speed, add guidanceFlows showing exits
Users don’t returnEmail/notification follow-upWeek 1 retention

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A/B test onboarding changes

When you ship changes to improve onboarding:
  1. Note the date of the change
  2. Compare funnel metrics before and after using date filters on your dashboard
  3. Check if retention improved for post-change cohorts using a Retention chart
This lets you measure whether each change actually moved the needle.

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Next Steps

Combine flow analysis with conversion funnels for deeper insights:

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FAQ

User Paths (flows) show all possible routes users take, including dropoffs. Funnels measure conversion through a specific sequence of steps. Use flows to discover paths, funnels to measure specific conversions.
Yes. In the flow filter, add a condition like “Time Since Starting Event: < 24 hours” to see only the first day of user behavior.
Flows can show up to 20 steps deep, though clarity typically degrades after 7-8 steps. If your flow is too complex, filter to new users only or segment by user property.
Yes. Click Export in the chart menu to download node and path data. Useful for reporting to stakeholders or further analysis in Excel.