How to Analyze User Onboarding with Flows

User flows show how people navigate your app after they land: where they drop off, which paths convert to transactions, and where onboarding needs work.

Part 1: Navigate to Dashboards and Create a Flow Chart

In the Formo dashboard:

Click Dashboards in the sidebar
Click Add Chart in the top right.
From the chart type selector, choose Flow.

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

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)

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.

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.

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.

Part 5: Filter by User Properties

Click Filter to narrow the flow to specific user segments. Filter options:

By Device (mobile vs desktop drop-off patterns)
By Country (geographic patterns)
By Browser
By OS
By Referrer (organic vs paid, specific campaigns)
By Referrer URL

Example: Compare flows for mobile users vs desktop. If mobile has 40% drop-off at wallet connect but desktop has 10%, your mobile UX needs work.

Part 6: Identify Bottlenecks and Optimization Opportunities

Look for:

Hard Stops: Nodes where 50%+ users exit (red flag for UX friction)
Unexpected Paths: Routes most users don’t take (may indicate confusion)
Long Paths: Users going 5+ steps before conversion (simplify)
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).

Part 7: 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 Flows”. Saved flows update in real time, so you can track onboarding improvements over time as you ship fixes.

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.

Measuring Onboarding Success

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)

Measure with the onboarding rate formula

Onboarding rate = (Completed onboarding / Landed) × 100

Monitor this metric daily to track onboarding health.

The “aha moment” drives retention

Compare retention for different first-session actions:

First session action	Week 1 retention
Only connected wallet	15%
Viewed 3+ pages	25%
Completed transaction	45%

Insight: Driving users to complete a transaction dramatically improves retention.

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

Common onboarding improvements

Issue	Solution	How to measure
Low landing to app conversion	Clearer CTA, better messaging	Funnel step 1→2 rate
Wallet connect drop-off	Simplify options, add trust signals	Funnel step 2→3 rate
High bounce on app page	Improve loading speed, add guidance	Flows showing exits
Users don’t return	Email/notification follow-up	Week 1 retention

A/B test onboarding changes

When you ship changes to improve onboarding:

Note the date of the change
Compare funnel metrics before and after using date filters on your dashboard
Check if retention improved for post-change cohorts using a Retention chart

This lets you measure whether each change actually improved onboarding.

FAQ

What's the difference between Flows and Funnels?

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.

Can I set a time window for flows (e.g., only first 24 hours)?

Yes. Set a Conversion window (value and unit, e.g. 24 hours) in the flow’s chart settings to limit how long after the starting event later steps can occur.

Can I export flow data as a CSV?

Yes, but not the node and path structure itself. Click a node or path to select the users behind it, then export that user list as a CSV. There’s no JSON export option. Useful for reporting to stakeholders or further analysis in Excel.

​Part 1: Navigate to Dashboards and Create a Flow Chart

​Part 2: Configure Your Starting Event

​Part 3: Read the Sankey Diagram

​Part 4: Analyze Forward Paths

​Part 5: Filter by User Properties

​Part 6: Identify Bottlenecks and Optimization Opportunities

​Part 7: Save Flow Chart to Your Dashboard

​Real-World Analysis Walkthrough

​Measuring Onboarding Success

​Create onboarding segments

​Measure with the onboarding rate formula

​The “aha moment” drives retention

​Query onboarding rate with SQL

​Common onboarding improvements

​A/B test onboarding changes

​FAQ