Stop Optimizing Pages.
Start Optimizing Journeys.

Journey Analysis is a way to visualize and understand the paths shoppers take through your website, from entry to conversion (or drop-off).

Instead of analyzing a single page in isolation, Journey Analysis helps you see:

• Entry points (where shoppers start)
• Page-to-page progression
• Funnel drop-off points
• Conversion-driving sequences
• Unexpected navigation patterns

This turns your analytics from static data into actionable behavioral insight.

Most analytics tools show you what happens on a page.

But they don’t show you how shoppers actually move through your site.

That’s where Journey Analysis comes in. It helps you see the full picture, not just isolated interactions.

Most analytics tools answer questions like:

• How is this page performing?
• What’s the conversion rate?
• Where are people clicking?

Useful, but incomplete. They don’t answer:

• What happened before this page?
• Where did shoppers go next?
• Which path led to conversion?

Without that context, optimization becomes guesswork.

Ecommerce teams are moving:

Instead of asking:

“How do we improve this page?”

You start asking:

“Which journeys drive the most revenue, and how do we send more shoppers through them?”

1. Identify Where Shoppers Drop Off in Your Funnel

Journey Analysis helps you pinpoint exactly where shoppers leave.

2. Find Your Highest-Converting Paths

Not all shopper journeys are equal.

3. Detect Looping Behavior (Hidden Friction)

Loops often signal confusion.

4. Discover Unexpected High-Value Paths

Shoppers don’t always follow your intended funnel. And that’s where opportunity lives.

5. Improve Conversion Rate Without Guessing

Journey Analysis shows where momentum breaks.

Step 1: Start With a Question

• Where are shoppers dropping off before purchase?
• Which journeys drive the highest revenue per session?
• Are shoppers finding what they need quickly?

Step 2: Analyze Entry Points

Identify where high-value shoppers begin their journey.

Step 3: Follow Shopper Paths

Click through journeys and observe:

• Navigation flow
• Drop-off points
• Behavior patterns

Step 4: Identify Patterns

Focus on:

• High-traffic paths
• High drop-off journeys
• Repeated loops
• Unexpected flows

Step 5: Take Action

Turn insights into tests:

• Adjust CTA placement
• Improve navigation
• Add missing information
• Reduce friction

Segment Your Data

Different shoppers behave differently. Compare:

• Mobile vs desktop
• Paid vs organic
• New vs returning shoppers

Combine With Other Data

Journey Analysis shows flow. Combine it with:

• Heatmaps, to understand what shoppers click
• Session recordings, to observe real behavior
• Conversion data, to measure impact

Focus on High-Impact Paths

Don’t analyze everything. Prioritize:

• High-traffic journeys
• Revenue-driving paths
• Critical funnel steps

Journey Analysis directly impacts:

• Conversion rate
• Average order value (AOV)
• Revenue per session (RPS)
• Customer experience

It helps you move from:

Journey Analysis isn’t just a feature. It represents a shift in how ecommerce teams optimize:

Your customers don’t experience your website as pages.

They experience it as a journey.

And that journey determines whether they buy, or leave.