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Funnels Migration from Classic to Console

Last Updated May 11, 2025
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Brief Overview

As part of our continued investment migrating insights to the console, Funnels created in Insights Classic have been automatically migrated into Flow Analytics within the WalkMe Console. This upgrade introduces a more powerful framework for tracking user behaviors, enabling deeper analysis, better visualizations, and greater flexibility in understanding end-user journeys.

This article explains the details of the migration process, the functional differences between Funnels and Flows, and why Flow Analytics represents a significant enhancement for customer-facing teams.

Migration

Funnels previously defined in Insights Classic have been automatically recreated in the Flow Analytics section of the Console. These migrated Flows can now be accessed and managed through the Flow List interface.

Key Migration Details

Tracked Events

  • Your existing tracked events will be supported in Flow Analytics

  • However, events with unsupported definitions will remain usable but not editable in Insights Console

Brief Overview

As part of our continued investment migrating insights to the console, Funnels created in Insights Classic have been automatically migrated into Flow Analytics within the WalkMe Console. This upgrade introduces a more powerful framework for tracking user behaviors, enabling deeper analysis, better visualizations, and greater flexibility in understanding end-user journeys.

This article explains the details of the migration process, the functional differences between Funnels and Flows, and why Flow Analytics represents a significant enhancement for customer-facing teams.

Migration

Funnels previously defined in Insights Classic have been automatically recreated in the Flow Analytics section of the Console. These migrated Flows can now be accessed and managed through the Flow List interface.

Key Migration Details

Tracked Events

  • Your existing tracked events will be supported in Flow Analytics

  • However, events with unsupported definitions will remain usable but not editable in Insights Console

Column displays

  • Name: To avoid naming conflicts, migrated Funnels have the suffix:
    [Funnel Name]-(Migrated)-[EnvironmentName]-[SystemName]

    • Example: “Open Email Flow-(Migrated)-Production-Gsuite”

  • Created By: Migrated funnels will show "System Migration" as the creator to indicate they were generated during the migration process
  • Timestamps: Original Created and Last Updated timestamps from Classic will be retained for historical accuracy

Functional Comparison

Funnels (Classic Insights) and Flows (Flow Analytics) are both tools for analyzing how users progress through a series of steps—like clicking buttons, viewing pages, or completing tasks. While they serve a similar purpose, they're calculated differently.

This breakdown explains how each method works, highlights key differences, and shows how Flow Analytics offers a more advanced and flexible way to track user behavior across sessions, users, and systems.

Step Joining Conditions

Funnels (Classic Insights)

Flows (Flow Analytics)
  • Funnels only supports matching steps by user ID
  
  • Flows give you the flexibility to define exactly what conditions should join the steps
  • For example, you can track how a ticket is influenced by WalkMe content by using an analytics property on the ticket number to join steps to ensure the flow you're tracking is always relevant to a specific ticket
    • Meaning you can track objects such as tickets, purchase orders, or opportunities that are interacted by multiple users

Step Matching and Repeats

Funnels (Classic Insights)

Flows (Flow Analytics)
  • Funnels only search for one user completion. This means you can't tell if the user completed the funnel multiple times

  • Flows identify every completion of a user flow. This means you can detect if a user completed a flow multiple times

Timing Flexibility

Funnels (Classic Insights)

Flows (Flow Analytics)

  • Timing in Funnels is tied to the session itself. You can't define how quickly or slowly steps should happen

    • This means no control or customization over how time impacts user progression

  • Flows give you the ability to set expectations for timing between steps, such as how long users have to move forward

    • This adds control and precision, helping to reflect real-world process timing more accurately

    • This gives you the ability to discover outliers or users who are struggling with completing a process

Flexibility and Complexity

Funnels (Classic Insights)

Flows (Flow Analytics)
  • Funnels only support linear user flows. If you want to see how a user completes multiple routes, you have to create another funnel
  • Flows allow you to detect which paths your users take most frequently. This can help with product or WalkMe implementation decisions

Real-Life Scenario: "Add to Basket" Behavior

Let's say a user logs in and adds items to their basket multiple times over two days:

User A's Activity:

  • Monday

    • 11:00 AM – Login

    • 11:30 AM – Add to Basket

    • 11:45 AM – Login

    • 12:00 PM – Add to Basket

  • Tuesday

    • 11:00 AM – Login

    • 11:35 AM – Add to Basket

    • 11:45 AM – Login

    • 12:00 PM – Add to Basket

Classic Funnel Calculation

Here we will describe the logic of Classic Funnels in multi-session mode since Flows doesn't support single-session analytics. For those looking to replicate a single-session in Flows, use a duration condition between steps.

What gets counted:

  • One login → add to basket counted

  • All repeated actions are ignored

Why?

  • Funnels only track the first valid completion per session or user

  • Any duplicate events (like the second login or second add to basket) are considered noise and are discarded

So even if the user adds to their basket twice, only the first Login → Add to Basket is counted per session.

Result:
You get a simplified overview of how many users complete a funnel once — but you miss out on repeated behaviors, retries, or ongoing engagement patterns.

Session

Steps Counted

Time Between Steps

Monday

Login (11:00) → Add to Basket (11:30)

30 min

Tuesday

Login (11:00) → Add to Basket (11:35)

35 min
Average Time Between Steps:
30 minutes

Why?

  • We only consider the timing of the first completion

Flow Analytics Calculation

What gets counted:

  • Every Login → Add to Basket counted — even repeated ones

Why?
Flows are built to reflect real-world usage patterns, where users often repeat the same journey multiple times.

So in this case, every Login → Add to Basket pair gets counted, including the second and third times the user goes through the same process.

Result:
You get a full behavioral map — showing all attempts, completions, and variations — which is critical for identifying patterns like:

  • Retry behavior

  • Re-engagement

  • Drop-off after initial success

  • Time between completions

Sequence

Steps Counted

Time Between Steps

#1 (Monday)

Login (11:00) → Add to Basket (11:30)

30 min

#2 (Monday)

Login (11:45) → Add to Basket (12:00)

15 min

#3 (Tuesday)

Login (11:00) → Add to Basket (11:35)

35 min

#4 (Tuesday)

Login (11:45) → Add to Basket (12:00)

15 min
Average Time Between Steps:

(30 + 15 + 35 + 15) / 4 = 23.75 minutes

Why?

  • We take the average of every completion between steps

How to Create a New Flow in Flow Analytics

Ready for guidance on creating your first flow?

  • Smart Walk-Thru guidance: Click Show me how to begin a guided Smart Walk-Thru on building a new flow in the console

Flow Analytics

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