How many users are dropping off from a Flow?
- 22 Aug 2024
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How many users are dropping off from a Flow?
- Updated On 22 Aug 2024
- 1 Minute To Read
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Consider that you've created a Flow and added it to an onboarding Pop-up to guide users through a new process. Based on your Trend Insight analysis, the number of users who started the Flow is much higher than the number of users who completed the Flow. You want to understand if there's any friction in the Flow that is making users drop off without completing the process.
With Funnel Insights, analyze the number of users completing each step of the Flow and where they're dropping off the most. This data enables you to update the Flow step that has the most drop off, improve the UI friction, or even create a Cohort out of the most dropped off step for further analysis.
Use the following steps to analyze the number of users who dropped off from a Flow:
- On the Whatfix Analytics dashboard, click Insights.
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Click Create Insights.
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Click Funnel Insights.
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Click the Edit icon to name your Funnel.
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Enter a Description that helps explain what the Funnel is about.
your title goes here
- The Description gives you context about the created Insight when added to a Dashboard.
- It also enables other stakeholders to understand what data the Insight depicts while viewing Dashboards created by other team members.
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Click Add and then click Flows.
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Select the Flow that you want to visualize as a Funnel.
your title goes here
- Add all the steps in the Flow or just the required steps.
- If you've added the same Flow to other widgets such as Self Help, Task List, and more, click Trigger location to visualize the engagement.
- In the User filter section, click Add user filter, and then select the filter that you want. Filter the users playing your Flow based on a particular country, city, browser, and more.
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- To exclude specific filter values for which you don't require data, see How can I exclude filter values in Product Analytics?
- By default, the Product analytics data may contain identified (users identified by User ID) and unidentified (users not identified but denoted by cookie values) users. To filter unidentified users for clearer data, see How can I filter unidentified users in Product Analytics?
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Scroll down to view the chart generated.
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Click Save.
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