Overview
Marketers often seek information about why a user moved along a particular path in a Flow, where they are in the Flow currently, or whether they entered the Flow. With Debug Flows, marketers can understand why a published flow is behaving the way it is. Debug Flows helps them understand the exact path that users are traversing in a published flow by following the journey of a particular target user. This helps them understand why the engagement for a specific campaign in a Flow wasn’t optimal or helps them understand why a user behaved a certain way.Debug Flows is a feature that helps a marketer trace a user’s path in a Flow. This helps validate the performance of a published flow, understand whether flow settings and set-up, such as entry criteria, triggers, and scheduling, are configured correctly, and also helps understand drop-off points or conversions within a specific user or cohort. Using Debug Flows, one can understand the following:
- Why a user did not enter a flow, even after performing a trigger event.
- After entering a flow, why a user did not receive a campaign.
- Once a user has entered the flow - understand the path the user has followed, how the user has engaged with the flow, and where the user has converted or dropped off.

How can you use Debug Flows?
- Understanding why your flow is not performing as per expectations You published a flow; however, viewing your analytics, you realize that the audiences who are receiving the campaign are not the intended audience. Using Debug Flows - you can understand why these audiences were part of the flow and take corrective action accordingly.
- Test the flow for yourself before publishing it for the larger segment/audience You are running a multi-channel customer journey across a large set of audiences. However, before publishing the campaign for the entire segment, you would like to publish it for a smaller set of users (or internal team members) and test it out. With Debug Flows, you can understand the flow performance for the smaller audience set by ‘Shadowing users”, optimize the flow, and accordingly publish the same for a larger audience.
- Debug a flow yourself You have published a flow. However, users are not engaging with the flow as expected. Debug Flows can be used to understand the gaps in the flow setup and make relevant changes.
How does Debug Flows work?
Debug Flows is not available for Fixed Time Flows that is, One-time or Periodic Flows.
- Navigate to the All Flows Page.
- Select the required Flow by clicking on it.
- Navigate to the Debug Flows tab.
- In the Search user entry search bar, select the user identifier - ID or MoEngageID in the dropdown. For more information, refer to User Identifiers.
- Specify the ID or MoEngageID of the user for whom you want to debug the user trips.
- Press Enter. This will populate all the attempts and entries of the user in the Flow for its various versions in the User Entry dropdown.
- You can specify a date range to select the attempts/entries of the user between a specific timeframe by clicking the
(filter icon) and specifying the date range in the date field. The options available are Yesterday, Last Week, Last Month, and Custom Range. Note: You cannot look back at a date range greater than 30 days from the current date for debugging. - Select the entry or attempt that you wish to look at in the User Entry dropdown and click Debug.

Terms to Know
Viewing Information About a Stage/Action
To view the information about a stage or action, or condition, click on the stage, and you will get the details about it on the left of the canvas. For example, if there is an email campaign attached to a Flow and user has moved through that stage, you can click on the campaign and see its status, locale, and variant information, along with when the user entered and exited that stage.Trip summary
The trip summary section provides information about when the user started the trip and when they exited the flow. The following details are available:- Trip start - this field indicates when the user entered the flow.
- Trip converted - this field indicates whether the user has converted within the trip or not.
- Trip end - this field indicates when the user exited the flow.
- Trip end reason - this field indicates why the user exited the flow. A user could have exited the flow because of one of the following reasons:
- Trip end stage - this field indicates at which the user exited the flow.

Conversion events
The conversion events section provides information about when the user has achieved the conversion goals set for the flow.