How to adjust to changes in attribution data filters in flows

Estimated 2 minute read
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Updated Oct 11, 2024, 7:53 AM EST
You will learn

You will learn

Learn how to adjust attribution data you may be using as flow filters. With recent changes to certain attribution filters, you will need to adjust how you set up your new flows to ensure profiles still meet the requirement criteria. 

Before you begin

Before you begin

Starting on 8/29/24, the following message filters, trigger filters, or conditional splits will not be supported: 

  • Attributed channel (“$attributed_channel”)
  • Attributed flow (“$attributed_flow”)
  • Attributed message variation (“$attributed_variation”)
  • Attributed channel (“$attributed_channel”)
  • Attributed experiment (“$attributed_experiment")
  • Attributed flow channel ("$flow_channel")
  • Attributed campaign channel ("$campaign_channel")

All existing flows using these attributes will still continue to function for now, but it is advised to update these as soon as possible to avoid issues. The section below walks through how to update flows currently using these filters.

Understanding what has changed

Understanding what has changed

Prior to 8/29/24, you may have used the attribution filters noted above to ensure that a profile fit a flow’s criteria by referencing other messages, flows, experiments, etc. that they also received. 

For example, you wanted to ensure that someone who has placed an order did not continue through a browse abandonment flow. In this example, using one of the former attribution filters, you set up your flow as Has Placed an Order since starting this flow where the Attributed flow equals Browse Abandonment. However, given these attribution data filters are no longer supported, the flow setup below serves as a replacement for most similar scenarios. 

New flow filter setup

New flow filter setup

If you are looking to ensure that someone has not completed an action or fits the criteria of the flow, you can use the What someone has (or has not done) condition. In the above example, if you want to ensure that someone continues through the browse abandonment flow as long as they have not placed an order, you can use the filter Person has placed an order at least zero times over time since starting this flow

In this setup, the flow or message that drove an order is not the important factor, but ensuring the flow still drives conversions for those that have not purchased. The What someone has (or has not done) condition along with your chosen conversion metric should replace most needs for the former attribution data filters. 

Additional resources

Additional resources

Understanding updates to attribution data  

Understanding flow triggers and filters

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