Attribution modeling

Data-driven attribution models

Train an attribution model based on your own data

If you’re new to attribution, we recommend using data-driven models. Since they're based on consumer behavior, you'll benefit from attribution reporting without studying the default algorithms or investing in user research.  Also, natural search traffic is eligible to receive credit in data-driven models, which can give a more complete picture of conversion data.

Create a new data-driven attribution model

  1. Go to Reporting & Attribution > Attribution.

  2. Choose a Floodlight configuration. All impressions and clicks tracked through this configuration will be taken into consideration by the model.

  3. Click Attribution Modeling Tool. 

  4. A default model appears. Last Interaction model icon Click dropdown next to the default model, at the bottom of the list click Create new data-driven model

  5. Name your model. Tip: Include today's date.

  6. To train the data-driven model correctly, select all Floodlight activities that represent conversions. (Don't include Floodlight activities that were created solely for building audience lists; such as remarketing pixels.) Filter reports to a single Floodlight activity later.
  7. Choose Basic Channel Grouping (for most setups).
    1. To create a custom channel grouping go to: Reporting & Attribution > Attribution > Attribution Modeling Tool > Channel Groupings.
  8. (Optional) Set a custom lookback window.
  9. Click Save.

You can only create one data-driven attribution model. Your model needs to train for 1 to 2 days, and will be greyed out until usable.  If you create a new model or make changes to an existing model, the model will need to retrain for another 1 to 2 days. Reporting is unavailable for date ranges prior to a model being trained.

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