Use the Model comparison report to compare how different attribution models impact the valuation of your marketing channels.In this article:
Available attribution models
An attribution model is the rule, or set of rules, that determines how credit for sales and conversions is assigned to touchpoints in conversion paths. Learn more about the models available in Attribution.
How to use the report
Access the report
- Sign in to your Attribution project at https://analytics.google.com/analytics/attribution.
- Go to Explore > Model comparison.
Choose your date range
Start by selecting a date range from the date picker drop-down menu at the top of the report (1, in the map above). When reporting on Conversion time (the default), use a date range that ends at least 3 days ago. When reporting on Interaction time, use a date range that ends at least 2 weeks ago. See below for additional context on Interaction time and Conversion time reporting.
Select conversion types
Select one or more conversion types from the drop-down menu (2, above). If you select multiple conversion types, they will be aggregated together in the report.
By default, all enabled conversion types are selected. If you want to disable certain conversion types, do so in the Settings > Conversion Types menu. Note: additional goals or Ecommerce transactions will be automatically synced with this menu.
Select attribution models to compare
Use the drop-down selectors in the Attribution model (non-direct) columns (3 and 4, above) to choose which attribution models to compare.
Customize your data view
To change the dimensions and metrics displayed in the report, click Edit report (5, above). In the Report settings panel, you can change the following settings: Dimension, % change selection, and Reporting time. You can also choose to include rows with empty dimension values.
The default dimension is Analytics default channel grouping. Specify up to two dimensions to get additional insights.
% change selection
The default is Attributed conversions. Select Attributed revenue to see the change in revenue between the two models.
The % change metric uses the following formula: (metric_from_model_2 - metric_from_model_1) / (metric_from_model_1 * 100%)
The default is Conversion time.
- Conversion time: This reflects attributed credit for all ad events occurring in the lookback window prior to the conversions in the specified time range. Note that these ad events may happen before the specified time range.
- Interaction time: This reflects attributed credit for all ad events occurring in the specified time range. Note that conversions may happen after the specified time range.
When your Attribution account is very new, many of the interactions on the conversion paths prior to account creation are not yet available.
If during this initial time period, you compare models based on Interaction time, you may see large discrepancies between models. Models with a longer average time lag (such as Data-driven) would likely show fewer total conversions than models with a shorter average time lag (such as Last interaction).
Empty rows (—)
Empty rows represent the portion of credit that doesn't have a value for one or both of your chosen dimensions. These rows are shown by default to ensure that credit totals are the same across dimensions. You can hide empty rows when you want totals to reflect the portion of credit that is classifiable by the chosen dimension(s). For example, if you only want to see the credit that is exported to Google Ads, choose Google Ads campaign as the dimension and hide empty rows.
Click the download icon (6, above) to download a CSV file that includes the data currently shown in the table.
Understand the data
By default, the data table shows your data broken out by the Analytics default channel grouping dimension. Learn more about how Attribution defines channels.
The data table shows 2 metrics as calculated by each attribution model:
- Attributed conversions: Count of conversions that are attributed to this dimension
- Attributed revenue: Amount of conversion revenues that are attributed to this dimension