Manage attribution models

About data-driven attribution models in Search Ads 360

Gain efficiency with a more accurate view of the paths that lead to conversions

By default, Search Ads 360 gives all credit for a conversion to the last click that leads a customer to your site. But a significant number of conversions may result from a path with several interactions—clicks on display ads as well as paid search clicks driven by shopping campaigns, generic or brand keywords, and other biddable items. By analyzing these interactions you may learn that some types of keywords or other biddable items tend to play a larger role in driving conversions than simple last-click attribution can reveal. If you increase bids for some of these previously undervalued keywords, you may gain efficiency with your advertising spend.

Data-driven attribution (DDA) analyzes interactions in your campaigns and creates a model for distributing conversion credit based on where an interaction occurs in a conversion path. Then DDA applies the model to the conversions in your advertiser, so you can see a more accurate picture of how clicks on keywords and other biddable items lead to conversions.

Example

For example, DDA may uncover that the following conversion paths occur frequently within an advertiser's campaigns (see the following image):

  • Click on a display ad > Click on a generic keyword > Click on a brand keyword > Conversion
  • Click on a generic keyword > Click on a brand keyword > Conversion


A data-driven model calculates distribution of credit in a funnel.

By comparing these paths with other interaction patterns, DDA may create a model that distributes credit as follows (the percentages below are just examples and may be very different for your specific campaigns):

  • In the "Display > Generic > Brand" path:
    Display: 10%
    Generic: 30%
    Brand:    60%
  • In the "Generic > Brand" path:
    Generic: 20%
    Brand:    80%

After Search Ads 360 generates this example model, the advertiser can compare conversions reported by the DDA model with the last click model. The example report below shows that the advertiser's upper funnel keywords play a larger role in driving conversions than last-click attribution reveals.

Optimize bids

While you can manually adjust bids based on performance data from a DDA model, a Search Ads 360 bid strategy can automate this process for you. Search Ads 360 bid strategies can leverage both Smart Bidding technology as well as a DDA model's assessment of a biddable item's value to achieve the most efficient spend for a specific ROI goal.

As with all bid strategies, comparing performance with manual bidding (or with other bid strategies that use last-click attribution) requires careful preparation and a timeline of at least a few weeks. Learn more about comparing bid strategies.

Identifying conversion paths

DDA can categorize interactions in conversion paths using some basic assumptions about how most advertisers organize their search campaigns. For example, most advertisers have both upper funnel keywords and lower funnel  keywords. Starting from this assumption, DDA can distribute credit based on whether a keyword led to an upper funnel or lower funnel interaction.

If you want to model other types of interactions, you can define custom channel groupings. For example, you might want to know how your generic, brand, competitive, and promotion keywords interact together to drive purchases and newsletter signups. To create this more complex model, you need to specify custom channel groupings when you set up a DDA model.

We recommend that you define custom channel groupings if you are a heavy user of shopping campaigns or dynamic search ad campaigns because the automatic channel groupings train DDA models on keywords only.

Learn more about channel groupings and see examples for various business verticals.

Floodlight conversions only

Each Search Ads 360 DDA model can analyze and report on interactions leading to as many as 50 different Floodlight activities. Search Ads 360 DDA models cannot analyze or report on conversions tracked by Google Ads conversion tracking, Google Analytics, or other conversion tracking systems (Google Ads and Google Analytics have their own attribution models that you can apply to Google Ads or Google Analytics data).

Depending on what you're trying to learn, you may want to create a model that includes only Floodlight activities related to a specific conversion funnel. However, make sure you include enough Floodlight activities to provide Search Ads 360 with sufficient data to generate the model

For example if you have two Floodlight activities that are not in the same funnel, such as "Retail purchases" and "Wholesale inquiries", you could do either of the following:

  • Create two separate DDA models, one for the "Retail purchases" funnel, and the other for the "Wholesale inquiries" funnel.
    This is the best practice if you think the conversion funnels are different enough from each other that credit would be distributed differently. For example, create separate models if you think the two funnels mostly look like the following:
    Generic -> Brand -> "Retail purchases"
    Generic -> Geo -> Competitor -> Brand -> "Wholesale inquiries"
     
  • Create one DDA model for both funnels.
    This is the best practice if you think the conversion funnels are fairly similar or close enough for your purposes.

Or you can create three models, one for each funnel and one for the combined funnels, and compare them.

Accounting for unattributed conversions

If you use Floodlight iframe or image tags instead of the global site tag or Google Tag Manager, Search Ads 360 is not able to observe conversions when the website cookies that store information about your ad clicks aren't available due to factors including browser settings. In these cases, Floodlight uses scaling to account for the conversion data that can't be directly measured. That is, Floodlight uses machine learning and historical data to model the number of conversions and amount of conversion revenue that cannot be measured. Floodlight can then add the resulting estimate to its conversion metrics to provide a more complete picture of how your advertising drives conversions. 

DDA models include these scaled conversions both when generating a model and when applying the model to a Floodlight column. 

Which advertising channels are considered part of a conversion path?

When examining conversion paths, Search Ads 360 DDA analyzes clicks from the following channels:

  • Paid search clicks
  • Paid social clicks
  • Clicks from the Google Display Network if Search Ads 360 manages the Google Ads display campaign, and if the ad is targeted with keywords or other items that Search Ads 360 tracks through placeholder keywords
  • Display clicks if your advertiser uses Campaign Manager and uses a common set of Floodlight activities to track both paid search and display conversions
  • Natural search clicks if your advertiser uses Search Ads 360 Natural Search reporting and you've chosen the appropriate attribution option (by default, natural search clicks are ignored by DDA)

Search Ads 360 only reports on clicks that are redirected through Search Ads 360. That is, a Search Ads 360 DDA model might attribute partial credit to a display ad managed by Campaign Manager and the rest of the credit to a paid search click. But because Search Ads 360 only reports on paid search clicks, when you view a report, you'll only see the partial credit attributed to the paid search click.

Note that just like other attribution models used in Search Ads 360, a Search Ads 360 DDA model ignores impressions (both search and display). Search Ads 360 doesn't have access to data about display and natural search impressions, so only clicks can be considered as interactions that potentially lead to conversions.

Data requirements

As a general guideline, DDA needs 15,000 clicks and 600 Floodlight conversions during the last 30 days to successfully generate a model. The clicks can come from any search engine, social engine, or engine track account that you've added to Search Ads 360.

For example, if you create a model with the following data:

  • Two channel groupings: one for Generic keywords and another for Brand keywords
  • All of the Floodlight activities in your retail funnel

You'll need a total of 15,000 clicks on the Generic and Brand keywords in your channel groupings and a total of 600 conversions from the Floodlight activities in your retail funnel, all during the last 30 days.

Search Ads 360 can start preparing the model as soon as you receive the minimum number of clicks and conversions over a period of 30 consecutive days. The initial learning period lasts about 24 hours.

Once the model has been generated, Search Ads 360 applies the model to the previous 60 days of conversion data (if available), as well as to all conversion data going forward.

Offline conversions

Offline conversions can also be used to generate a model if the conversions are attributed to a click ID that is less than 30 days old. This applies to conversions uploaded from the Search Ads 360 API or bulksheets and conversions uploaded from the Campaign Manager API. Offline conversions that meet these criteria count towards the total number of conversions required to generate a model.

Once the model has been generated, Search Ads 360 applies the model to offline conversions that meet the following criteria:

  • If you use the Search Ads 360 API or bulksheets to upload the conversions, the conversions must be attributed to a click ID that is less than 60 days old.
  • If you use the Campaign Manager API to upload the conversions, the conversions must be attributed to a click ID that is less than 60 days old, or an encrypted user ID or mobile device ID.

The DDA model learns continuously

The DDA model continues to learn and updates the model each week. Any new campaigns, keywords or other items you add to your channel-grouping labels will be reviewed and incorporated into the model. That is, the attribution can continue to change. Note that updates to the model only apply to new performance data going forward. Search Ads 360 does not apply the updates to historical data (conversions that occurred before the model was updated). 

If the weekly number of clicks and conversions falls below the data requirements, Search Ads 360 uses a previously generated model. If Search Ads 360 hasn't been able to generate a model within the previous 30 days, the DDA model applies the basic linear model and will retry the update next week.

Model updates are typically subtle, and the effect on reporting data is gradual, since the updates apply only as new conversions are reported.

If you create a bid strategy that uses a DDA model, during the bid strategy's learning period you might see a bit of volatility in the DDA model as both the bid strategy and DDA model adjust to each other. Usually, you'll see fewer updates to the DDA model after the bid strategy's learning period completes.

The model is applied once a day

Once a day, DDA applies its current model to the data reported during the previous 24 hours. Depending on when you view a report, data in a DDA column from today or even yesterday may not reflect the DDA model yet. To get the most complete attribution data when including a DDA model in a Search Ads 360 report, don't include today or yesterday in the report's time range.

Similarly, bid strategies using a DDA model take a day before seeing the model's effects on the latest activity.

Create and compare multiple models

You can create up to five DDA models in Search Ads 360. Consider starting out with a couple of different DDA models with different channel groupings and compare the insights you gain from each.

After you create the model, compare data from the model with other models. For example, create the following Floodlight activity columns that report on the activities in your model:

  • One column that uses the DDA model you created (If you created multiple DDA models, create one column for each model) 
  • Once column that uses the default last-click attribution model

Add the columns to a reporting table and compare the data in each. You may learn that some of your long-tail keywords are playing a larger role in driving conversions than you thought.

If you find a model that you think accurately reflects your business and business goals, use the model in a bid strategy to achieve your goals with the optimal spend.

Include cross-environment conversions

To get the most complete view of conversion paths, include cross-environment conversions when you report on a data-driven attribution (DDA) model or use a DDA model in a new or existing bid strategy that adjusts mobile bids.

Cross-environment conversions start on one device or browser and end in another. For example, a customer may click a search ad on a mobile phone,  then later use a desktop device to directly access an advertiser's site and convert. By default, Search Ads 360 only reports conversions that occur on a single device or browser. But by leaving out cross-environment conversions, you may be undervaluing the role some of your ads play in driving conversions. A default report in DS—even a report that contains a column with a DDA model—wouldn't count the conversion in the example above because the paid search click and the conversion occurred on separate devices.

The best practice is to include cross-environment conversions in your DDA Floodlight column. You can also create two DDA Floodlight columns: one with cross-environment conversions and another without. Then add both columns to a report and compare the difference. See more detail about which Search Ads 360 features support DDA models and cross-environment conversions.

Cross-environment reporting is available only for ads, keywords, ad groups, and higher levels. If you add your DDA Floodlight column to other types of reports (such as product groups), cross-environment data won't be included in the column. 

In April 2018, Search Ads 360 introduced an improvement that reduces the amount of conversion data needed to detect cross-environment conversions. This change requires your advertiser to contain a mix of single-environment conversions as well as cross-environment conversions. In reports that include dates before April, 2018, you may see an increase in cross-environment conversions that is due to the change in the way Search Ads 360 detects cross-environment activity.

How soon do cross-environment conversions appear in a DDA Floodlight column?

Within 24 hours of creating a DDA model, a DDA Floodlight column that has enabled cross-environment conversions will start showing the effects of cross-environment conversions. The column does not include cross-environment conversions that occurred before you created the model.

How do DDA models in Search Ads 360 differ from Campaign Manager?

If you use Campaign Manager to manage display ads, you can also create a data-driven attribution model in Campaign Manager. The model you create in Campaign Manager is completely separate from Search Ads 360 models. It cannot be imported into Search Ads 360, so it can only be applied to performance data in Campaign Manager.  

Both Search Ads 360 and Campaign Manager models analyze the following types of events:

Campaign Manager models also analyze the following types of events:

  • Paid search impressions
  • Display impressions

Search Ads 360 doesn't analyze impressions.

While the Campaign Manager DDA model can show the number of whole or partial conversions attributed to paid search and display activity, Search Ads 360 only reports the number of whole or partial conversions attributed to paid search. For example, if a conversion path starts with a paid search click but also includes display activity, Search Ads 360 will report partial credit for the paid search click.

Ready to get started?

  1. If you're creating a DDA model with custom channel groupings, apply labels to your campaigns, keywords, or other items at least 12 hours before you create the model. Otherwise, the model may not recognize your custom channel groupings. 

  2. Create a data-driven attribution model.
  3. Use the model by doing any of the following:
Was this article helpful?
How can we improve it?