Why use data-driven attribution? And which Google product to use?

Jimmy McCann

Head of Digital Strategy

Analytics and Data Science

Understanding what marketing channels contribute to customer conversions and then assigning credit to each appropriately is crucial to any digital marketing strategy.

Google’s products have a range of attribution models and each varies greatly with the level of customisation and how much of a whole picture they present to you. Different models let you allocate how much credit each action gets for your conversions; depending on the model chosen, the credit is given out in different ways.In this blog, we review each Google product that has DDA available.

Why use data-driven attribution?


Data-driven attribution (DDA) uses predictive algorithms to analyse your data and to determine which channels, campaigns, creatives and keywords have the biggest impact on conversions. Unlike other attribution models, data-driven attribution can identify steps throughout the whole customer journey, increasing the likelihood of conversions and gives these interactions more credit.

These insights show that streams are most (or least) valuable and allow brands to allocate their marketing budget accordingly. Funnelling money into the right campaign can improve ROI and increase online revenue, without the need for additional advertising budget.

What data driven attribution models are available?


  • Last click: full credit is given to the last clicked ad and relevant keyword
  • Last non-direct click: full credit is given to the last non direct click (this is only available in GA and is the default attribution model)
  • First click: full credit is given to the first clicked ad and relevant keyword
  • Linear: credit is equally distributed across all clicks (organic and paid) in the customer journey
  • Time decay: more credit is given to clicks that happened closer to time of conversion
  • Position based: the first and last clicked ads are both given 40% credit, and the remaining 20% is split equally across all other clicks
  • Custom model: you are able to build a completely bespoke model based on any of the predefined models available
  • Data-driven attribution: credit is distributed based on past data for this conversion.

Google Ads


The Google Ads logo.

By default, Google Ads uses a last click attribution model – however, we are able to set up data-driven attribution modelling as long as the following campaign requirements are met:

  • 15,000 clicks and 600 conversions per conversion type in 30 days
  • 10,000 clicks and 40 conversions in 30 days ongoing.

When attributing credit, Google Ads’ DDA only takes paid campaigns into consideration. Other marketing channels that have been involved will not be recognised for the part they played in the conversion.

While this means the data-driven attribution model in Google Ads does not necessarily provide a holistic overview of your customer journey, it is still useful for optimising keywords and paid campaigns.

Search Ads 360


The Google Search Ads 360 logo.

SA360’s data-driven attribution model can encompass display clicks, paid clicks, paid social clicks and natural search clicks. To use DDAM in Search Ads 360, you’ll need:

15,000 clicks and 600 Floodlight conversions in the last 30 days.

The initial learning period takes 24 hours, so ideally data-driven attribution would be set up at least 24 hours before you want to use it.

To set up data-driven attribution in Search Ads 360: Create Channel Groupings (e.g. generic keywords, brand keywords) > Select which Floodlight activities you want to be analysed in the DDAM > Apply Channel Groupings > Create columns in the interface.


Things to consider:


  • SA360 ignores search and display impressions, so the DDAM only considers clicks that lead to conversions
  • You need to be set up on Campaign Manager and a common set of Floodlight activities to track display clicks
  • You need to use Search Ads 360 Natural Search reporting and have Equal attribution option chosen to track natural search clicks
  • Offline conversions can be used to generate a model if the click ID for conversions is less than 30 days old.

Campaign Manager


The Google Campaign Manager logo.

Data-driven attribution in Campaign Manager incorporates the same metrics and channels as Search Ads 360, but also offers a slightly more comprehensive view of the customer buyer journey through impression data.


To use the Campaign Manager Attribution Modeling Tool:

  1. Go to Reporting > Attribution
  2. Select a Floodlight configuration
  3. Click Attribution Modeling Tool
  4. Click the dropdown next to the default model, and select Create new data-driven model
  5. Name the model
  6. Select all Floodlight activities that represent conversions
  7. Choose Basic Channel Grouping or select a custom channel grouping
  8. Set a custom lookback window.

It takes up to 48 hours for Campaign Manager to ‘train’ a data-driven attribution model before it is usable.

The Google Analytics 360 logo.

Google Analytics


There are seven attribution models to choose from in the free version of Google Analytics, but you will need to be an Analytics 360 customer to access data-driven attribution modelling.


Google Analytics 360


Unlike Google Ads and Search Ads 360, Analytics 360 has a holistic overview of user actions from all digital marketing activity. So, creating a data-driven attribution model in GA360 can provide in-depth insight to how each channel contributes towards conversions.


Data-driven attribution models (DDAM) are only available in GA360 if you meet the following initial requirements:

  • Google Analytics 360 customer
  • Have either Ecommerce Tracking or Goals set up
  • Have a Google Ads account with at least 15,000 clicks on Google Search and a conversion action with at least 600 conversions in the last 30 days.

You also need to meet the ongoing requirement of 400 conversions per conversion type, with a path length of 2+ interactions, and 10,000 paths in the selected reporting view, over a 28 day period. DDAM in Analytics 360 provides a rounded view of how each channel contributes to conversions. The insights can be used to inform your budget strategy, highlighting how investing in particular channels may provide a higher ROI.

Need help getting the most out of data driven attribution?Contact us and our data scientists can provide the answers

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