Google launches a new Attribution Beta | Publications

 

A couple of days ago, you might have seen a new tab in your Google Analytics report: Attribution Beta. This news Beta from Google did not make a lot of noise in the news, but only a couple of weeks after the launch of the “Web + App” properties in Google Analytics, it is another big move from Google.

It has been a while since we were patiently waiting for an improvement on the classic Multi-Channels Funnels reports in Google Analytics. But then, what does the new Beta has to offer?

For those who need a refresher on attribution, I encourage you to go through that introduction to the attribution article. It’s only a 5 minutes read and it will help you get a good understanding of the topic.

For the lazy ones, here is how Google defines Attribution:

Attribution is the act of assigning credit for conversions to different ads, clicks, and factors along a user's path to completing a conversion. An attribution model can be a rule, a set of rules, or a data-driven algorithm that determines how credit for conversions is assigned to touchpoints on conversion paths.

It is the last sentence of this definition that is interesting for us today. Historically, Google and other similar Analytics tools provided marketers with default rule-based models such First & Last Click, Time Decay, Linear or Position Based attribution. All those models were interesting to look at when trying to attribute the real value of any touchpoint other than the Last Click default model.

But the truth is that all those models are wrong and misleading, in their own specific ways.

If you want to deep-dive on that topic, go through this article explaining the evolution of attribution over time.

For the ones lucky enough to run on Google Analytics 360 (paid version), Data-Driven Attribution might not be new to you, but for the others, it is a true game-changer to have access to a free data-driven attribution tool.

Data-Driven Attribution Model

The new feature of the Attribution that gets us all excited is the launch of Data-Driven Attribution inside Google Analytics (finally!). DDA is a machine-learning-based attribution model that evaluates both the conversions and the non-conversions path to better allocate credit to any touchpoint.

As explained by Google: the model incorporates factors such as time from conversion, device type, number of ad interactions, the order of ad exposure, and the type of creative assets. Using a counterfactual approach, the model contrasts what happened with what could have occurred to determine which touchpoints are most likely to drive conversions. The model attributes conversion credit to these touchpoints based on this likelihood.

Here is a visual example of how this model works:


Data-Driven Attribution example

In the example above, Google will compare the path to conversion with the path that did not convert and will, therefore, be able to allocate more credit to the differentiator, in this case, the bannering touchpoint.

Is there any requirement?

Asking the question is already answering it. As the model is data-driven, it needs a minimum volume before you can access your first data-driven models. The minimum requirement is to have at least 600 conversions within the last 30 days. Note that eligibility for data-driven attribution is determined by the data for each conversion type, so you may see a Data-driven model for some of your website and Google Analytics conversions but not for others. Also, what is true to access the DDA model is also true to keep accessing it, so if your conversion volume drops under the minimum requirement, you won’t be able to access your DDA report anymore.

Test, test & test

As the product is still a beta, you can expect some limitations. For example, it is not (yet?) possible to use Custom Channel Groups in the different models. Another limitation is the absence of Google Ads cost data and click data for reporting.

We can expect those features to be incorporated as the product grows. 

We, therefore, encourage you to test this new beta and share feedback with the development teams in order to make the product evolve in the way marketers are expecting it to evolve. From our experience, Google engineers take those feedback very seriously and do not hesitate to include those in their product roadmap.

 


publication author Grégoire le Hardy
AUTHOR
Grégoire le Hardy

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