Data-driven attribution: How to think about Google's default attribution model

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Attribution has been the holy grail for advertisers since the beginning of time, especially for media platforms that typically sit further away from the conversion and play a role in branding (i.e., billboards, banner ads and videos).

In September 2021, Google Ads announced its plans to move away from last-click attribution to a data-driven attribution (DDA) model. This change is intended to better allocate credit that search keywords play in a consumer’s purchase decision. 

Last month, Google started letting advertisers know it will automatically switch conversion tracking to the data-driven attribution model. Using machine learning, Google believes that data-driven attribution provides the greatest opportunity to value each unique interaction properly.  

Here’s what this change in default attribution model means for advertisers and businesses.

Media platforms have long maintained their contributions in influencing consumers about the brands and products they purchase. 

How will the recent attribution shift affect these platforms? 

Think about Hulu’s path and the ad products Disney+ and Netflix will sell to advertisers wanting to tie conversions to their media placements. 

Think about Pinterest and Snap’s challenges when cutting ad budgets. 

What is the first to go? Conversion drivers at the end of the funnel, like search, or awareness-based tactics, like sponsored stories? 

This discussion is what makes attribution such a timeless discussion. 

Google has the same problem as all these companies but within their own properties. 

While Google has shown its ability to grow its search business consistently in almost any economic condition, its real growth opportunity comes in non-search tactics (YouTube, Gmail and Google Display Network). 

Inventory is essentially limitless in these areas, unlike search. This is why this change is so important for Google and advertisers. 

Let’s start by breaking down attribution and the different models that indicate how “credit” for conversion is applied. The six common attribution models are:

Moving to a DDA model will create conversions for keywords that are Attribution > Model Comparison. 

This tool will allow advertisers to see the variances between the models. Using these comparisons, you can help communicate and educate your internal team about the potential impact.  

Overall, data-driven attribution, while not a silver bullet solution completely, provides better insight into various ad types and keywords and how they impact the customer journey. 

This will allow your brand to allocate budget and resources better – ultimately optimizing your business to maximize results.

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