Recently, Google announced that they will no longer provide four of the attribution models that are essential for data-driven marketing. First-click, linear, time decay, and position-based attribution models will all be deprecated from GA4 later this year. This decision has implications for users of Google's platform, as they will now have access to only one attribution model outside of the data-driven attribution option: last click.
This move is yet another power grab from the Analytics monopolist; controlling around 90% of the market, they are forcing as many users as possible to trust their black box and allow them to mark their own homework when it comes to advertising performance.
It’s time for marketers to wake up. GA4 is free for a reason and attribution and analytics is getting muddier for a reason. Google will sell way more ads abusing their analytics monopoly position. Marketers who care about data accuracy, or use multiple platforms for advertising, have to move to impartial analytics solutions if they want to be able to optimize effectively.
In this article, we will discuss the importance of attribution models in digital marketing, the implications of Google's decision, and the need for unbiased, third-party options that provide access to all attribution models in a transparent way.
What are Attribution Models?
Attribution models are used in digital marketing to determine which channels or touchpoints in a customer's journey contribute to a conversion. In other words, attribution models help to answer the question: "Which marketing efforts are responsible for driving sales or conversions?"
There are different types of attribution models, including Last Click, First Click, Linear, Time Decay, and Data-Driven Attribution. Each attribution model has its unique way of assigning credit to various touchpoints in the customer journey, allowing marketers to better understand the impact of their marketing efforts on conversions. We have more detail on that here.
The first-click, linear, time decay and position-based models will all be removed in Google Ads and Google Analytics at the start of September. Prior to the sunset, newly created conversions in these attribution models will no longer be available in GA4 from May and Google Ads from June.
A Google spokesperson said the decision was made due to “increasingly low adoption rates, with fewer than 3% of conversions in Google Ads using these models”. So essentially because most GA users use the most basic features and don’t optimize their marketing using the full picture, they have chosen to remove the full picture for everyone.
The Huge Limitations of Google's Data-Driven Attribution
Google's data-driven attribution model uses machine learning to assign credit to different touchpoints in a customer's journey based on historical data. While this can be useful, it also presents some limitations. For one, the data used to train the machine learning algorithm may be biased towards Google's own platforms (from what we can tell, it is completely biased). This could lead to an overemphasis on Google's platforms at the expense of other marketing activity that could be driving conversions.
While the DDA model can provide valuable insights, and some additional insights when it comes to tracking Google performance, it is important to recognize that it is not a one-size-fits-all solution. Different businesses have different marketing strategies and customer journeys, and therefore require different attribution models to accurately assess the impact of their marketing efforts.
DDA is a black box, meaning it is impossible for marketers to understand how the model is assigning credit to different touchpoints. This lack of transparency means that users are flying blind almost as much as if they were not using attribution at all.
Users Need to Switch to Unbiased, Transparent Solutions
Investing in unbiased, third-party options will provide ROI many times over. Having access to all attribution models in a transparent way is crucial for optimizing budgets and marketing campaigns effectively. Using a third-party attribution platform (of course we recommend Incendium) that offers a range of attribution models allows marketers to select the model that best suits their business needs and marketing strategy, and to properly compare activity.
Independent platforms are not biased towards any specific marketing channel or activity, and therefore provide a more accurate representation of the impact of all marketing efforts.
If your business relies on accurate, impartial web analytics and attribution data, you need to prepare to sunset your reliance on GA. Google's Data-Driven Attribution can provide valuable insights if you are a Google only advertiser, however if you have a mix of marketing channels and platforms, GA4 should not be your primary source of truth. To make decisions on budget allocation, landing page or campaign optimizations, you have to have impartial attribution you can configure to your business.
One-size-fits-all doesn’t work, and nor does trusting a 90%+ market share monopoly (in both analytics and online advertising) to act honestly when marking its own homework.