Say Goodbye to These Google Ads Attribution Models

In the ever-changing world of digital advertising, staying ahead of the curve is essential. Google Ads and Google Analytics are at the forefront of this transformation, and they've recently made some significant changes to their attribution models.
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In this blog post, we’ll delve into the evolving landscape of attribution models and explore why first-click, linear, time decay and position-based models are on their way out.

The Rise of Data-Driven Attribution

Traditionally, rules-based attribution models assigned values to advertising touchpoints based on predefined rules. While these models served their purpose, they lacked the flexibility required to adapt to the dynamic nature of modern consumer journeys. This prompted Google to introduce data-driven attribution as the default model in Google Ads and Google Analytics 4.

Data-driven attribution leverages the power of Google AI to analyze the impact of each touchpoint on conversions. It takes into account the entire customer journey, acknowledging the various interactions a user has with your ads before making a conversion. This holistic approach allows advertisers to gain valuable insights into the effectiveness of their campaigns at every stage.

When combined with auto bidding, data-driven attribution can significantly enhance advertising performance. This means your ad spend is optimized based on real-time insights into what’s working and what isn’t. The result? Improved ROI and a more efficient allocation of resources.

The Decline of Traditional Models

Today, less than 3% of Google Ads web conversions rely on first-click, linear, time decay, or position-based attribution models. The writing is on the wall for these models as advertisers increasingly turn to data-driven attribution for its adaptability and accuracy.

Data-driven attribution paints a more accurate picture of how different touchpoints contribute to conversions. It recognizes the changing behaviors of today’s consumers, who often interact with ads across multiple devices and channels before converting. With this level of granularity, advertisers can make informed decisions about their marketing strategies and budget allocation.

The Transition Timeline

To align with these changes, Google Ads will implement a transition plan. Starting in June 2023, advertisers will lose the ability to select first-click, linear, time decay, and position-based attribution models for conversion actions that do not already use these models.

Then, in September 2023, any conversion actions still employing these traditional models will automatically switch to data-driven attribution. However, Google Ads ensures that advertisers retain some degree of choice. If data-driven attribution isn’t the right fit for your campaign strategy, you’ll still have the option to use the last-click model, providing flexibility within the evolving landscape.

The Impact on Reporting

These changes are not limited to attribution model selection. The transition extends to reporting throughout Google Ads, including the Overview page and the Model comparison report within the Attribution tab. Advertisers will notice that first click, linear, time decay, and position-based models will be removed from these reporting interfaces.


As the digital advertising landscape continues to evolve, adaptability and precision are paramount. Google Ads and Google Analytics 4 have recognized this need by making data-driven attribution the default model, effectively phasing out first-click, linear, time decay, and position-based models. Advertisers must embrace these changes to stay competitive and ensure their campaigns are optimized for success in the ever-evolving world of online advertising. By leveraging data-driven attribution, advertisers can gain a deeper understanding of their customer journeys and make data-informed decisions that drive better results and maximize their advertising investments.

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