Why is GA4 dropping some
Marketing Attribution

Why Is Google Phasing Out Four Attribution Models?

With the release of GA4, four attribution models are being dropped. In this blog post, we have covered what exactly is happening, why these attribution models are being phased out, and what it means for businesses.


Written By:

Akanksha Akanksha Dass

Date Published: 12th May 2023

21 min read


Akanksha Dass

Manager – Content Marketing

Akanksha is a content marketing expert who strongly focuses on driving a brand’s narrative through modern content marketing techniques. With extensive experience in the B2B world, she has worked for brands like Dell and American Express. She specializes in content, email, inbound, social media, and copywriting. A writer at heart and a marketing technology enthusiast, currently she spearheads a team of intelligent writers, mentoring them with purpose, passion, and empathy.

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Frequently Asked Questions

Marketing attribution models are used to measure the impact of each marketing touchpoint on a conversion. They assign credit or value to different marketing channels or touchpoints based on predefined rules. Attribution models help businesses understand which marketing efforts are driving the most value and optimize their marketing spend accordingly.

Google is phasing out certain attribution models, including Last-Click, First-Click, Time Decay, and Position-Based models, because they have limitations in accurately reflecting the complexity and diversity of customer journeys. These models often assign all credit to the first or last touchpoint, neglecting the contributions of other touchpoints. They do not account for customer behavior across multiple touchpoints and devices, leading to inaccurate data and poor marketing decisions. Google aims to provide more precise, accurate, and privacy-centric insights by making data-driven attribution the default model, which utilizes Google's AI to understand the impact of each touchpoint on conversions.

There are several reasons for Google's changes to attribution models:
Lack of Accuracy: The traditional attribution models, such as Last-Click and First-Click, do not accurately capture the entire customer journey, overvaluing certain touchpoints and undervaluing others. This leads to inaccurate data and suboptimal marketing decisions.
Customer Behavior: Customers now engage with businesses through multiple touchpoints, making it essential to consider the contributions of all touchpoints in the customer journey. Traditional models often focus on one touchpoint and disregard others, resulting in incomplete data.
Cross-Device Tracking: With customers using multiple devices, tracking the entire customer journey becomes challenging for traditional models, which typically track activity on a single device. This can lead to attribution inaccuracies and incomplete insights.
Real-Time Data: Traditional models rely on historical data, which limits their ability to provide real-time insights. Real-time data is crucial for businesses to make informed marketing decisions in a dynamic environment. The new Google Analytics 4 model utilizes machine learning algorithms to provide real-time insights into the customer journey.

The timeline for phasing out the attribution models is as follows:
May 2023: Linear, Time Decay, First-Click, and Position-Based models will not be available for new conversion actions in Google Analytics 4 properties.
June 2023: Linear, Time Decay, First-Click, and Position-Based models will not be available for new conversion actions in Google Ads accounts.
September 2023: Google will sunset these four attribution models in both Google Analytics 4 and Google Ads.

Data-driven attribution is considered important because it provides a more accurate representation of the customer journey. It considers the contributions of all touchpoints based on data analysis and machine learning algorithms, rather than relying solely on predefined rules. Data-driven attribution offers more precise and actionable insights into how marketing campaigns influence conversions, allowing marketers to allocate their marketing budgets more effectively. Without data-driven attribution, marketers risk investing in the wrong marketing channels or touchpoints, leading to suboptimal results and lower conversion rates. It is also essential for platforms like Google to ensure relevant ads and campaigns for users to maintain engagement and drive revenue.