Plenty of words have been spilled on the tactical benefits and data-cleanliness necessity of moving from Universal Analytics to GA4 sooner rather than later. Those effects are real, and they’re important, but they don’t account for one of the most promising outcomes of the move to GA4: the long-awaited demise of last-click attribution.

In this post, we’ll put GA4’s approach to attribution in focus: what’s changed, what’s better, what you might miss, and the strategic shift Google is not-so-gently encouraging marketers to take in a cookie-less future.

GA4 Attribution vs. Universal Analytics Attribution

GA4 provides its users with a new cross-channel, data-driven attribution model that uses an algorithm to assign credit across touchpoints in a user’s journey to a conversion. If this sounds relatively complex, it is – it’s less transparent and linear than UA’s most popular attribution models: last-click, first-click, and evenly weighted attribution.

In other words, it’s a big (forced) transition for marketers used to simple measurement. Whether or not that sounds to you like a good thing – and I’m in the good-thing camp – it’s where things are headed, with the July 1 implementation deadline coming up quickly.

What GA4’s Attribution Functionality Does Better

In GA4, marketers can:

Upload offline conversions – phone calls, in-store purchases, CRM qualification actions, etc.

Track users across websites and apps in a unified property

Count any event as a conversion. GA4 uses event-based tracking (taking the perspective of one user and one journey) rather than session-based tracking, making it much easier to define almost any action on your site as a conversion and see attribution modeling on those conversions. In GA4, these events and conversions can have far more detailed parameters assigned to them, unlike the limited set of Category, Label, and Value parameters we could assign to events in UA.

These upgrades range from detail-focused (the ability to track a greater, more nuanced set of events without manual rigor) to business-critical. Brands in many verticals rely on offline conversion tracking to understand the ultimate value of customers and the engagements that led to acquisition. The ability to feed that data back into the platforms gives advertisers more precision in bidding for those engagements – and the audiences who resemble their most valuable users.

What You Might Miss in the Transition to GA4

Marketers who are used to having manual controls are having a tough go lately; from Facebook’s AI-heavy algorithm to Google’s push toward Performance Max and campaign automation, controllable levers are giving way to machine learning in the face of privacy regulations and an eventual cookie-less future.

Put simply, GA4 is attempting to use machine learning to fill in some blank spots. While Google is claiming near-perfect accuracy with its reporting, GA4’s attribution models require a leap of faith for marketers and site/app owners to fully trust its data – particularly if you’re skeptical enough to suspect Google could be over-crediting actions on its own properties.

What’s GA4’s Most Promising Attribution Model?

The cross-channel data-driven model is the future; marketers might as well embrace it sooner rather than later. It uses machine learning to create a much more intelligent, nuanced view of the touchpoints that went into a conversion, and its dynamic nature attributes more or less credit to channels based on their effectiveness in real time.

Where Is Google Leading Us?

Google is leaning more heavily on AI and machine learning to not only fill in missing data but to provide an even better way of thinking about attribution than we have in the past. As we all become more and more comfortable with the integration of AI into our everyday lives, any concerns about Google’s use of it in online analytics will diminish.