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    Data-driven attribution: Getting started with Google Analytics 4

    The arrival of Google Analytics 4 understandably has people nervous. Using its increased capabilities means learning new processes and thinking about things in new ways. We’re here to help. Working with Colleen Harris, head of business intelligence and reporting strategy at Sincro, we’ve put together a multi-part guide to getting started with GA4. See below for our previous installments.

    Data-driven attribution (DDA) is one of GA4’s biggest upgrades. It uses AI-based algorithms to determine which user touch points were most important for a conversion.

    “It’s really the ability to have data science done without having to hire a data scientist and without having to really be a very technical person,” says Harris. “It’s gonna let you do probability modeling like this, attribution modeling like this.”

    Dig deeper: Is Google Analytics going away? What marketers need to know

    DDA looks at the sources, mediums and campaigns a user interacted with and tries to determine which had the most impact. It does this by using a weighting system to assign credit to the different parts. 

    Data-driven attribution: Getting started with Google Analytics 4
    Image courtesy of Google Support

    While all this makes for a more flexible way to examine conversion data, it also makes the reporting of it more complex.

    In GA4, as In Universal Analytics, the basic marketing traffic source dimensions are channel grouping, source, medium and campaign. However, now there are three types of each dimension. Where UA had a single source dimension, GA4 has a session source dimension, a first user source dimension and the standalone source dimension.

    Each of these has a different scope and can provide different information depending on the metrics you use.

    GA4 also has Universal Analytics’ attribution model options — last click, first click, linear, position based and time-decay. You can make them or the new Data-Driven Attribution your primary model.

    Getting started with Google Analytics 4

    Redefine success

    Setting up goals

    Setting up your website

    Data-driven attribution

    GA4 has a model comparison tool which can be very helpful in learning DDA. Try comparing it to a measure you’re familiar with, like last non-direct click. Adding different source dimensions will demonstrate what it can do and maybe new ways to think about what you need.

    “What this really is is the AI’s at Google are telling you all these different pieces, and these are going to be customized based on your own data,” says Colleen Harris. “It’s not some sort of generic, ‘Everybody did this or something like that.’ It’s going to show you all the things that they, the AI machines, deem most important.”

    And we’ll be looking at how to customize this in our next installment.

    Also, a helpful thing to keep in mind from Colleen: “Even those of us who are thought leaders, industry experts on GA4, we’re all figuring this out, too. It is a plane being put together at 30,000 feet. So, don’t feel like you’re alone in this lack of understanding or frustration.”


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