When it comes to digital marketing, attribution model strategies are a must. While credit for online conversions is often given to the last ad a customer clicks before buying, other ads may have influenced that decision, and attribution models can help you get a comprehensive picture of the path to purchase.

To really understand the customer journey (and the meaning of attribution to your campaigns), you have to recognize that conversions are usually preceded by multiple interactions with a website or app. Knowing the impact of each of those touchpoints can make a huge difference to your advertising strategy, which is where marketing attribution and attribution theory come in.

Since Google Analytics 4 (GA4) has now officially replaced Universal Analytics (UA), it’s time for search marketers to investigate how GA4 attribution models work, the differences between the two analytics solutions, and what to expect when comparing metrics between these two models.

For example, UA used to give conversion credit to the last click in a conversion journey, though marketers could conduct additional attribution analysis as well. While GA4 offers fewer attribution models to choose from, you can get detailed user acquisition reports that include metrics like engagement time, engaged sessions, and first user medium (the means of acquiring users to your site or app).

Another big upgrade within GA4 relates to the three scopes of source dimension, namely user, session, and event. For context, UA only included session scope in its source dimensions.

You can find attribution models in GA4 under the attribution reports session, and users can select an attribution model used by GA4—along with a conversion window for specific website properties—in their reports. Before you dig in, though, let’s talk more about the attribution models you’ll find in Google Analytics 4 today.

Attribution Models Available in GA4

In Universal Analytics, there were 6 attribution models available to digital marketers:

  1. Data-driven Attribution Model
  2. Last click Attribution Model
  3. First click Attribution Model
  4. Linear Attribution Model
  5. Time decay Attribution Model
  6. Position-based Attribution Model

These models were grouped into 3 main attribution types: Data-Driven, Cross-Channel, and Ads-Preferred. In GA4, however, first click, linear, time decay, and position-based attribution models were discontinued because, as Google notes, they “don’t provide the flexibility needed to adapt to evolving consumer journeys.”

So what’s left? There are now two GA4 attribution types: data-driven and last click (both for paid and organic, and Google paid channels). These revenue attribution models allow marketers to understand how different customer touchpoints influence conversion outcomes.

Getting a handle on which of these is the best fit for your cross-platform attribution strategy can make all the difference when you’re analyzing ad performance and focused on conversion rate optimization for your brand.

1. The Data-Driven Attribution Model (DDA)

It’s safe to say the machine learning-based data-driven attribution GA4 model, introduced by Google in 2021, is currently the most prominent and the default model for GA4. It’s unlike other attribution models in that DDA looks at multiple marketing touchpoints in the customer journey to determine which had the biggest impact on the conversion. DDA uses artificial intelligence (AI) to process historical data from your account, and incorporates a broad variety of data from your site visitors—like device type and the order in which ads are clicked—for attribution optimization.

Despite its benefits, the DDA attribution model might not be the best attribution tracking solution for marketers who advertise heavily on platforms outside of Google Ads. One of its limitations is that attribution assignment remains vague, so small variations in data can lead to completely different outcomes, making it difficult for marketers to identify trends.

It’s important to note that while last click models assign 100% of the credit to a single channel, DDA may assign portions of the credit to different channels even within a single conversion. As an example, last click may give 100% of the credit for a single conversion to paid search, DDA may assign 25% to paid search, 25% to social and 50% to organic search

2. Last Click Attribution Model

The alternative is the last click attribution model, which places all the value on the last touchpoint the customer engaged with before converting. This model is used in both cross-channel (the default reporting attribution model for GA4) and ads-preferred attribution, although it functions a little differently with each.

With cross-channel attribution, the conversion credits are given to the final non-direct click that precedes the conversion, whether or not it is a Google Ad. With last click attribution within the Ads-Preferred type, though, the full credit for the conversion goes to the last click on a Google Ad even if it wasn’t the real last touchpoint. If the path doesn’t contain a Google Ad, 100% of the credit is assigned to the last touchpoint of the conversion path.

If you advertise on other platforms, like Taboola, rather than just on the Google Ads platform, choosing the ads-preferred type could be risky. That’s because it may appear that your paid campaigns have a lower conversion rate than Google Ads, when, in fact, Google Ads are getting additional credit. On the flip side, if Google Ads is your main source of revenue, you might find this model to be very useful.

Picture this: Jane sees an ad you’ve placed on Instagram. She’s intrigued, and visits your site to learn more. That night, she visits your site again as she continues to consider making a purchase. A few days later, Jane sees one of your Google ads, clicks through, and finally converts. With last click attribution, full credit for that sale would go to Google, when in fact there were several other paid and organic touchpoints involved in the conversion.

It’s always important to understand the impact of each touchpoint on your conversions. But you should also be using an attribution model that’s a good fit for your marketing strategy and campaigns.

Conclusions on GA4 Attribution Models

It should be clear by now that attribution models are hugely helpful when it comes to analyzing the digital landscape and the value of your ad investments. These models empower advertisers to make more educated and effective marketing decisions and maximize their ad budgets.

All of that said, digital marketing and online brand interactions are more than just touchpoints. Consumer behavior can vary dramatically based on countless factors, some of which aren’t as visible to the naked eye. Relying only a single attribution model could be risky, since it focuses entirely on a particular touchpoint—or combination of brand interactions—without considering the conversion journey as a whole.

Mobile analytics strategies should be a consideration for you and your brand as well. With more than 90% of online conversions originating with a mobile interaction (GeniusMonkey), it’s crucial that you gain a deeper understanding of your mobile ad campaigns, including how consumers are engaging with your mobile native advertising. The right mobile attribution strategies can help.

Combining multiple data sources and insights beyond the realm of GA4, like Taboola reporting tools and platforms, could give you a more complete picture of your customers’ behavior and a better understanding of their journey to your site, which in turn can enhance your key performance indicators (KPIs) and overall ROI.

Think of GA4 attribution models as the tip of the iceberg. There’s much more to see below the surface, and Taboola can help.

Interested in learning more about Taboola’s reporting and attribution solutions? Contact us today.

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