Today more than ever, marketers have a range of tools and solutions available to them. One of the most readily utilized tools, Google Analytics, is used on millions of websites. When it was rolled out, Google Analytics 4 (GA4) represented a step forward from Google’s previous Universal Analytics, setting Google’s data-driven attribution model as the default across the Google ecosystem. While Google’s data-driven attribution might sound like the endgame, GA4’s attribution tools still face some hidden constraints that prevent them from delivering comprehensive cross-channel attribution.
In this article we’ll:
- Explain how GA4 attribution actually works and how its Last Click and Data-Driven Attribution Models both fall short.
- Explore how dedicated attribution tools like Roivenue operate differently; plus, how GA4 and Roivenue can strategically complement each other for higher performance and deeper data-driven insights.
GA4 was introduced and built as a behavioral analytics platform. It was designed to help analyze how visitors interact and behave on your website. One component of that has been attribution; while GA4 presents its attribution modeling as an authoritative solution, it’s important for decision-makers to be aware of its constraints and limitations.
For instance, GA4’s Last Touch attribution model is actually not a true Last Touch Model; rather, it is a “Paid and organic last click” or “Last non-direct click” attribution model.
Let me explain.
If a user:
- Arrives via a Social Advertisement, but leaves without a purchase.
- Returns through a Paid Search, but again leaves without a purchase.
- Returns 4 days later directly and converts.
GA4’s Last Touch model will give all the conversion credit to Paid Search, rather than Direct — the true last touchpoint. Direct will only appear if it was the only touchpoint in a user’s journey.
This can be observed when GA4 users compare GA4 results in the UI with data from streaming export to Big Query that does not have any attribution model applied. The last touch from Big Query will have significantly more direct conversions. GA4’s other models, including its Data-Driven Attribution, continue to minimize Direct in its attribution models. Limited customizability available in Google means that there are few options to overcome these pre-set limitations. While some marketers may prefer this set up, as it highlights marketing levers that can be controlled and prevents Direct from swallowing up attribution credit, there is a tradeoff. Because direct is suppressed in Google’s attribution models the contribution of paid channels will be overestimated, especially for lower-funnel channels like Brand Search. Upper funnel campaigns might still be underestimated, as explained in the next part.
In short:
- Google Analytics 4 suppresses contribution of direct in last touch model and data-driven model.
- While helpful for many marketers and performance analysis, there are few options to control this behavior.
- As a result, the contribution of channels may be skewed.
On top of all of this, GA4’s attribution is only as good as the amount of data and inputs it is allowed to see. GA4’s attribution, rooted in a web analytics solution, relies on website visits for its data touchpoints. This effectively means that all the impact of impressions is unaccounted for in its modeling. This significantly limits what credit upper-funnel campaigns can get in GA4. This includes ad campaigns in walled gardens like Meta, TikTok, all RTB, and direct buys you run through DSP platforms. Google only has partial visibility into them. This results in unequal attribution measurements.
When these factors are added together, it causes lower-funnel activity to be overvalued and upper-funnel activity to be undervalued. Marketers who oversee complex multi-channel marketing mixes across all funnel levels need to be aware of the constraints and limitations of attribution models before relying on them for strategic and operational decisions. Relying solely on GA4’s attribution models may not give an insight into true attributed performance.
Multi-Touch Attribution (MTA) tools like Roivenue can step in here and provide clearer perspectives with a laser-eyed focus on providing reliable and in-depth cross-channel attribution. Roivenue ingests more data sources from each marketing platform, strives to measure activity from across the funnel, and allows more flexible and customizable data-driven attribution models.
Roivenue tracks website activity similarly to GA4 but adds multiple methods of customer journey reconstruction to really cover the entire customer journey. Roivenue can track all impressions with a pixel from platforms that support that (majority of DSP platforms, Google Ads and others). On the other hand, there are certain walled-garden platforms like Meta, TikTok, and others that do not allow pixel-based tracking. For these situations, Roivenue downloads granular data directly from each platform’s APIs and combines multiple techniques of matching the platform-reported data with website activity to model the missing impressions. The entire setup can also run in a cookieless mode for maximum privacy. On top of the better reconstructed user journeys, Roivenue also gives clients the option to configure multi-channel data-driven attribution models. With a range of features, including custom touchpoint weights, max journey lengths and others, Roivenue users can have precise control over how different interactions contribute to the final conversion. Rather than completely excluding Direct or Organic traffic, you can increase or reduce the weight of any source, medium, or campaign, allowing countless possibilities when testing the role of upper-funnel or assistive channels. With visibility into upper-funnel platforms and granular control of each attribution model, MTA tools like Roivenue optimize reporting accuracy.
To summarize:
- A dedicated MTA solution typically provides better journey reconstruction and customizable attribution models.
- Roivenue tracks both ad impressions and website visits and assigns fair credit to all types of digital campaigns. Roivenue Synthetic Impressions methodology solves impression tracking in walled gardens and Roivenue Pixel tracking tracks all the other impressions.
High Performing Teams should strive to use both GA4 and Roivenue complementary to unlock the full value of their data. GA4 should continue to be utilized in order to measure visitor experiences. When looking at questions like UX, engagement, and audience discovery, GA4 still delivers some of the most clearly presented insights available. Roivenue on the other hand, should be used to measure Channel and Platform ROI, guide budget reallocations, and plan for growth. Together, GA4 and Roivenue can allow you to shift to a data-driven decision-making workflow for your company.
If you’re interested to learn more on this topic, watch our webinar: Understanding the Customer Journey – From First Click to Checkout. Accurate measurement for tomorrow’s marketing.
