Since the announcement of the new reporting mode in Google Analytics (GA4) in July 2019, it has been clear to digital marketing and e-commerce professionals that the way we capture and analyze data about online promotion results will transform with the updates to Google Analytics. After this version started being used alongside Universal Analytics, we saw in numbers what this change in data collection and reporting entails.

It’s a new era, and Google explains this through the differences between UA vs. GA4 metrics and the types of data and reports accessible in both versions.

In this new context, significant changes are observed in the attribution of results to various channels in Google Analytics. Globally, online stores report lower volumes of conversions attributed to non-Google channels (Meta Ads, TikTok Ads, Organic Social Media, and other traffic sources), including affiliate marketing promotion. These discrepancies are specific to GA4 and the Data Driven Attribution (DDA) model and do not affect the accuracy and stability of tracking done through affiliate links generated in our platform. To support the understanding of these differences, we go into more details below.

Impact of GA4 on Conversion Attribution or How Online Store Reports Look Now

It’s important to mention that Google has not published a clear position on this subject yet. As official information becomes available, we will update this material.

The observed discrepancies are largely the result of the widespread adoption of the Data Driven Attribution (DDA) model in GA4, leaving behind the Last Click model used in Universal Analytics. There are three factors impacting data:

1. Credit for Conversions: This model gives credit for online store conversions to each channel that contributes to converting a visitor into a buyer based on the impact of each channel, calculated from various data points such as:

• Interactions with ads from different online marketing channels (clicks, video views, etc.);

• Purchase scenarios (Conversion Paths), i.e., the type and number of interactions users make until conversion;

• Comparisons between different paths through which a user makes a purchase;

• Recognizing scenarios where a particular online marketing channel generates more interactions, but not necessarily the most conversions, to eliminate so-called Channel Bias;

• Continuous Machine Learning, as it is a dynamic model that becomes more accurate as it collects and analyzes more data.

In short, while the Last Click model considered the last channel a user interacted with before a conversion, the Data Driven model recognizes the merit of all interactions in the User Journey, focusing on interactions with Google’s own channels. This means data interpretation is more nuanced, and any comparison between Universal Analytics and GA4 data becomes irrelevant.

Example from Google Documentation on How the Data Driven Model Works

You can analyze an online store’s data comparing attribution models (e.g., Last Click vs. Data Driven) in the Advertising section of GA4. This shows whether the results attributed to the last channel buyers interacted with differ from those attributed to the channels with the most significant impact on purchase decisions (Data Driven). Example from the Demo GA4 account made available by Google:

The Conversion Paths report in the Advertising section of GA4 details the channels’ impact on conversions across three pillars: first-contact clicks, intermediate clicks, and clicks closest to the purchase moment.

Challenges with Data Driven Model Applied to Non-Google Channels

From the available analyses in digital marketing and Data Analytics, the Data Driven model encounters difficulties when applied to non-Google channels. It is primarily designed for Google-owned channels and is not optimized to track or attribute results accurately for non-Google channels such as email marketing, social media marketing, or affiliate marketing. Even with the addition of tracking parameters (UTM) in affiliate campaigns, scenarios exist where parameters are ignored, and results are attributed to the channel itself (Google Ads, Google Organic Search). This prioritization of Google channels in attribution can generate significant discrepancies between GA4 reported data and reports from our platform.

GA4 Attribution Model (DDA) vs. Affiliate Link Tracking

The attribution model used by GA4 (DDA) and the method of tracking promotion results through affiliate links are different. To attribute a conversion, the 2Performant tracking system considers any real interaction (click) with the online store of a user who makes a purchase within the cookie life period (which can be set in the 2Performant account). This tracking system enables a unique solution for promotion at cost per real, confirmed sale delivered and paid for by the customer. Its goal is to provide transparency and predictability for the results and investment made to generate those results.

Additionally, GA4 composes reports from data sourced from all traffic-generating channels for an online store, considering all user interactions with the site, from all sources. Therefore, we are talking about different methodologies and reports.

Recommendations for Navigating These Changes:

1. Ensure that Google Analytics 4 is correctly implemented to avoid potential discrepancies caused by technical issues.

2. Monitor the reports available on the platform for a complete and clear understanding of the performance of campaigns run by 2Performant partners.

3. Follow other important indicators in GA4 reports that can clarify your business’s evolution, such as the volume of direct traffic and its conversion rate, the performance of Google channels over time as you start campaigns on new channels or through affiliate marketing, and the impact of non-Google channels in the first two stages of customer knowledge (Early Touch Points and Mid Touch Points).

For an applied opinion on the subject, we spoke with one of the top Business League players. Cătălin Radu (CataR) provides a perspective shaped by working with over 200 GA4 accounts for affiliate sites, as well as online stores and commercial sites:

In the context of affiliation, the differences between reports we have observed create frustrations for all involved. Stores see a significant discrepancy between data recorded in Google Analytics and those reported by the affiliate network, with the network’s efforts for accurate conversion tracking and attribution being distorted by GA4’s underreporting for such channels. The most affected are the affiliates, who spend time, budgets, and expertise promoting advertisers in a performance marketing system and find themselves having to explain these discrepancies.

To understand this situation and provide a complete explanation to our clients, we analyzed the GA4 vs UA methodology and the issues reported by other online stores worldwide in this case.

First, it’s important to emphasize that GA4 represents a significant change from UA. Its reporting model is event-based and not session or page view-based, as was the case in UA. This means GA4 is more flexible and can track a wider range of user interactions, but it can also lead to discrepancies in how visits and conversions are accounted for.

When comparing data from GA4 with those from 2Performant, it’s essential to understand that these systems have different functions. GA4 offers a holistic perspective on user behavior and their journey on the site, while affiliate platforms focus on the direct attribution of sales and conversions through tracked links and conversions attributed directly through these links.

Types of interactions tracked and reported by GA4 throughout the entire browsing process:

• Page views

• Ad clicks

• Content interactions

• Ecommerce transactions

• Actions that do not generate a page load (scroll events or external link clicks)

Types of interactions tracked and reported by 2Performant:

• Tracking clicks on affiliate links

• Direct attribution of conversions made through these links (last click)

The discrepancies between the data can be frustrating, but they reflect the complex nature of a customer’s journey online. In an ideal world, we should use these tools complementarily, using GA4 to understand the broad customer journey and affiliate platforms to efficiently attribute direct conversions to specific sources. Thus, these two systems can report the same transactions or conversions differently, as each has a unique methodology for attributing the role of conversions.

Many online stores have reported discrepancies between clicks and conversions reported by affiliate platforms and those recorded by GA4.

Among the reported issues are:

• Underreporting of non-Google channels (such as social media and affiliate channels) in GA4

• A preference of the DDA model from Google for Google-related products, such as Google Display Ads

The Data-Driven Attribution (DDA) model of Google Analytics 4 has been observed to favor, in some cases, Google products and services such as Google Display Ads. This suggests that in the DDA model, contributions to conversions from Google channels may be overvalued compared to external channels such as affiliate platforms. Therefore, this can lead to discrepancies between data reported by GA4 and those reported by affiliate platforms.

Furthermore, a large portion of traffic is labeled as “direct,” with a loss of data from the marketing channel that led to the consumer’s visit. These problems are partly attributed to GA4’s data-driven attribution model and issues related to the use of UTM tags for non-Google channels.

As GA4 continues to evolve and this new analytical context becomes clearer, we remain close to you on our blog, social media, and newsletter for updates. Happy converting!

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