In some cases, clients report that GA4 is significantly under-reporting revenue for non-Google channels such as affiliate, compared to their previous Google Analytics version. These errors seem specific to GA4 and\/or Google\u2019s Data-Driven Attribution (DDA)<\/a> model. We\u2019re not seeing these changes within CJ tracking or reporting, which remains accurate and stable.<\/strong><\/p>\n\n\n\n We understand that Google has not acknowledged this issue, so we created the following guide to help our clients navigate internal conversations around GA4. While a migration to Google Analytics 4 should\u00a0not<\/strong>\u00a0have any effect on CJ\u2019s ability to track or report publisher value, we understand that it\u2019s important to explain any significant shifts in Google Analytics to the rest of your organization.<\/p>\n\n\n\n This is an emerging issue, to which Google has not yet responded. As such, this guide is based on CJ\u2019s best understanding of the issue. We will update as Google provides more information.<\/p>\n\n\n\n Within this guide, we link to Google documentation wherever possible to help you access their relevant guidance; however, Google\u2019s documentation relating to GA4 is not comprehensive. In some cases, we may point to non-GA4 documentation that we believe is still relevant.<\/p>\n\n\n\n It seems that a notable number of the issues are attributable to Google’s significant expansion of their Data-Driven Attribution (DDA) model in GA4, and the issues attached to that model when applied to non-Google channels. We explore these issues in the guide below:<\/p>\n\n\n\n DDA documentation states that it is designed to \u201clook at all the interactions\u2026. on your Search, Youtube, Display and Discovery Ads<\/a>\u201d<\/a>. As currently designed, DDA does not accurately track or attribute revenue for non-Google channels, including email, search, or affiliate.<\/p>\n\n\n\n This means there are significant issues that arise within DDA when applied to some or all non-Google channels. This could result in large data gaps and inaccuracies in DDA\u2019s revenue attribution.<\/p>\n\n\n\n Google states in their documentation that there are common scenarios where they cannot provide measurement for valid data. This particularly applies to gathering crucial data on conversion paths.<\/em><\/p>\n\n\n\n DDA compares different conversion paths <\/em>to infer the value of the channels within that path. To do so, DDA requires at least 400 conversions per unique path over 30 days. If this threshold isn’t met, all journeys which took that path are discarded from DDA. Google acknowledge that these journeys are valid, but that their model is unable to measure them (see \u201cInsufficient data to generate a model\u201d)<\/a>.<\/p>\n\n\n\n Put simply, GA4 discards these journeys because the DDA model is not able to reach statistical significance for that conversion path. Because Google increased the number of possible touchpoints so significantly in Google Analytics 4, the number of possible unique paths increased exponentially, and the likelihood of any path leading to 400+ conversions is much lower vs previous versions of GA.<\/p>\n\n\n\n CJ looked at our data for over 1,200 clients. Google\u2019s methodology would likely exclude ~98% of affiliate conversion paths from its DDA model. <\/strong>CJ observed that only 1.4% of conversion paths containing an affiliate touchpoint resulted in 400+ conversions.<\/p>\n\n\n\n When DDA rejects these valid journeys, they are no longer measured using the DDA methodology. Instead, Google uses \u201caggregate data<\/a>\u201d to make assumptions about the value of those interactions, and does not share how these assumptions are made.<\/p>\n\n\n\n Conversion paths from high-volume channels (i.e., Google-owned channels such as display and search) are more likely to pass this conversion threshold, and therefore their journeys are less likely to be ignored by DDA.<\/p>\n\n\n\n Google-owned channel interactions are more likely to be assigned value in DDA. Google collects more data on ad interactions for Google-owned channels, and they provide features that measure Google interactions with more consistency and preference than non-Google channels.<\/p>\n\n\n\n While DDA includes impression and video view data from its own channels, Google ignores all impression and video data from non-Google channels.<\/a><\/p>\n\n\n\n The inclusion of Google-only impression and video data creates far more touchpoints for Google-owned channels than non-Google channels. This creates significant potential for bias in DDA results.<\/p>\n\n\n\n Google clicks are recorded using Google Click Identifier (GCLID), a unique parameter that is only <\/strong>available for Google channels and can be \u2018auto-tagged\u2019 onto any Google-owned links.<\/p>\n\n\n\n Google describes auto-tagged clicks as providing \u201cmore detailed reporting\u201d and \u201celiminating errors\u201d<\/a>. However, Google requires non-Google channels to use their less reliable \u201cmanual tagging\u201d solution (commonly known as UTM Parameters) for identifying clicks in Google Analytics 4. This design choice means that GA4 tracks Google-channel clicks more reliably, and with more detail, than other channel clicks.<\/p>\n\n\n\n When a user click occurs where \u201cgclid\u201d and UTM parameters are present, GA4 ignores the UTM parameters<\/a> and favors the \u201cgclid\u201d. This means that when there is ambiguity around whether a non-Google channel or a Google channel drove an interaction, the Google channel will always win.<\/p>\n\n\n\n In prior versions of Google Analytics,\u00a0the option existed to switch this auto-tagging bias off<\/a>\u00a0and ensure Google counts non-Google click data at all times (see \u201cYou need to use auto-tagging for non-Analytics purposes\u201d). They acknowledged that this option was required to \u201cavoid data discrepancies\u201d in their Analytics products. Google removed this crucial option in Google Analytics 4.<\/p>\n\n\n\n Google\u2019s current design for GA4\/DDA contains inherent and unavoidable biases toward Google-owned channels. Google\u2019s own documentation alludes to such biases. CJ\u2019s data indicates that DDA is not able to provide reliable measurement on the affiliate channel.<\/p>\n\n\n\n With the current methodology, you should not use Google\u2019s Data-Driven Attribution model to measure the affiliate channel, particularly if you are using the updated version of DDA in GA4.<\/p>\n\n\n\n CJ has robust tools available for measuring the value of your affiliate channel, including\u00a0Cross-Channel Customer Journey<\/a>\u00a0reporting, Channel Incrementality tools,\u00a0Competitive Benchmarking<\/a>, and more. These tools are available in-platform and can be used to reliably derive the value of the channel, your partners, and your strategies.<\/p>\n\n\n\n For clients looking to understand a deduplicated view of all channels\u2019 performance using GA4, last click is currently the most reliable methodology provided by Google.<\/p>\n\n\n\nCJ’s Position<\/h2>\n\n\n\n
Why This Shift is Happening<\/h2>\n\n\n\n
If you were <\/strong>not <\/strong>using Data-Driven Attribution in your previous GA version<\/strong><\/h3>\n\n\n\n
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If you were using Data-Driven Attribution in your previous GA version<\/strong><\/h3>\n\n\n\n
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A Guide to Google Data-Driven Attribution & Non-Google Channels<\/h2>\n\n\n\n
DDA Was Designed to Measure Google-Owned Channels<\/h3>\n\n\n\n
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Google terminology used in this section:<\/strong><\/h3>\n\n\n\n
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Issue 1: Google Acknowledges Potential Gaps in DDA Methodology<\/h3>\n\n\n\n
Issue 2: Interactions with Google Channels May Be Given Preference in GA4<\/h3>\n\n\n\n
Google Impression & Video Measurement<\/strong><\/h3>\n\n\n\n
Google Click Measurement<\/strong><\/h3>\n\n\n\n
<\/h4>\n\n\n\n
CJ\u2019s Viewpoint: How Does This Apply to Your Affiliate Program?<\/h2>\n\n\n\n
GA4 Best Practice: Alignment of Methodology<\/h2>\n\n\n\n
If your previous version of Google Analytics was set to Last Click:<\/h3>\n\n\n\n