Attribution analysis is one of the more powerful analysis tools you have at your disposal. What is attribution analysis? Simply put, it’s getting an understanding of which digital channels are helping you reach your goals. For example, you’ll want to know if your email channel is helping you convert prospects to customers. To find this information about your attribution analysis you head right over to your conversion data in Google Analytics and see that they’ve mapped the channel attribution for you already. Great! Once you start looking around you realize that your data doesn’t line up with what you are pretty sure is the reality. Why? Because out of the box channel grouping is always wrong.
What is channel grouping?
It’s a collection of sources and mediums that Google buckets together for ease of understanding, like social media or email. The default channels that Google Analytics offers are Direct, Organic Search, Social, Email, Affiliates, Referral, Paid Search, Other Advertising, Display and Other.
How do you do a quick test to see if your channel grouping are wrong?
Navigate to your admin section and then the channel grouping menu item. If what you see is that every channel is listed as system defined, its wrong. Additionally, Google Analytics, if not customized, will classify your data incorrectly. Channel definitions are case sensitive. When manually tagging URLs, use lowercase tags to ensure Analytics categorizes sessions correctly. For example, email campaigns tagged as Email using an uppercase “E” do not match the system definition for the Email channel, which uses a lower case “E”. Even more painfully, you have little control over what other parts of your company do with their tagging and tracking, and even less control over what well-intentioned third parties do when they link to your website, your blog, your content, etc.
What about Google Analytics Tagging?
Google Analytics, depending on when you set it up on your website, uses one of three tracking codes in order of oldest to newest: ga.js, analytics.js, or gtag.js. These codes activate when visitors come to your site, helping Google Analytics understand who they are and where they came from – but only to a degree. The most current version of this code is gtag.js. The default way to include Google Analytics on your website is GTag.
If you want to use any other features such as Google Optimize, Google Ads or Google Surveys, GTag won’t cut it, you’ll still need to set up Google Tag Manager. You can start by setting up GTag, but you’ll eventually need to update to Tag Manager – so why set it up twice? Do it right the first time. If you set up GTag, and then Google Tag Manager you could also risk double counting your data.
What’s the impact of incorrect tagging and attribution?
Channel misclassification leads to poor decisions about resource allocation. If your data is telling you that email isn’t working but paid advertising is, you may decide to double down on your ad campaigns and skip your email campaigns. Did you know? Source and medium are case sensitive (lower case only) so it’s you’re using UTM tags, great! It could still be wrong. If Google can’t figure out what your UTM tag means, it will classify it as other, and you’ll miss out on the data.
Teams may not get credit for their work. Similarly, if your channel data is misclassified, the advertising team will get the kudos, but the team that spends all their time on email marketing may be in hot water when really their channel is the strongest.
You will likely also have unhappy clients. When you’re reporting up to your manager or your client, they may be frustrated that the money that they spent on a certain channel appears to be underperforming. Taking the example of email marketing and paid advertising again, your client may start to pull back funds if they don’t feel like their money is being well spent or achieving a decent ROI, or return on investment.
How do you fix your attribution analysis?
The process to extend Google Analytics, to repair these channel attribution issues, requires more than just random quick fixes. First, you’ll want to get your stakeholders and clients on the same page first about what changes you’re proposing to make. You may need to loop in your IT team to implement the proposed changes. Next, you’ll want to do a tech stack audit to understand what data is being collected and how it’s integrated into Google Analytics. This may involve custom code with Google’s API to make sure that the data is getting transferred correctly. You’ll also need a governance plan for UTM tagging and data collection. This plan is to ensure that everyone is following the standards you’ve agreed upon and so that you can run tests to make sure you’re getting the right results.
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