Correctly implemented, attribution provides us with a window into how our marketing efforts have succeeded or failed. There are various tools to measure attribution along the customer journey, but the most common attribution tool may be the first line of attribution — Google Analytics.
While the promise of Google Analytics’ insights is great, attribution is only as accurate as your Google Analytics tagging. For Google properties, such as Google Ads, it’s not necessary to manually tag destination URLs because Google automatically tags them. For other platforms, however, tagging is necessary to pass important campaign information from the marketing platform into Google Analytics.
But if the data sent to Google Analytics isn’t accurate, then marketers run the risk of making flawed assumptions based on this data. My team relies on the data we glean from Google Analytics to demonstrate the value of various channels and initiatives. However, we’ve found that nearly every client, from startups to global enterprise companies, has errors with Google Analytics data input, thereby affecting their attribution. These are the four most common errors I encounter that can skew your Google Analytics attribution data.
1. Tag Capitalization Mistakes
Google Analytics tags are case sensitive, meaning that a UTM (Urchin Tracking Module) source of “Forbes” is different than “forbes.” While initially, this may not seem like a major issue, it can cause data segmentation and lead to incorrect assumptions about site traffic.
The fix? First, adopt a tagging nomenclature throughout your organization. Ensuring that everyone is using the same tags will reduce errors in reporting.
If you do find errors in your tagging, you can fix them going forward with search and replace filters. However, filters only work for data collected after they’re set.
2. Improper Tagging Within Your Website
Companies often inadvertently overwrite their valuable source and medium data by resetting the UTM source and medium tags when a visitor interacts with various elements on the website. For example, if a marketing team is measuring clicks on a banner graphic, they might reassign the UTM source and medium tags when a visitor clicks on the banner.
However, UTM source and medium tags weren’t designed for this use. A website is essentially a piece of content — it has no source or medium. The source and medium are the marketing channels that brought the visitor there. By reassigning source and medium tags once a visitor arrives at your website, you lose all the valuable information about how a visitor from a particular channel interacted with your website and possibly completed goals after that reassignment. Generally, I advise avoiding UTM tagging of URLs within the same domain.
Have you ever looked at your Google Analytics reports and seen your own domain as a referral to your site? In actuality, your domain really can’t be a referral source to itself, so how does this happen?
Google Analytics ends a session automatically after 30 minutes of inactivity. In the age of prolific browser tabs, this can be problematic because a user may leave a tab open to continue using the site later. For example, if I find an article via an organic Google search, the initial source/medium may be listed as “google/organic.” However, if I leave my browser tab open, stop interacting with the page for 30 minutes and then return later and continue to interact with the site, a new session begins, and my new source/medium might be assigned as a referral from the site itself. However, changing my source/medium isn’t an accurate representation of what occurred. An organic Google search is still the channel I used to find and interact with the site. Just because I took a break from browsing doesn’t change the fact that the organic Google search was the main contributor to my actions.
To fix this issue, add your domain to the referral exclusion list, found in the “Admin” area. Look for “Tracking Info” and then “Referral Exclusion List,” and then add your site’s domain as a referral exclusion. This will begin to attribute your traffic to the original source/medium instead of using your website as a referral source. Note that excluding your domain doesn’t reassign attribution for historical data.
4. Incorrect Channel Groupings
Channel groupings provide a quick way to aggregate all traffic with a certain source or medium together to see how visitors from that channel interacted with the website. For example, “Organic Search” is a default channel grouping. By selecting this channel grouping in a report, we can see how all organic search traffic interacted with the site, regardless of whether the traffic originated from Google, Bing, DuckDuckGo or other search engines.
However, default channel groupings have problems. In addition to typical channels you might expect, such as “Organic Search” or “Referral,” you may see a channel grouping named “(other).” While Google recognizes many sources and mediums and categorizes them appropriately under a channel grouping, it may not recognize all of your sources and mediums.
For example, Google understands that traffic from an organic Bing search is a source and medium of “bingorganic” and places that traffic data under the “Organic Search” channel grouping. But what about sources and mediums your organization uses that don’t fit these standards? Check the sources and mediums listed under the “(other)” channel grouping to determine which of these may need to be recategorized.
Google Analytics allows website owners to create new channel groupings, edit the existing channel groupings and add additional sources and mediums to a channel grouping. By editing the default channel groupings via the “Admin” page in Google Analytics, you can clean up your channel groupings and ensure that your data is correctly reported under its corresponding channel. However, like most settings in Google Analytics, changes to the default channel groupings are not retroactive.
Correct attribution is key to our marketing decision making, and Google Analytics is often the first attribution tool most marketers rely on. Ensure that your Google Analytics is reporting accurately so that you can have confidence in your data and decisions.
Article source: https://www.forbes.com/sites/forbesagencycouncil/2019/10/08/four-of-the-most-common-attribution-mistakes-when-using-google-analytics/