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8 reasons why Google Analytics does not show all website data

You’ve gone to the trouble of creating a good Analytics setup, but Google Analytics isn’t showing you all the data. You are sure that you should have more page views, but you don’t know why they are not displayed? It’s also quite possible that you’re not even aware that not all web page views are showing up in Google. Since this is much more common than you think, below we will show you possible reasons why you are not seeing all the data in Google Analytics.

1. Browsers Block Tracking

There are internet browsers that block some or all tracking by default. Website visitors who use these browsers would have to activate tracking manually in order to be included in Analytics. Those browsers include Firefox and Safari. Apple is protecting users from “cross-site tracking”, in which users can be identified again and again when they visit websites on which a corresponding third-party cookie is integrated. The Edge browser from Microsoft contains a Tracking Prevention feature that blocks third party trackers and, on the Strict setting, also many ads.

According to Statista, in June 2021 around 18% of all users used Safari as their browser of choice, around 3% used Firefox and 3% used Edge.

2. Operating Systems Block Tracking

Google Analytics mostly does not have a problem being able to track on websites, due to 1st party cookies, but apps may be a different story. Operating systems, especially iOS, are currently implementing options in their phones where you can turn off all forms of tracking in your apps by default. For example, when you install a new app on an apple device it insists on asking users ahead of time to opt in or out of tracking. If you opt out, none of your data will be tracked on your apps. Since iOS 14.6 you can also switch off the tracking in your settings directly. Theoretically any tracking on an iOS phone can be blocked by default. Even though the main targets are trackers like Facebook and Google Ads, Google Analytics could also fall under this category and thus no longer be able to record data.

3. Changes to Your Website

You have made changes to your website and now tracking no longer works? The errors here can be as specific as an HTML element that has been changed or removed. The classic example is: After a relaunch, the tracking codes were not migrated across. Therefore, it is best to test and debug tracking implementations before going live with the new website.

4. Cookies are Denied

Especially in Europe: Here, the General Data Protection Regulation (GDPR) requires that consent for cookies be given for most cookies to be used. Cookies, which are absolutely necessary for the operation of the website, do not require any active consent of the user – the user just has to be informed. On the other hand, the user can decide whether or not to allow marketing, targeting as well as performance cookies (e.g. Google Analytics) to be used.

5. Ad Blocker

Most ad blockers allow tracking of Google Analytics data, but almost all of them allow Google Analytics to be added to the block list. Ad blocker usage is around 35% depending on the region (in Europe, as of Dec. 2019). This means your data collected in Analytics may differ from the real result.

6. Tracking Code Implementation Errors

The recommendations for correctly installing the Google Analytics tracking code used to be to implement the tracker at the end of the source code to increase the page load speed. This is now outdated. We now know that due to the delayed execution of the tracking code some user transactions are not captured at all by Analytics. The reason is that users may have left the page before it was fully executed. Therefore, we recommend the asynchronous tracking code from Google: One part of the code goes into the head, the rest into the body. Overall, it is estimated that switching from the old tracker to the new asynchronous code resulted in “data improvements” of 5 to 20%.

7. Dark Traffic

Dark traffic can include offline campaigns in newspaper or magazine ads. If you don’t track how many people come from your offline ad, then it can create a hole in your data. It can prove difficult to track offline campaigns fully, but there are ways to achieve it.

For example, your business is trying to sell coffee machines by running a campaign in a newspaper and now you would like to know how many people came to your website via that specific ad. In this case you could use a discount code or custom short link, which is exclusive to this ad. The discount can be tracked by how often it was used and the link can bring your visitor to a specific landing page, which you can then track. For the link you can even redirect it to a custom campaign with campaign parameters, which you can build in a UTM builder.

In some cases dark traffic is not a problem of missing data but rather of misinterpreted data. How does this happen? Suppose your colleague sends you a link via mail: If you follow this link, Google Analytics evaluates the site access as direct traffic.

You will never be able to fully identify the proportion of dark traffic, but by using UTM parameters, creating a direct traffic segment report in Google Analytics, and optimizing untagged campaigns in your social media, you will have a much better understanding of where your traffic comes from.

8. Error in the GA filter setup

When you set up a Google Analytics Property then you will automatically get an All Website Data View. It is advisable to not alter this View with filters. Generally, it is a good idea to set up a Test View where you can test your newly implemented filters before adding them to the Views that are being used for analytical insight. You also must be careful with using them because once the data is filtered out, it cannot be brought back. The data cannot be adjusted retrospectively. There is a function where you can verify your filter before implementing it. If you did all this and the filters are still not working properly then look at the following two possible issues:

  • Too many filters: Depending on how the filters are set, the filters may prevent your data from being recorded. For example if you use an exclude filter and an include filter, which contradict each other you might end up with no data in your View. All data sent to a given property is visible in all created “unfiltered” Views. So, the correct approach is to add more Views with as few filters as needed. This way your data will not be filtered so much that it becomes unusable.
  • Incorrect order of filters: Another important point to note is that the order of the filters matters. The order can directly affect the data you end up with in the View. The problem with setting up too many sequential filters is that once the first filter is triggered, Analytics will only provide data that matches that filter, leaving only a reduced data set. Therefore you need to be careful about your first few filters, so that you don’t accidentally negatively impact the filters lower in the order. Google Analytics has a function where you can reorder the filters according to what you need.

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