Web Analytics

5 Google Analytics Metrics You Should Check Regularly

Google Analytics Data Check

In Google Analytics, there are key figures that can indicate faulty tracking or even serious problems with your website. You should, therefore, check these valuable metrics from time to time as they can show that your data is unreliable or even useless. In this article, we present five of these indicators:

  • Average page views per session are less than 1
  • The majority of traffic comes from Direct
  • Your own domain is the main referrer
  • The bounce rate is very low (<10%)
  • Significant and persistent variations from the mean for conversions

Average Page Views per Session are Less Than 1

A value less than 1 is certainly incorrect because every visitor to the website has at least one pageview.

This is generally due to faulty tracking. A possible cause may be third-party tools: These often send data such as events and pageviews directly to Google Analytics and, thus, influence the collection of user and session data.

To investigate this problem, we first recommend finding more information about the origin of these “hits”. To do this, identify the issue by following these steps:

  • Investigate which pages are viewed during a session. In Google Analytics under “Site Content” you can analyze this with the help of the “All Pages” and “Landing Pages” reports.
  • Check whether all events actually have a page on which they were triggered. Is the number of hits of both comparable, e.g. on a daily level? Check this using the report “Top Events” and select the secondary dimension “Page” to find out more.
  • Incorrectly configured tracking of iframes and the integration of tracking on partner websites can often lead to incorrect data collection. In this case, we advise you to take a closer look at the tracking for the iframe or the Google Analytics settings in the third-party tool.

You should correct the issues by adjusting your tracking accordingly. You can also change the configuration in the corresponding tool to exclude certain hits through filters.

The Majority of Traffic Comes From Direct

A high percentage of direct traffic can be plausible if the majority of your visitors are returning customers who, for example, access your site daily via bookmarks or directly via the URL. However, if there is no plausible explanation for this, there is most likely a problem. It could imply that traffic from certain channels is not correctly recognized by Google Analytics and is therefore assigned to the “Direct” channel (e.g. newsletters). It should also be checked whether channels are overwritten by faulty tracking or specific Google Analytics settings.

As a solution we suggest the following checkpoints:

  • Take a closer look at direct traffic and check in detail which landing pages are connected with these visits. Work with secondary dimensions to obtain further information.
  • If you look at the channels overall, do the remaining channels show realistic figures? Is a channel missing? If something appears wrong then we recommend analyzing the “Source/Medium” dimension for all your traffic. Additionally, check the “Default Channel Grouping” settings. It is possible that wrong or missing configurations can skew data. To do this, go to “Admin” in Google Analytics, select your data view and then click on “Channel Settings” and “Channel Grouping”.
  • Make sure that your newsletters are not sent without UTM tags.
  • Check your website and ensure that you do not have “outlier cases”. This can be content that runs on a separate server or domain, and which obtains content from your website through iframes, for example.
  • Check your “Referral Exclusion List” in the property settings in Google Analytics.

Your Own Domain Is The Main Referrer

Ideally, your own domain should never appear under referral traffic. Exceptions can occur if you have different products or sites on separate sub-domains (third-level domains), e.g. product1.yourdomain.com, product2.yourdomain.com.

Other possible causes:

  • Is your cross-domain tracking set up correctly?
  • Is the session possibly interrupted by a manually modified session timeout?

We advise you to check the above points thoroughly and to correct them immediately.

The Bounce Rate Is Very Low (<10%)

An extremely low bounce rate should always be a red flag as this implies that practically all visitors to the website interacted with its content. In general, the bounce rate should be somewhere above the threshold of 30%, depending on your industry vertical. If you look at your marketing channels individually, it is quite possible that this value is much higher: For example, display traffic usually has a bounce rate between 50-90%.

We have listed possible scenarios that can lead to a low bounce rate:

  • Incorrect tracking is often an underlying error. For example, Google Tag Manager can initiate automatic events that simulate/trigger an interaction and adversely affect the bounce rate.
  • The web page itself can also contain automatic elements that change, thereby triggering a Google Analytics track event.
  • Automatic redirects can lead to distortions (e.g. with meta tags or JavaScript)

We recommend checking the possible causes one after the other and fixing errors as quickly as possible.

Significant and Persistent Deviations of Conversions From the Mean

If your total conversions fluctuate widely then there must be a plausible explanation. Has a new marketing campaign been launched that attracts many visitors and aims at conversions? Can these fluctuations be attributed to a specific channel?

If you cannot find a plausible reason, we recommend that you continue your research:

  • Could there be an underlying tracking error?
  • Have any recent changes been made to the website that could have an impact on the tracking? These could be adjustments to the design, wording, forms, or renaming of pages and they might affect your triggers in Google Tag Manager. If such triggers no longer fire correctly then any linked conversions may not be captured too.

To find the problem, we recommend checking the following points:

  • First, check whether related metrics correlate with the variances (e.g. number of sessions and number of pageviews related to the target action. Are there events that track as the basis of a conversion and do they show similar variations?).
  • Then check whether the Google Analytics conversion trigger is still activated correctly. The Preview and Debug mode in Google Tag Manager is ideal for tracking tests.
  • Make sure that your filters in Google Analytics are (still) set correctly.

When you have found the error, correct it, and remember to test your tracking changes extensively before publishing them.

Conclusion

Varying key metrics do not always have to be an error. It is quite possible that a plausible explanation can be found. However, if there are no such explanations and the variances seem surprising, it is important that you investigate and look for the cause. Always pay attention to larger deviations. Set up custom notifications in Google Analytics so that you are automatically alerted when your KPIs exceed or fall below specific thresholds. This way you will never miss anything again.

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