If you think your Google Analytics set-up is not optimal or has errors, then use our free spot check tool to check to see if there any issues.
The easy-to-use tool checks ten of the most commonly found problems with Google Analytics set-ups. Once you have access, set the account you would like to be checked - you'll get the results instantly!
Check common Google Analytics errors instantly
Our FREE Google Analytics Troubleshooter resource will instantly tell you if you have problems with the following common areas.
- Query Parameters Polluting Page-Level Reporting
- Data Collected from Irrelevant Hostname
- Self Referrals
- Internal Site Search Tracking
- Miscategorised Referral Traffic
- Uncategorised Traffic in Channels Report
- Hit Limit
- Personally Identifiable Information (PII) Collected in GA
- Duplicate E-commerce Transactions
- Not Set Landing Pages
Access the Troubleshooter now.
It's really clear, easy to understand and the use of graphics is excellent."Ian, user researcher, Charity Commission
Common questions about the tool
What aspects of Google Analytics does the tool check?
The tool checks for ten common errors that can have a detrimental effect on reporting, see the full list of errors the Troubleshooter checks
Who should use this analytics tool?
The Troubleshooter is useful for any organisation that uses Google Analytics.
How often should I use the Troubleshooter?
We recommend using the tool regularly but, it is not exhaustive. There are lots of other things that are custom to your setup that will likely require checking alongside it.
Is there any limit to how many times I can use the resource?
No. You are free to use the tool as many times as you like.
If any of the following are true of your needs, you should test to see if your analytics set-up has any problems.
You need a quick and easy way to check the health of your Google Analytics account/s
You need a quick way to check if your GA set-up is recording Personal Identifiable Information (PII)
You suspect query parameters are polluting page-level reporting
You want to check if data is being collected from irrelevant hostnames
You want to see if internal site search is setup and being tracked correctly
You want to quickly see if there is any uncategorised traffic in channels report
The Google Analytics Troubleshooter tool is a great place to start if you want to get a rapid assessment of your Google Analytics set up without having to engage with a third party. Using this tool is simple and allows you to form a quick evaluation of the reliability of your GA data. You know instantly from the results whether you are experiencing some of the more common issues we typically find in our analytics audits along with recommended fixes or links for further assistance to assess your bespoke setup. You can then either fix the problems yourself or provide a clear brief to a third party to make the fixes for you."Dwight Thomas, Business Director
How to use the resource
Solutions to the impact of these 10 issues found in Google Analytics Troubleshooter
1. Query parameters polluting page-level reporting
Query parameters are key/value pairs that are used to add information to a URL. They are often needed for marketing purposes, such as campaign tagging, and sometimes as part of a site’s functionality to pass data from one page to another.
The query strings cause the data for a page to be split out over multiple pages within page-level reporting, making it difficult to analyse content performance in Google Analytics.
For example, you may see pages with query parameters relating to different language options on your site. They might be used by your developers to carry certain product information and can also be added to URLs by third parties too. Facebook uses the fbclid parameter to carry an identifier for their own tracking purposes.
The example below shows how query parameters can split data for one page out onto multiple lines in Google Analytics, which usually means you have to export everything and clean it up in order to analyse page-level performance.
Unless reporting views are in place for reporting purposes, we recommend stripping all query parameters from reporting views.
You can use query parameters to change content on the page (e.g. for pagination). If used in this way, then keep query parameters in place to enable Google Analytics to recognise them as distinct pages.
- Accurate page and landing page data is a crucial building block of successful content and marketing strategies
- Stakeholders misinterpreting page-level data
- Additional work required to analyse page-level data outside of GA
- Filter individually in view settings
- Filter all from reporting view
2. Data collected from irrelevant hostnames
By default, Google Analytics reports on traffic to all hostnames that have the Google Analytics tracking code installed, including test and staging domains. These should either be filtered from the reporting views or send data to a different property because test users will behave very differently to normal website users, skewing metrics.
Check that all the hostnames you want to collect data from being included in the list. Hostnames may consist of payment gateways and should consist of translation services (e.g. translate.googleusercontent.com) and cache/speed services (e.g. webcache.googleusercontent.com).
- Test traffic behaves completely differently to your genuine website visitors so this will skew your engagement and conversion metrics, harming your ability to optimise content, conversion rates or marketing spend
- If you’re missing any domains that are part of the user journey, then you’re not capturing the full picture in Google Analytics, which is detrimental to all areas of marketing and website optimisation
- Apply filters to ensure you only collect data from relevant sources
3. Self referrals
A self-referral is referral traffic that originates from your site(s). In general, these indicate a problem with your implementation, e.g. cross-domain tracking issues or untagged pages. Self-referrals can cause loss of correct channel attribution and affect user journey analysis because sessions are effectively getting split up in Google Analytics and not treated as one session.
- User journey analysis is flawed because single session journeys appear as multiple sessions
- Channel performance data is unreliable because the source of the session is lost when the session breaks into multiple sessions
- Inflated session metrics dramatically affect data quality as a whole
- Depends but usually, it’s correcting an issue with cross-domain tracking or missing tracking code
4. Internal site search tracking
Does your website have an internal search filter? Is Google Analytics site search tracking set up and collecting data? This data can be compelling in identifying areas of the site users are struggling to find and also helps uncover potential new content opportunities for the website. It’s essential to have a lowercase filter for the search terms to prevent duplication when some users capitalise and others don’t (e.g. ‘Fresh Egg’ vs ‘fresh egg’)
- Similar to query parameters, if you’ve got duplicates, data misinterpretation is a problem for people who aren’t aware of the issue. To analyse the data you’ll need to export and clean the data
- Enable in the view settings if you don’t have it set up
- Add a lowercase filter for search term
5. Miscategorised referral traffic
Google Analytics does an excellent job of correctly categorising traffic into sensible channel groupings in the channels report. The referral channel can include incorrectly placed sources. These sources often include email traffic and traffic from lesser-known search engines.
- Look for sources that you think should be categorised as other channels. Rewrite sources using filters.
6. Uncategorised traffic in channels report
The channels report is probably the best place to start for an overview of website and marketing performance, so it’s essential to ensure that it’s accurate. As well as miscategorised traffic you may also see uncategorised traffic falling into (Other). Usually, this is due to UTM-tagged campaign traffic that is either incorrectly tagged or has no corresponding channel grouping rule.
Even when traffic in (Other) is a small percentage of overall traffic, it can still be a significant proportion of marketing spend.
The way to resolve this is to have a structured approach to campaign tagging. Download our free UTM tagging tool for Google Analytics to make campaign performance analysis simple.
- Correct channels are not getting credit for sessions and conversions
- Makes it hard to see a topline view of channel performance in GA
- Data may need to be exported and cleaned up to make it useful
- Add organic search sources in property settings
- Use filters to rewrite source/medium
- Follow campaign tagging best practices to ensure your data gets categorised correctly
7. Hit limit
The free of Google Analytics has a hit limit of 10 million hits per month. If you are close to or over the limit, you are at risk of losing access to your data. There are two options for properties that breach these limits: either reduce the number of hits sent to Google Analytics or upgrade to the paid product Google Analytics 360.
- Google doesn’t guarantee to process all hits over 10million, although in reality, this wouldn’t happen without fair warning
- If you’re over the limit, you’ll likely be affected by data sampling
- Reduce the complexity of GA implementation
- Upgrade to GA 360
8. Personally identifiable information (PII) collected in GA
If there is an instance of PII collection, it requires urgent attention! Collection of PII in Google Analytics is against Google's Terms of Service (TOS) and the data protection privacy of your organisation.
The Google Analytics Troubleshooter dashboard searches pages for query parameters that contain personal data like 'name', 'address' and 'tel'. It also searches for '@' anywhere within the page and page title. Troubleshooter looks in the most common places to find PII but is not an exhaustive check. We recommended that you check campaign and event dimensions, user ID (if you're using it) and custom dimensions.
Filtering the data out of Google Analytics reporting views is not sufficient as it is sending the data to Google for processing that constitutes a breach. Although some solutions use Google Tag Manager to prevent sending PII information, the most robust solution is to ensure that it's not passed to Google Analytics in the first place, whether via the URL or anywhere else.
- The importance of this issue is pressing. There are legal risks involved with not processing personal data correctly
- Filtering out is not sufficient, stop this from happening at the source
- Once fixed, you can delete existing PII-affected data. Although the data deletion API is not that sophisticated
9. Duplicate e-commerce transactions
An incorrect (or no) implementation will lead to the transaction event firing multiple times if the user refreshes or revisits the page.
You can check the extent of the discrepancy between total transactions and unique transaction IDs using the Troubleshooter. Transaction IDs with multiple transactions will appear in the table in the dashboard.
- Over reporting on revenue and conversions
- Misattributed conversions
- Work with your developers to ensure that the transaction code only fires once
10. Not set landing pages
Where does (not set) rank in your list of landing pages? The problem occurs when sessions contain no pageview. A high proportion of (not set) landing pages can be indicative of tracking issues, although it can be that this is merely capturing natural user behaviour.
If this seems to be an issue, create a segment of sessions with no page views and use the Google Analytics User Explorer Report and the events report to try and work out what’s causing them.
Potential causes include:
- Misconfigured tracking code: if there are sections of the site where no pageview fires, this could cause sessions with only events.
- Filters: you may have filters that are preventing pageviews from appearing in your view. Check your list of filters and try looking at the data in your unfiltered view.
- Expired sessions: By default, sessions expire after 30-minutes of inactivity or at midnight; this is the most common cause. If a session ends and then the user triggers an event before leaving the site with no further pageview, this new session will have a not set landing page.
- If sessions are breaking where they shouldn’t, this raises a question about any user journey or channel performance analysis
- Depends on the underlying cause, this needs more in-depth investigation
- If due to some misconfiguration then this should be fixed
- If natural user behaviour and sessions expiration is causing the issue, you can consider increasing the 30-minute session timeout length