Top 10 Google Analytic Fails

It doesn’t take long to realise that something so useful a tool as Google Analytics can be undone with some simple set up errors and poor housekeeping.

Whether you’re a complete newbie or consider yourself a data wiz, ensuring your GA is working properly is something you always need to keep on top of, no matter your competency level!

Take a read through this list and if you have a light-bulb moment and think ‘Whoops!’ I’ve done that… and that… and that…  or haven’t done that or that…  then get in contact with the brilliant & helpful team at Polka Dot Data via email hello@polkadotdata.comWe are here to help you. 

Check out our Top 10 GA Fails…

1. Sending data to the wrong GA

This first one may seem simple but actually is extremely common. Many users believe to have added their code, only to log on to their GA to see no data at all. Making sure the correct property code matches up with whats on your web page, is vital and definitely an error not to make!

2. Sending PII Data

To protect user privacy, Google policies mandate that no data be passed to Google that it recognises as personally identifiable information e.g. email, addresses, mobile numbers. Take a look in your pages report, search ‘@’ for example and if you spot any email addresses then this is definitely something that needs sorting asap!

3. Channel Groupings Not Configured

Orgnising traffic correctly, allows you to accurately check the performance of channels quickly. Not doing this may result in errors in reporting and strategic decision making.

4. Double Tracking

Whilst having “too little” tracking is not recommended, “too much” is not ideal either. Sometimes, multiple cases with more than one pageview per load, can get recorded along with many other similar circumstances. We recommending checking for old code as well as duplicated code through GTM and hardcode to avoid this error!

5. Not Filtering Internal Traffic

We all know the importance of seeing how users interact with your website, however unless you have excluded your own traffic, this data will be skewed by how you or your employees are interacting with the website! Take a look at our other blog post on ‘How to filter internal traffic in GA’. 

6. Only having one view

Many users make the mistake of getting too excited and diving deep into the data. Don’t worry, we get it. Unfortunately, they forget to set up a Raw and Test View in the process.  These views allow a back up of data and also to see data without any configuaration so make sure you have all 3 views set up!

7. Not checking if there have been any effect from GTM changes.

When making alterations or any changes to tag and triggers in GTM, it is vital that corresponding changes are also made in GA if needed. This is very common when looking at Goals. A minor change such as altering the event label can cause the whole goal to break in GA so make sure you are routinely checking your data to ensure this isn’t what’s occured!

8. Forgetting to exclude bots

Bots are an large problem amongst websites and lead to skews in data.  This traffic is automated and adds no value to the site. The majority of these can be eliminated by simply ticking the box in Admin Settings in GA, so make sure you don’t forget!

9. Not using annotations

Another common error may seem rather small however can save you a whole lot of time and pain when done. Some GA users make multiple changes to their website, tags and data but forgot to make a note or date stamp this on Analytics. This can then lead to unnecessary worries or uncertainties in data fluctuations. So whenever you make a change, add an annotation to understand if this has effected the data in anyway. You will thank yourself a year down the line!

and the one that had us nodding our heads…

10. Not Employing Us

Need we say anymore.

So there you have it. Our Top 10 Fails made in Google Analytics definitely to be more aware of!

If you have any questions or would like to speak to one of our data experts, Contact us today.