How to ensure your traffic is accurate in Google Analytics


6 mins

If you’ve delved into the world of web analytics, you have most likely heard of Google Analytics (if you haven’t, then I think you need to get a spell checker or something because something’s not quite right). Launched in 2005, it quickly became the most widely used web analytics service on the web, with GA4 taking over from July 1st 2023.

If you’re a beginner, you may look at your data and feel a little overwhelmed to say the least. There are so many figures in front of you, it’s hard to know what’s most important and what’s not. You also need to ask yourself – Is this data accurate? Can I trust it? What could go wrong?

Take a look at our top tips to prepare your analytics, prevent and reduce spam traffic and provide the most accurate data. 


We all know the old classic, fail to prepare and prepare to fail. There are some things you should do before you begin analysing data.


What could go wrong?

Distracted Dan applied some filters to his Google Analytics traffic. He got rid of all possible flawed dimensions and was sure that no spam traffic could get through. His client had a quick look at how their site was doing. They could see they had under 10 views that month which they weren’t happy about, and they were looking at Dan as the culprit.

He had added too many filters and now even relevant traffic was being filtered out. He forgot to add an unfiltered view. He had a lot of fixing to do.

If he had created an unfiltered view, the problem would have been fixed in seconds.



Spam traffic happens, as we’re all aware of, but there are things you can do to prevent it.


What could go wrong?

Distracted Dan saw that his client’s conversion rate had gone up 50% in January. Amazing, he thought. They’ll love that.

However, he looked into the data and found that all sales had come from his work’s address. Oh. They weren’t actually orders from customers, they were from when his colleague completed those user tests earlier in the month.

If he had created the correct filters to exclude any internal traffic, his data would have been more accurate.



Don’t worry, there are things you can do to remedy spam – it’s never too late!


What could go wrong?

Systematic Sophie was looking through some data at the end of the month ready for her monthly meeting with her client. She saw that on Tuesday there were 240 views, Wednesday there were 2450 but it was back down to 210 on Thursday. Hm. She asked Distracted Dan if he had any idea what had happened.

Now that he thought about it, he did remember something causing that a few weeks ago but had forgotten to write a note about it.

Sophie had to analyse the data again and figured out it was because the client was mentioned on the local radio that day, causing a spike in views. 

If Distracted Dan had added a note to remind all users of this fact, it would have saved a lot of time.


Although these are just a few tips, luckily we are experts in analysing web traffic in order to ensure it is accurate, from real users and not warped by spam. Get in touch with us today. 


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