On the surface, the above sounds exciting. In practice, Google’s application of predictive algorithms means you’re not seeing actual data.
To offer a variation of cookieless tracking, Google algorithms close the gaps in reporting by creating models (i.e., data-backed predictions) instead of reporting on actual user behaviours. Therefore, your GA4 numbers may not be accurate.
For bigger web properties (think websites with 1+ million users), Google also relies on data sampling — a practice of extrapolating data analytics, based on a data subset, rather than the entire dataset. Once again, this can lead to inconsistencies in reporting with some numbers (e.g., average conversion rates) being inflated or downplayed.
Solution : Try an Alternative Website Analytics App
Unlike GA4, Matomo reports consist of 100% unsampled data. All the aggregated reporting you see is based on real user data (not guesstimation).
Moreover, you can migrate from Universal Analytics (UA) to Matomo without losing access to your historical records. GA4 doesn’t yet have any backward compatibility.
Spam and Bot Traffic Isn’t Filtered Out
Surprise ! 42% of all Internet traffic is generated by bots, of which 27.7% are bad ones.
Good bots (aka crawlers) do essential web “housekeeping” tasks like indexing web pages. Bad bots distribute malware, spam contact forms, hack user accounts and do other nasty stuff.
A lot of such spam bots are designed specifically for web analytics apps. The goal ? Flood your dashboard with bogus data in hopes of getting some return action from your side.
Types of Google Analytics Spam :
- Referral spam. Spambots hijack the referrer, displayed in your GA referral traffic report to indicate a page visit from some random website (which didn’t actually occur).
- Event spam. Bots generate fake events with free language entries enticing you to visit their website.
- Ghost traffic spam. Malicious parties can also inject fake pageviews, containing URLs that they want you to click.
Obviously, such spammy entities distort the real website analytics numbers.
Solution : Set Up Bot/Spam Filters
Google Analytics 4 has automatic filtering of bot traffic enabled for all tracked Web and App properties.
But if you’re using Universal Analytics, you’ll have to manually configure spam filtering. First, create a new view and then set up a custom filter. Program it to exclude :
- Filter Field : Request URI
- Filter Pattern : Bot traffic URL
Once you’ve configured everything, validate the results using Verify this filter feature. Then repeat the process for other fishy URLs, hostnames and IP addresses.
You Don’t Filter Internal Traffic
Your team(s) spend a lot of time on your website — and their sporadic behaviours can impair your traffic counts and other website metrics.
To keep your data “employee-free”, exclude traffic from :
- Your corporate IPs addresses
- Known personal IPs of employees (for remote workers)
If you also have a separate stage version of your website, you should also filter out all traffic coming from it. Your developers, contractors and marketing people spend a lot of time fiddling with your website. This can cause a big discrepancy in average time on page and engagement rates.
Solution : Set Internal Traffic Filters
Google provides instructions for excluding internal traffic from your reports using IPv4/IPv6 address filters.