I would assume but I haven't tried it yet either.

Here's how to approach this:

1. Add an annotation documenting the launch
2. Watch New Users for bumps (not daily, don't go wild)
3. Prepare stakeholder language if questions come up

Nothing dramatic, just aware monitoring.

And you can find my expanded thoughts here: kpplaybook.com/resources/go...

This is privacy-preserving behavior working correctly. Browsers shouldn't share cookies with each other.

But it creates an analytics interpretation challenge: Your stakeholders see "new users up 15%" and think growth.

You know it's just people trying a new browser.

But here's the important part: when you import your Chrome data into Atlas, you get bookmarks + passwords + history. Great!

You know what you DON'T get? Cookies.

Which means GA4 can't recognize you as a returning visitor. You're "new" again, even if you've been visiting that site for years.

We installed Atlas yesterday to test the analytics behavior. First thing I checked: user agent string.

Result? Identical to Chrome. EXACTLY the same. Which means GA4's Browser dimension is going show Atlas as "Chrome" not as its own thing.

Full walkthrough here: youtu.be/l_gz2SRrMec

If you're dealing with this, hope the video helps. Reply if you have questions or comments, and I will share updates if I find better solutions or if Google fixes this.
#analytics #GA4 #dataQuality

I just recorded a quick video showing how to filter it out using browser version segments in GA4 explorations. It's not perfect - browser version isn't available as a custom dimension outside explorations (GA4 limitation) - but it's what we've got for now.

Here's what's happening: People are seeing massive spikes in organic search traffic in GA4, but Search Console is completely flat. The engagement rate is terrible. It's spam traffic coming from Chrome 139.0.0.0 on Windows 10.

@rustybrick.com covered it here: www.seroundtable.com/ga4-surge-or...

Thanks for sharing!

The difference this makes is incredible. Clean platform names, easy totals, professional reports that make you look good.

Here is the full breakdown with all the regex patterns: kpplaybook.com/resources/tr...

Questions? Ask away!

#analytics #GA4 #socialmedia #marketing

Here's the process:

1. Create custom channels for each platform using regex patterns (I have a list for you!)

2. CRITICAL: Reorder these channels ABOVE "Organic Social"

3. GA4 processes top-to-bottom, so order = everything

The fix is a custom channel group, and they aren't difficult to set up, BUT the channel order matters! If you don't reorder them correctly, your lovely new channels never get used.

GA4's default channel grouping system wasn't designed for how social platforms actually work.

When someone clicks your link from the LinkedIn mobile app vs desktop vs a shortened link, GA4 sees three different sources instead of just one LinkedIn channel.

Here is my full breakdown with step-by-step guides: kpplaybook.com/resources/re...

And the replay of the webinar where I went over this process: www.youtube.com/watch?v=qw0z...

Questions? I genuinely want to hear about your GA4 experiences!

#analytics #GA4 #marketing #AIanalysis

The framework I shared in my recent webinar works because it acknowledges LLM limitations while leveraging their pattern recognition strengths.

Your business context is what turns AI-identified patterns into actual strategic insights.

Here's what to do:

1. Create a custom channel group in GA4 using my regex pattern (10 minutes of hands-on time)

2. Set up text highlighting tracking for AI Overviews (another 15 minutes)

3. Build a framework for AI data analysis

(And check with legal first to make sure you can use AI)

Here's the thing that really gets me excited: AI traffic is QUALITY traffic.

Visitors from AI tools show higher engagement rates, spend longer on the website, and view more pages than your average visitor.

This isn't just a measurement exercise - it's a revenue opportunity hiding in your data!