An analytics manager opens her weekly report and notices something odd. Direct traffic has crept up, and much of it is landing on deep blog posts and product guides, pages nobody types into a browser from memory. She has no campaign to credit and no new backlinks. Somewhere in that bucket, she suspects, are visitors who came from an AI assistant that cited her pages.
She is probably right, and the problem has just become harder. At the end of September 2026, Google’s Gemini stopped adding a tracking tag to the links it cites. According to research by Kilowott, the change only came to light a month later.
This matters because reports drive decisions. If a growing source of visitors is hidden inside a catch-all bucket, content that is being cited and recommended can look like it is underperforming. And since click-through from AI answers is often low, every visit you can’t identify costs you more.
What Happened to Gemini’s Tracking Tag
Around the start of September 2026, Gemini began adding the parameter utm_source=gemini to the source links in its answers. Google did not announce it. A Reddit user spotted it, and Google’s John Mueller confirmed in the thread that he could see it too.
Then the tag disappeared. Server logs shared by search consultant Natzir Turrado show it vanishing around September 28 or 29, after about three weeks. Turrado raised it on October 27, and Search Engine Roundtable reported on October 30 that it could no longer find the tag. Google has not commented on either the addition or the removal.
Why AI Visits Land in “Direct”
Without the tag, you depend on the referrer, which is the information a browser passes about where a visitor came from. On desktop and the web, Gemini visits still arrive with a gemini.google.com referrer, so they can be identified.
Mobile is the weak spot. One analysis reports that Gemini’s iOS app opens links in its own in-app browser without passing a referrer, so those visits appear as Direct in Google Analytics 4. The same source says the tag had previously revealed between 16 and 65 extra hidden clicks for every 100 sessions counted through a standard referrer. That comes from a single report, so treat the range as indicative.
The Trap: Fake Trends in Your Data
There is a second problem that is easy to miss. If you looked at Gemini traffic in September, you would have seen it appear, grow for about three weeks and then collapse. That pattern says nothing about interest in your content. It reflects a tag switching on and off.
ChatGPT had a similar wobble. According to reporting, its links lost their utm_source=chatgpt.com tag between about October 7 and 16 before it returned, and the gap was later described as a bug. Comparing October with September could make you read a drop in AI traffic that never happened. Mark these dates in your reports and treat any sharp rise or fall around them as a measurement artefact until proven otherwise. Kilowott makes a similar point about over-reading platform data in its post on Google adding links to AI answers.
A Practical Plan for Measuring AI Referrals
No single step is perfect, but together they give a far better picture than the default reports.
Create an AI channel in your analytics. In GA4, a custom channel group lets you gather known AI sources, such as chatgpt.com and gemini.google.com, into one place. Check which sources actually appear in your own data before you build it.
Look at your server logs. Logs record details analytics tools miss, including the user agent. One analysis reports that Gemini’s iOS visits can be spotted through a particular token in the user-agent string. Ask your developer or host whether that is feasible for you.
Watch landing pages, not just sources. A jump in direct traffic to deep informational pages is a useful clue, though only a clue.
Ask people directly. Add a “How did you hear about us?” field to enquiry and checkout forms, with an option for an AI assistant.
Track brand demand. If AI answers mention you, branded search and direct home page visits often rise.
Tag what you control. For links you place yourself, in newsletters, profiles and partner pages, use your own UTM parameters.
Automate the reporting. A weekly view that combines these sources saves hours and keeps your annotations consistent. This is a natural fit for automation, and Kilowott’s digital marketing team builds this kind of reporting for clients.
What Not to Conclude
Avoid two opposite mistakes. One is deciding AI traffic is negligible because the identifiable slice is small, when much of it may be hiding in Direct. The other is blaming every rise in direct traffic on AI, which without evidence is guesswork. A better stance is to say what you can measure, name what you can’t and estimate the gap honestly. Kilowott’s piece on why agentic AI makes AEO non-negotiable makes the related point that visibility and traffic are different things, and both need tracking.
AI Referral Measurement Checklist
- Reports are annotated with the dates Gemini and ChatGPT changed how they tag links
- An AI channel grouping exists in analytics, based on sources you actually see
- Direct traffic to informational pages is checked against your usual baseline
- Your developer or host has been asked about log analysis
- Forms include a “how did you hear about us” option for AI assistants
- Branded search and direct home page visits are tracked
- Every link you place yourself carries your own UTM parameters
- A weekly report combines these views
Quick FAQ
Did Gemini stop adding UTM parameters?
Yes, according to server-log data from Natzir Turrado and a Search Engine Roundtable report on October 30, 2026. Gemini added utm_source=gemini for roughly three weeks in September and then stopped, and Google has not commented.
Can I still track Gemini traffic?
Partly. Desktop and web visits still arrive with a gemini.google.com referrer, but mobile app visits may appear as Direct because the app does not pass a referrer.
Should I stop using UTM parameters?
No. Keep using them on links you control, and don’t depend on AI platforms to add them for you.
Final Thoughts
The Gemini change is a small technical event, but it points to something bigger: the way AI assistants send people to your site is still being worked out, and most analytics tools were built for a different era. Teams that cope best build a measurement approach that holds up when tags appear and disappear, and are honest about what they can and can’t see.
If you would like help setting that up, Kilowott’s digital marketing team can build reporting that combines these views, and their automation work keeps it running every week. You can also browse their case studies or get in touch.
Source and further reading: Where Did That Visitor Come From? Fixing Attribution for AI Referrals After Gemini Dropped Its UTM Tags by Kilowott.
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