# AI Referral Attribution: What Gemini’s Missing UTM Tags Mean for Your Analytics

Marketing teams are increasingly asked to account for traffic that originates in AI assistants. The task has become harder. In late September 2026, Google’s Gemini stopped appending a UTM parameter to the source links it cites, a change that went unnoticed for roughly a month and has not been explained by Google.

The practical consequence is a measurement gap. Visits that were briefly identifiable as Gemini-originated are again being absorbed into Direct traffic, and reports built on default analytics settings are likely to understate the contribution of content that AI systems cite. This article reviews what is known about the change, explains why AI referrals are prone to misattribution, and sets out a structured approach to measuring them with appropriate caution.

### Why attribution accuracy matters

Attribution informs investment decisions. When leadership evaluates the return on content, or when budgets are allocated between channels, the underlying reports determine the outcome. If a growing source of visitors is recorded in a catch-all category, the work that earned those visits appears less effective than it is.

The issue is compounded by the changing shape of search. AI-generated answers now account for a larger share of research and comparison activity, and the click-through rate from those answers is generally low. Each identifiable visit therefore carries more weight, and each unidentifiable one represents a larger loss of information. Because platforms have offered no guidance on how AI assistants should pass visitors to websites, organisations must rely on their own measurement discipline.

### What is known about the Gemini change

The reported sequence of events is as follows.

Around the start of September 2026, Gemini began adding the parameter `utm_source=gemini` to the source links in its answers. Google made no announcement. A Reddit user noticed the tags, and John Mueller of Google confirmed in the same thread that he could see them as well.

Server logs later published by search consultant Natzir Turrado show the parameter disappearing overnight around September 28 or 29, after approximately three weeks. Search Engine Journal reported the original addition on October 1. Turrado drew attention to the removal on October 27, and Search Engine Roundtable reported on October 30 that it could no longer find the parameter on Gemini links. Google has not commented on either the addition or the removal.

### Why the parameter mattered

A UTM parameter is the most direct way to label the origin of a visit. In its absence, analytics platforms rely on the HTTP referrer, the information a browser passes to indicate where a visitor came from.

On desktop and the web, Gemini visits continue to arrive with a [`gemini.google.com`](http://gemini.google.com) referrer and can therefore be identified. The weakness lies on mobile. One analysis reports that Gemini’s iOS application opens links in an in-app browser that does not pass a referrer, causing those visits to be recorded as Direct in Google Analytics 4. The same analysis states that the parameter had previously exposed between 16 and 65 additional hidden clicks for every 100 sessions identified through a standard referrer. As this derives from a single source, the range should be treated as indicative rather than definitive. The underlying point is nonetheless clear: a portion of AI-originated traffic cannot be identified using standard methods.

### The risk of artificial trends

Changes in tagging behaviour can produce patterns in the data that have no connection to audience behaviour. An analyst reviewing Gemini traffic across September would have observed it emerge, grow for three weeks and then fall sharply. That curve reflects a parameter being enabled and disabled, not a change in interest.

ChatGPT provides a comparable example. According to reporting, its links lost the `utm_source=`[`chatgpt.com`](http://chatgpt.com) parameter between approximately October 7 and 16 before it was restored, and the interruption was subsequently described as a bug. A comparison of October with September could suggest a decline in AI-referred traffic that did not occur.

The appropriate safeguard is to annotate analytics reports with the dates on which sources changed their tagging, and to treat any abrupt movement that coincides with those dates as a measurement artefact unless other evidence indicates otherwise.

### Interpreting growth in Direct traffic

Direct traffic has always served as a residual category. It includes visitors who typed an address, used a bookmark, or arrived from an application that does not pass a referrer. AI assistants have added a further source of the last type, particularly within mobile apps.

This does not mean that all Direct traffic originates from AI, nor that Direct traffic should be reclassified wholesale. It does mean that sustained growth in Direct visits, especially to informational pages that users rarely enter manually, merits investigation. It is a lead to be tested, not a finding to be reported.

### A multi-signal measurement approach

No single method resolves the problem. The following measures are most effective when used together.

1. **Define an AI channel in GA4.** A custom channel group allows known AI referrers, such as [`chatgpt.com`](http://chatgpt.com) and [`gemini.google.com`](http://gemini.google.com), to be reported together instead of being dispersed across Referral and Direct. The group should be built from sources that actually appear in your own data.
2. **Review server logs.** Logs capture details that analytics tools omit, including the user-agent string. One analysis reports that Gemini’s iOS visits can be recognised by a distinctive token in that string, which makes it possible to estimate visits that analytics classifies as Direct. Feasibility depends on developer or hosting support.
3. **Monitor landing-page patterns.** Comparing Direct traffic to deep informational pages against a historical baseline can reveal unusual increases. This is supporting evidence, not proof.
4. **Collect self-reported attribution.** Adding a “How did you hear about us?” field to enquiry or checkout forms, with an option for AI assistants, captures discovery that no tag can record. Responses are imperfect but valuable as a cross-check.
5. **Track brand demand.** Where AI answers mention an organisation, branded search and direct visits to the home page often increase. Observing these indicators alongside content performance shows influence that click data does not.
6. **Apply UTM parameters to controlled links.** Links placed in newsletters, profiles and partner pages should carry the organisation’s own tags, because third-party platforms cannot be relied upon to add them.
7. **Combine with Search Console data.** Google Search Console’s AI reporting shows impressions in AI Overviews and AI Mode, though not clicks. Used alongside first-party analytics, it provides a second partial view of the same activity.

### Avoiding two opposite errors

Two interpretive errors are common. The first is to conclude that AI traffic is negligible because the identifiable portion is small; a substantial share may be recorded as Direct, so the true volume is probably higher than reported. The second is to attribute every increase in Direct traffic to AI, which, without corroborating evidence, amounts to conjecture.

A defensible position states what can be measured, identifies what cannot, and offers a transparent estimate of the difference.

### Frequently asked questions

**Did Gemini stop adding UTM parameters?**\
According to server-log data from Natzir Turrado and a Search Engine Roundtable report dated October 30, 2026, yes. The parameter appeared on cited links for roughly three weeks in September and was then removed. Google has not commented.

**Can Gemini traffic still be tracked?**\
In part. Desktop and web visits retain a [`gemini.google.com`](http://gemini.google.com) referrer. Visits from the mobile app may be recorded as Direct.

**Why does AI traffic appear as Direct?**\
Some AI applications open links in their own browser without passing a referrer. With neither a referrer nor a UTM parameter, analytics platforms have no basis for attribution and default to Direct.

**Did ChatGPT also lose its tracking parameter?**\
Reportedly, for about a week in October, between roughly October 7 and 16. The interruption was later described as a bug.

**Should organisations stop using UTM parameters?**\
No. They remain essential for links an organisation controls. They should simply not be assumed on links generated by third-party platforms.

### Conclusion

The removal of Gemini’s UTM parameter is a minor technical event, but it illustrates a broader limitation. AI assistants pass visitors to websites inconsistently, and most analytics tools were designed for an earlier model of web traffic. Parameters will continue to appear and disappear, applications will continue to share limited information, and new assistants will continue to emerge.

Organisations that adapt best will be those that rely on several imperfect signals rather than a single tag, and that report their limitations candidly. A clearly qualified estimate is more useful than a confident figure that is incorrect.

*Adapted from a longer article originally published at* [*kilowott.com*](http://kilowott.com)*.*