Introduction
Google’s recent introduction of AI Mode was designed to reshape how people engage with Google Search. This new AI-powered interface promised quicker answers, richer summaries, and a shift away from traditional lists of search results. Yet, for marketers, SEO professionals, and analytics teams, its arrival has revealed a problem that threatens to undermine years of data-informed digital marketing strategy.
The issue? Invisible traffic. Website visits originating from Google AI Mode no longer include referrer data, making it impossible for Google Analytics 4 and similar tools to attribute traffic correctly. As a result, marketers are now dealing with what many are calling the next version of the “Not Provided” era—a situation where data vital for measuring campaign success is either obscured or entirely absent.
This article breaks down what’s happening, how it affects campaign types and ecommerce advertising strategy, and what steps marketers can take to maintain clarity in a fast-changing digital landscape.
The Technical Core: What’s Going Wrong?
Referrer data is a key signal used by platforms like Google Analytics to determine how users arrive at a website. This includes whether a visit comes from Google Search, Google Ads, social media, email campaigns, or direct navigation.
When users click links within Google AI Mode—including AI Overviews and experimental Search Labs features—the referrer is removed by using the HTML rel=”noreferrer” attribute. This prevents browsers from passing the source of the traffic to the receiving website.
This change affects a wide range of tools beyond Google Analytics. HubSpot, Adobe Analytics, and other PPC tools are similarly impacted, making it impossible to track whether those clicks came from organic listings, paid ads, or content strategies based on generative AI tools.
Tom Critchlow, a fellow advertising expert, put it plainly: “Clicks from AI Mode show up as direct traffic, not just in Google, but in all analytics tools.”
Google’s Position: A Bug or a Strategic Change?
Initially, speculation swirled about whether the change was deliberate. It reminded many of the earlier shift in 2011, when keyword data in Google Search was hidden from webmasters, birthing the infamous “Not Provided” keyword grouping.
Google spokesperson John Mueller addressed these concerns directly, stating on Reddit: “We’re currently considering this a bug, so I’d expect it to be fixed.”
But as weeks passed without resolution, many in the SEO and PPC communities began questioning whether this was more than a bug. Barry Schwartz, Danny Goodwin, and Lily Ray have all voiced scepticism. Ray posted on LinkedIn, suggesting this lack of transparency might conceal low click-through rates from AI Mode: “Google does NOT want us having access to traffic data for AI Mode… because it will reveal just how little traffic both are actually driving to external websites.”
Why This Matters: Real-World Impacts on Marketing Teams
Attribution Confusion and Reporting Gaps
For marketers, attribution is the foundation of every performance report. With Google AI Mode misclassifying traffic as “Direct,” it becomes nearly impossible to evaluate campaign success, especially for campaign types tied to Google Performance Max, Google Shopping, and personalised advertising.
Losing clarity on conversion rates, click-throughs, and incremental clicks undermines performance reports and obscures ROI calculations. For businesses with complex customer journey maps or those using Customer Match and Audience Builder, the impact is even greater.
Search Console Limitations
The problems extend to Google Search Console as well. Google has stated that AI Mode traffic is included under the “Web” search type. However, there’s currently no label, no breakdown, and no visibility into whether users came via AI Overviews.
Danny Goodwin confirmed: “Clicks on links shown in AI Mode don’t appear in Google Search Console.” This lack of insight means marketers can’t measure impressions or search clicks tied to AI Mode.
Damaged Trust and Growing Cynicism
Without meaningful data, marketers are forced to rely on Google’s own claims that AI Mode sends higher-quality traffic. But when platforms that previously offered robust insights now feel like black boxes, trust erodes. Many now see a disconnect with user preferences, advertiser scepticism rising, and questions around whether Google Ads and Analytics still offer actionable insights.
Misconceptions: Debunking the Noise
Misconception 1: AI Mode Only Affects Organic Search
In truth, the issue impacts both organic and paid links. Ads rankings and product listings in Google Shopping campaigns also lose referrer data. This means that whether you’re running SEO content strategies or paid search campaigns through Google Ads, the data loss is universal.
Misconception 2: Only Google Analytics Is Affected
The issue is browser-based. Because the referrer data is stripped by the browser due to the noreferrer tag, all analytics platforms suffer. This includes those used for programmatic advertising and agentic tools designed to track multi-touch journeys.
Misconception 3: UTM Parameters Will Save the Day
While UTMs still appear in the URL, Google Analytics 4 and other platforms typically rely on referrer data to classify sessions. Without that, traffic appears direct, and campaign tagging can’t reconstruct the full picture unless complemented by server-side logic.
Industry Reactions: A Chorus of Concern
Patrick Stox from Ahrefs reflected on the implications: “We’ve been here before with ‘Not Provided.’ The difference now is that it affects more than just keywords—it affects entire sessions.”
Ginny Marvin, Google Ads product liaison, has yet to address the bug in detail, further deepening confusion.
Maggie Humphrey and Menachem Ani have also noted how the change complicates Performance Max reporting and disconnects performance for advertisers focused on campaign success and personalised campaign recommendations.
Alternative Approaches for Marketers
1. URL Shorteners with Custom Tracking
Services like Bitly and Rebrandly allow marketers to gather metrics directly at the link level. While they can’t restore referrer data, they provide a layer of insight into link clicks that would otherwise vanish from analytics dashboards.
2. Server-Side Analytics and Conversion Modelling
Server-side tracking enables marketers to log user interactions without depending on browser signals. When paired with Conversion Modeling or Incremental conversions, server-side analytics provide a fuller picture—especially valuable for ecommerce search ads and shopping features.
3. Tagging Experiments and Landing Page Variants
Creating specific reviews or 2025 Photo-rich landing pages for AI Mode traffic can help isolate it. Paired with adjusted payment profile data or unique image optimisation features, this tactic can yield clues about traffic sources.
4. Public Advocacy and Community Effort
The more SEOs and advertisers speak up—via LinkedIn, Twitter/X, or Reddit—the more pressure there is on Google to fix the bug. Thought leaders like Anu Adegbola and Jyll Saskin have urged collective advocacy to hold Google accountable.
Comparative Landscape: What About Bing?
Microsoft’s Bing, powered by OpenAI and Copilot, does not suffer from the same tracking failures. Bing’s AI-powered tools continue to pass referrer data, which means marketers using Microsoft Ads retain insight into where traffic originates.
For businesses looking to diversify or address the decline of ecommerce search on Google, Bing currently offers a more transparent playing field.
Trends and Statistics: The Bigger Picture
- A 2024 Trust Insights report found that 73% of marketers noted AI search caused issues with analytics reporting.
- INBOX INSIGHTS and In-Ear Insights data show growing interest in agentic tools and first-party data.
- Google Marketing Live 2025 is expected to provide updates on consent requirements and legal requirements related to tracking.
The rise of AI Mode reflects broader shifts in search engines, where automation and generative interfaces blur the line between content creation, product recommendations, and ad rankings.
Practical Implications for Strategy
To succeed, marketers must adapt their marketing campaign strategy to embrace transparency, redundancy, and diversified data sources. Recommendations include:
- Relying more on first-party data such as email lists and account behaviour.
- Adopting server-side tracking for better visibility.
- Exploring alternatives beyond Google Ads, including Bing, Reddit, and emerging vertical search engines.
- Revisiting content creation workflows to align with the shift toward AI summaries and Deep Search models.
Marketers should also revisit business model assumptions around analytics, audit campaign attribution strategies, and ensure their team is up to date on changes to Google Consent Mode and customer match list minimum thresholds.
What the Future Might Hold
If Google AI Mode becomes the default, marketers will need to pivot away from click-based measurement and towards engagement-based KPIs. These may include:
- Scroll depth
- On-site interaction rates
- Micro-conversions
- Repeat visits and session recency
Expect tools like Google Ads and Analytics to evolve with additional parameters, especially as non-signed-in users require stricter privacy rules.
Meanwhile, marketers should prepare for future core algorithm updates that will further shape keyword rankings, digital marketing strategies, and the types of pieces of content that perform best in a more AI-driven landscape.
Conclusion
Google AI Mode has introduced new opportunities for businesses but also new obstacles. The current analytics blackout affects visibility across PPC performance, ecommerce tracking, and organic search. Until Google resolves the issue or provides new labels in search results, marketers must rely on creative strategies, server-side logic, and community engagement to retain control of their data.
By focusing on campaign types that rely on first-party data, re-evaluating use of Google Ads and Analytics, and leveraging both traditional and agentic tools, marketing teams can continue delivering performance for advertisers focused on real results—not just search clicks.
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