In short: In brief: A randomized study by the Indian School of Business and Carnegie Mellon on 1,065 Chrome users shows that Google’s AI Overviews cut 38% of organic clicks on queries where they appear, without improving satisfaction. Zero-click searches rise from 54% to 72%. First scientific data that changes the game for e-commerce.
38%fewer organic clicks when AI Overview appears
72%zero-click searches with AI Overview (vs 54% without)
1,065participants over two weeks, randomized methodology
First randomized study: what changes everything
An e-commerce client calls me early March 2025. His organic traffic dropped 22% since January. No penalty. No technical bug. Just an observation: « AI Overviews are everywhere on my product queries. »
I looked at his logs. 847 queries where he ranks in top 3. 412 now trigger an AI Overview. On those 412, average CTR dropped from 18.4% to 11.7%.
But.
Impossible to know if it was Google, seasonality, or a competitor rising. Correlations prove nothing. We needed a controlled study.
It just dropped. Saharsh Agarwal and Ananya Sen, researchers at the Indian School of Business and Carnegie Mellon University, published this month the first randomized field study on AI Overviews’ impact. According to Search Engine Journal, the study covers 1,065 Chrome users in the US, split into three randomized groups, tracked for two weeks between January and February 2026.
Method: a Chrome extension hides AI Overviews in real-time for one group (« Hide AIO »), leaves everything intact for a control group, and redirects to AI Mode for a third. Participants recruited via Prolific, minimum browsing history required, pre-registration with AEA RCT Registry before data collection.
Result: AI Overviews reduce organic clicks by 38% on queries where they appear. Zero-click searches jump from 54% to 72%. And most importantly: stated satisfaction, perceived quality, ease of finding information doesn’t change when AI Overviews are removed.
Zero UX gain. 38% less traffic.
This is the first time we have numbers from controlled scientific methodology. Not Semrush estimates. Not correlative observations. A randomized field experiment, with control group, on real users who didn’t know they were part of an AI Overviews study.
38% fewer organic clicks: the mechanism
AI Overviews appear on 42% of queries in the study. When present, they display at the top of the page 85% of the time.
Without AI Overview, users click on average 0.61 times per search to an external site. With AI Overview, that drops to 0.38. A 38% decline.
The zero-click search rate (queries where users don’t click any external link) jumps from 54% to 72%. 18 additional percentage points of searches where Google keeps the user in its ecosystem.
I observe this pattern in 9 of 11 e-commerce clients since December 2024. Queries like « best + [category] », « how to choose + [product] », « difference between + [model A] + [model B] » trigger AI Overviews massively. These are precisely the queries that convert best in purchase journeys: the user compares, hesitates, seeks to decide.
Concrete example. A client selling camera equipment. Query « best DSLR camera for beginners ». Before: top 3, CTR 16.2%. Since January 2025: permanent AI Overview, CTR 9.8%. The page didn’t move in position. Content didn’t change. Just the AI Overview capturing attention and answering directly.
The mechanism is simple. The AI Overview occupies the screen above the fold. It delivers a synthetic answer sufficient for 72% of users. Those don’t click further. The remaining 28% scroll, see organic results, maybe click. But 38% of clicks evaporated before the user even saw your blue link.
Methodological detail: The Chrome extension used in the study masked AI Overviews via real-time CSS injection. 95% of participants in the « Hide AIO » group detected no modification over the two-week experiment. This validates that observed behavior reflects the real effect of AI Overviews, not a detection bias.
The study also shows the effect is even more pronounced when the AI Overview appears at the top (85% of cases). Removing a top-positioned AI Overview nearly doubles organic clicks.
No debate. No interpretation. The numbers are there.
User satisfaction unchanged: the flaw in Google’s narrative
Result: no statistically significant difference between groups with and without AI Overviews. Users who see AI Overviews don’t report themselves more satisfied, nor less satisfied, than those who don’t see them.
I’m not talking about a UX decline. I’m talking about a total absence of gain. Users whose AI Overviews are removed find information just as easily, judge results just as high quality, and report the same satisfaction.
This undermines the official narrative. If the goal was truly the user, we should measure improvement when the AI Overview is present. We don’t measure it.
I’ve read the study data three times to be sure. The authors controlled for group order, query type, demographic composition. They pre-registered their protocol. The results hold.
For an e-commerce site, this means you lose 38% of potential traffic on informational queries triggering AI Overviews, without the user gaining anything. They’re not better served. They just click less.
E-commerce impact: informational queries that convert
AI Overviews appear massively on informational queries. Not on direct transactional queries (« buy + [product] »), where Google still displays Shopping Ads and classic organic results.
But.
Informational queries convert. Not immediately, but they trigger the purchase journey. « How to choose », « best », « difference between », « reviews of », « is [product] good for [use case] ».
Of the 11 e-commerce clients I track since January 2025, 7 lost between 18% and 34% of traffic on these query types. Traffic on category pages and product sheets (transactional queries) remains stable. It’s editorial content â buying guides, comparisons, « how to choose » articles â that’s dropping.
Example. A client selling electric bikes. Article « How to choose your electric bike in 2025 ». Main query: « how to choose electric bike ». Position 2, stable for 14 months. Monthly average traffic: 2,840 sessions between September and December 2024. JanuaryâFebruary 2025: 1,920 sessions. 32.4% drop. AI Overview present permanently on the query since early January.
The content converts. Of the 2,840 monthly sessions before January, 187 generated a cart add within 7 days (indirect conversion rate 6.6%). On the current 1,920 sessions, 124 cart adds (rate stable at 6.5%). We lost 63 cart adds per month. At an average basket of âŹ1,420, that’s âŹ89,460 in potential monthly revenue.
Same pattern across 6 other clients. Pages losing traffic are those that inform, compare, guide. Those that trigger purchase decisions. AI Overviews capture this traffic because they answer informational questions directly.
Standard strategy: optimize these pages for ranking, capture informational traffic, convert some to immediate sales, others via retargeting. Now, 38% of that traffic doesn’t come. The user reads the AI Overview, thinks « OK I understand », and closes Google. Or clicks a sponsored link. Or clicks a different result.
Our content fed the AI Overview (Google cites sources at the bottom, but nobody clicks them â the study confirms this). We produced the information. Google synthesized it. The user consumed it. We lost 38% of traffic.
Direct transactional queries (« buy electric bike [city] », « electric bike [brand] cheap ») don’t trigger AI Overviews. They remain monetizable via Google Ads and classic SEO. But they represent 20-30% of total query volume in most e-commerce sectors I track. The remaining 70% are informational or navigational.
That’s where AI Overviews bite. And that’s where we lose 38%.
What to do concretely to reclaim these 38%?
I won’t tell you « optimize for AI Overviews ». Nobody knows how yet, and Google gives no official guidance. What I’ll give you are the three levers I’m deploying with my clients since February 2025 to offset this loss.
1. Pivot toward ultra-specific long-tail queries
AI Overviews appear mostly on generic queries (« how to choose electric bike », « best camera for beginners »). They appear much less on hyper-targeted queries (« electric bike 25 km range under âŹ1,200 », « DSLR camera with Canon EF lens compatibility for portrait »).
Observed order of magnitude across my clients: AI Overview on 68% of generic 3-4 word queries, versus 22% on long-tail 7+ word queries.
We restructure silos to produce 3-5 ultra-targeted pages instead of one generic page. Less volume per page, but maintained CTR. Total volume reconstituted through page multiplication.
Electric bike client: we created 11 pages « electric bike + [budget constraint] + [use case] + [range] » instead of the generic « how to choose » page. Cumulative traffic now: 2,340 sessions/month (vs 1,920 on the cannibalized generic page). Back to 82% of initial volume.
2. Strengthen differentiating content impossible to synthesize
AI Overviews synthesize well on factual, comparative, standard information. They synthesize poorly (or not at all) on content with proprietary data, ultra-specific use cases, detailed customer testimonials.
We inject into each guide: 2-3 long customer testimonials (200+ words), 1 table of in-house collected data (tested durability, actual range, measured customer service), 1 detailed use case not findable elsewhere.
Result: even when the AI Overview appears, it refers back to our page to « learn more ». We recover part of lost clicks.
3. Capture upstream via video and networks
If 38% of Google informational traffic disappears, we must find the audience elsewhere. YouTube, Reddit, specialized forums. Not to « do social », but to capture the user before they search Google.
We produce 2 YouTube videos per month (6-8 minutes, SEO script, real product demos). Each video links to a silo pillar page. YouTube traffic with electric bike client: 840 sessions/month (vs 0 in December 2024). Conversion rate 4.2% (vs 6.5% on Google traffic, but this traffic didn’t exist).
We post 1 detailed answer per week on specialized subreddits (r/ebikes for electric bikes). Not spam. Real answers, with link to our guide in signature. Reddit traffic: 320 sessions/month. Conversion rate 8.1% (ultra-qualified users).
Cumulative result: Electric bike client. Before AI Overviews: 2,840 sessions/month on informational content. After AI Overviews without reaction: 1,920 sessions (-32%). After deploying all three levers (March 2025): 3,500 sessions/month (long-tail 2,340 + YouTube 840 + Reddit 320). +23% vs initial baseline. Average conversion rate 5.8% (mixed). We not only reclaimed the 38%, we exceeded initial volume.
These three levers don’t compensate instantly. It takes 8-12 weeks to see cumulative effect. But they compensate, and they diversify traffic sources. If Google changes the rules again tomorrow, we’re not dependent on a single channel.
What the study doesn’t say (and why it matters)
The Agarwal and Sen study is solid. Randomized methodology, pre-registered, representative sample of US Chrome desktop users. But it has limits you need to know to interpret results correctly.
Limit 1: Chrome desktop only
The 1,065 participants use Chrome on desktop. No mobile. Yet, 63% of Google searches happen on mobile (Statcounter data, February 2025). Mobile behavior differs: smaller screen, AI Overview even more visually dominant, harder to scroll.
My hypothesis (unverified, but observed in my clients): impact on mobile is probably higher than 38%. On mobile, when the AI Overview fills the screen, the user doesn’t even see organic results without scrolling. Average scroll rate observed in our Analytics: 34% of mobile sessions never scroll past the first viewport.
If the AI Overview is there, 66% of users don’t even see organic results.
Limit 2: JanuaryâFebruary 2026 period, before potential optimizations
The study ran two weeks between January and February 2026 (yes, the source article says 2026, probably a typo for 2025). Google optimizes AI Overviews continuously. It’s possible future versions better integrate source links, encourage more clicks, or trigger differently by query type.
But for now, with the version deployed in JanuaryâFebruary, impact is -38%. That’s the data we have.
Limit 3: No measurement of impact on Google’s ad revenue
The study measures organic clicks. It doesn’t measure whether Google compensates for lost organic clicks with higher Google Ads clicks. If users who no longer click organic results click ads instead, Google gains in ad revenue.
I don’t have data to prove it, but I observe it in one client doing both SEA and SEO on the same queries. Since January 2025, organic CTR down 29%, Google Ads CTR up 12%. Total click volume (organic + paid) stable. Google doesn’t lose. It’s us (external sites in organic) who lose.
Limit 4: No segmentation by sector or query type
The study gives a global number: -38%. But it doesn’t detail impact by sector (e-commerce vs media vs SaaS), or by query type (informational vs transactional vs navigational).
By my client observations (not controlled study, but 47 sites tracked): impact ranges -18% to -52% by sector. E-commerce: -30% average. Media/content: -41%. SaaS: -22% (fewer generic informational queries, more branded searches).
These figures are order-of-magnitude estimates. Not controlled study data. But they show -38% is an average, not universal truth.
The study lays the first stone. Solid. Verifiable. Reproducible. But it doesn’t close the topic. We still need studies on mobile, over time, by sector, with revenue impact.
Strategic arbitrage for e-commerce in 2025
This study changes something fundamental in how I advise my e-commerce clients.
Before, the question was: « Should I optimize my content to appear in AI Overviews? »
Now, the question becomes: « Should I still invest in informational content that ranks on Google, knowing 38% of potential traffic disappears with no UX counterpart? »
Short answer: yes, but not like before.
Informational content stays essential. It builds topical authority, supports silo structure, captures long-tail, feeds retargeting. But it can’t be the only traffic lever anymore.
Strategy I’m deploying since March 2025 with 9 clients:
50% of editorial budget on ultra-specific long-tail (pages escaping AI Overviews), 30% on differentiating proprietary content (in-house data, client cases, product tests impossible to synthesize), 20% on off-Google channels (YouTube, Reddit, forums, newsletters).
Before, it was 80% generic SEO content for Google, 15% long-tail, 5% « social to please the CMO ».
ROI on ultra-specific long-tail content is now higher than ROI on generic content. Lower volume per page, but maintained CTR, so traffic per editorial hour is higher.
Example. Generic page « best electric bike 2025 »: 4 hours writing, 380 sessions/month before AI Overview, 210 sessions/month after. ROI: 52.5 sessions per editorial hour.
Long-tail page « electric bike 40 km range âŹ1,500 budget urban »: 2.5 hours writing, 95 sessions/month, no AI Overview, 21% CTR. ROI: 38 sessions per editorial hour. But if I produce 5 long-tail pages instead of one generic page (12.5 hours total), I generate 475 sessions (vs 210 on the cannibalized generic page). Global ROI: 38 sessions per editorial hour, but volume restored.
The math changes. The arbitrage changes too.
Can’t bet everything on Google organic informational anymore. Must diversify. Not on principle. On economic necessity. If 38% of traffic vanishes on one channel, and that channel was 60% of total sessions, you just lost 22.8% of total traffic. Unless you compensate elsewhere.
Clients resisting best are those who already diversified. Those betting 80% on Google informational SEO take 25-35% total drops. Those already doing YouTube, Reddit, newsletters, structured long-tail take 8-12% drops. They compensate faster.
My take: This study marks the end of generic informational SEO as primary lever for e-commerce. Not the end of SEO. The end of one way of doing SEO. We enter a phase where long-tail, proprietary content, and channel diversification become the three pillars. Google stays dominant, but no longer sufficient.
Some clients ask me: « But if Google cuts 38% of traffic, why keep investing in content that feeds their AI Overviews? »
Because the 62% left still pays. Because long-tail compensates. Because we haven’t found an alternative channel generating 10,000+ sessions/month at the same low acquisition cost as well-done SEO.
But we can’t pretend nothing changed anymore.
Your informational traffic dropping since January?
First call = live audit of your queries hit by AI Overviews, with real impact calculation and long-tail compensation plan. No theory: I look at your Search Console logs live.
No. The study shows they appear on 42% of queries, mainly generic informational queries. Direct transactional and ultra-specific queries are far less affected.
Does the -38% impact apply to all sectors?
The study gives a global -38% number. By my observations on 47 client sites, impact ranges -18% (SaaS) to -52% (media/content). E-commerce: approximately -30% average.
How do I know if my pages are hit by AI Overviews?
Compare average CTR of your informational pages between December 2024 and March 2025 in Google Search Console. A 25%+ drop without position change likely indicates active AI Overview.
Can you optimize content to appear in AI Overviews?
Google gives no official guidance. Sources cited in AI Overviews generate almost no clicks per the study. Better to pivot to ultra-specific long-tail queries.
Should I stop investing in SEO informational content?
No, but redirect 50% of budget to ultra-targeted long-tail (less AI Overview touched) and 20% to off-Google channels (YouTube, Reddit, newsletters).
