In Q2 2025, Google’s new AI Overview (AIO) answers siphoned off more than a quarter of the clicks that once hit ads or top organic results.
Google's AI Overviews now appear in 13% of searches and create 27% zero-click rates on desktop (75% mobile). The #1 organic result loses 34.5% of clicks when an AI Overview is present.
Bottom Line: If you're not cited in the AI Overview, you're invisible where users form their first impressions. Pages with schema markup are 3x more likely to earn AI citations.
Your prospects now skim an AI-generated summary at the top of Google’s results (position zero) before they ever see an ad or organic listing. That AI Overview (AIO) can push your brand to the forefront with a cited snippet, or bypass you entirely and siphon away traffic. For marketing leaders, AIOs are the new frontline for awareness, authority, and conversion.
How do these answer blocks work? What's the ripple effect on organic and paid performance? How do you capture share-of-voice as search evolves from “query” to “conversation," and your insight content goes straight to the AIO, leaving your company out of the engagement?
Google is no longer a single SERP to “rank” in; it’s a collection of layers, with AI Overviews now sitting on top of roughly one in eight U.S. queries (13.14 % as of March 2025). Because that generative answer immediately addresses the searcher’s intent, it has resulted in a 27% zero-click rate on desktop and 75% on mobile. In other words, visibility that used to belong to ads and classic blue links is being intercepted before the funnel even opens.
To stay relevant, there are three overlapping, but distinct, optimization targets (SEO, GEO, LLMO):
GEO focuses on crafting concise, citation-ready “answer nuggets” and structured data so the generative engine lifts your content. LLMO pushes that idea further, engineering machine-readable insights and brand vectors that travel with the user into chatbots, voice assistants, and vertical AI tools. Classic SEO fundamentals still matter, but they’re now a foundation for reaching layers two and three.
On most informational queries the sequence now looks like this:
AI Overview block (Position 0) – multi-source summary, link carousel, follow-up chips
Optional Featured Snippet – single-source excerpt, often pushed beneath the AIO
Ads / Shopping (shrinking above the fold)
Organic listings
This stacking order is more than cosmetic. Two large-scale studies show that the presence of an AIO chops the click-through rate of the #1 organic result by about one-third (-34.5 %), and when an AIO and featured snippet appear together the loss can deepen to -37 %. Even featured snippets themselves take a hit, with publishers reporting a 25 % drop in their historical CTR when an AIO is also present.
Traditional SEO (rank, impressions, clicks) no longer tells the full story. You may “own” the featured snippet yet still miss the conversation happening above it, where prospects form first impressions without ever landing on your page. Mastering GEO and LLMO alongside SEO is therefore the only way to secure share-of-voice in a SERP that has shifted from query to answer.
Here's break down of how the AI Overview pipeline works:
Top-of-page real-estate now arranges itself in five distinct layers. A well-placed image can be just as influential as a blue link:
Visual authority matters. A compelling, well-marked diagram can leapfrog text results and win the second-most prominent slot on the page.
Snippet cannibalization is significant. When both an AIO and a featured snippet appear, the snippet’s CTR typically falls; the image pack can soften that blow if it’s yours.
Optimization now spans three layers. SEO secures the link, GEO wins the AIO citation, and smart image/diagram markup earns the visual card, together controlling the story a prospect sees before they click.
ClickPoint Software, historically, had difficulty ranking for the broad "lead management" keyword. As a relatively small company with a product aimed at professionals, the competition was just too steep (Hubspot, Salesforce) to rank for the broad term. Through a simple, unique explanatory diagram within ClickPoint's content, ClickPoint were able to achieve the #1 spot as a visual card, above all competitors content and ads.
When a user asks a complex question, Google explodes it into dozens of simpler sub-queries (“query fan-out”) and sweeps the web for short, high-relevance text chunks called passages. Each passage is reranked for freshness, authority, and topical variety before anything touches the language model.
The top passages feed a retrieval-augmented generation (RAG) step driven by Gemini 2.5—a lighter, search-tuned version of Google’s flagship model. Because the model may only quote the retrieved passages (not its stored training data), hallucinations drop and every sentence can carry a live link. The draft answer is trimmed to about 2–4 sentences and a link carousel.
If one passage clearly outperforms the rest on relevance and clarity, Google lifts it verbatim as a Featured Snippet (the familiar single-source box). When several passages tie, they stay as multi-source citations surrounding the AI Overview. Owning the snippet often pre-positions you for a citation, but not the other way around.
Before surfacing, the draft runs through automated safety gates that block harmful or low-trust content. It then meets Google’s E-E-A-T (Experience, Expertise, Authoritativeness, Trust) safety filter, plus core page-experience signals like loading speed and schema hygiene. Passages that fail here are dropped, even if they ranked well earlier.
Together these four steps explain why technical SEO lets you enter the race, but GEO tactics (citation-ready nuggets, robust schema, demonstrable expertise) determine whether the generative layer actually quotes you, or your competitor, in the answer that users see first.
Search visibility now breaks into three complementary layers, each with its own levers and KPIs. Treat them as a stack, not silos.
Key distinctions
Input surface: SEO targets the crawler; GEO targets Gemini’s retrieval set; LLMO targets the training or RAG corpus of every major LLM.
Output surface: SEO wins links; GEO wins citations & visuals; LLMO wins brand mentions inside conversational answers everywhere.
Feedback loop: measure SEO progress in Google Search Console; track GEO wins in AIO-monitoring tools like BrightEdge or Authoritas; gauge LLMO impact by running the same test prompts in chatbots each month to determine whether the AI now groups your brand closer to your target keywords, and farther from competitors.
Why all three matter together
Eligibility cascade – Clean technical SEO gets your content into the retrieval pool.
Citation capture – GEO tactics convince Gemini to quote you in the answer block that most users read first.
Conversation carry-over – LLMO ensures that, when prospects continue the journey in chatbots or voice agents, your brand remains the recommended choice.
JSON-LD schema markup has evolved from an SEO nice-to-have to a critical requirement for AI Overview citations. Google's generative engine relies on structured data to understand content context and determine citation worthiness.
FAQ Schema – Structures answer nuggets for easy AI parsing and quoting.
HowTo Schema – Perfect for step-by-step content that frequently appears in AI summaries.
ImageObject Schema – Helps diagrams earn visual card placement below AI Overview text.
Organization/Person Schema – Strengthens E-E-A-T signals for citation eligibility.
Pages with comprehensive JSON-LD markup are 3x more likely to appear in AI Overviews. The markup bridges your content with Google's understanding algorithms.
For complete implementation guidance, see our comprehensive schema markup guide.
How do these layers interact with organic CTR, ad performance, and overall funnel health?
Organic visibility now hinges on where you’re cited, not how high you rank.
• A single cited sentence can out-shine a top ranking blue link because the reader never scrolls that far.
• Pages that answer narrow follow-up questions often surface in the Overview even if the page itself sits on page three.
• Writers who frame every section as a self-contained “answer nugget” earn far more surface area than those chasing one perfect keyword cluster.
Paid media visibility is in decline.
• When an Overview satisfies intent, shoppers don't reach search ads. Budgets tied to broad, information-heavy queries suffer most.
• Brands that appear inside the Overview often see higher click-through on the ads that follow—they’ve already been endorsed by the AIO, so the ad feels like a next step.
• Smart teams sync headline language and offer hooks to whatever the Overview highlights (“Compare our service to X and Y”).
Search results pages follow a new hierarchy.
• An AI answer block can run the height of an entire mobile screen; everything below it (ads, snippets, organic links) now competes for second impression.
• Well-marked diagrams, product images, or step-by-step graphics can break through this wall: Google often inserts them just under the text summary as a “visual card,” acting like a second citation layer.
Secure the citation to offset traffic loss.
Brands that land a citation or visual in the Overview recover much of the traffic they’d otherwise lose—and enjoy a halo effect across paid campaigns and social shares. In practice, that means:
Track citation share, not just rank. Treat Overview mentions as a KPI alongside classic positions.
Budget flexibly. Shift spend toward branded and remarketing audiences when your content already earns the AI’s nod; pour discovery dollars into queries where you’re absent.
Curate “second-click” assets. If the Overview quotes you, be sure the landing page offers an enhanced view. Assets such as interactive tools, calculators, or richer media give visitors have a reason to continue the journey on your site.
Keep one clear, short answer high on the page—preferably under an H2 that mirrors the query.
Avoid colorful filler and open with the core fact.
Refresh quarterly to protect current relevance signals.
Add a short “answer nugget” directly below each major heading.
Mark it with FAQ or HowTo schema so Gemini can parse and quote it.
Include a publication date and byline to reinforce E-E-A-T.
The image above shows a staged citation optimization strategy.
Supply diagrams or process graphics in SVG/PNG and wrap them in ImageObject schema with descriptive alt text (“lead-management-workflow-diagram”).
Host visuals on the same URL as the nugget so both can surface together in the Overview.
Publish machine-readable datasets (CSV, JSON-LD) that state your key stats—pricing tiers, integrations, user counts.
Use consistent naming (“Acme CRM”) across docs, PR, partner sites, and Wikipedia to tighten the model’s entity resolution.
Mirror the language the Overview uses in your RSAs and Performance Max assets.
Bid protect branded terms when your citation share is low; ease spend when you dominate the Overview.
Execute these steps in sequence—snippet, citation, vector, alignment to shift an AI-dominated results page from an obstacle to an advantage.
Traditional SEO metrics like rankings and organic CTR only tell part of the story when AI Overviews dominate the first screen. You need new KPIs that measure performance at each stage of the AI-first funnel: getting cited, retaining authority, and converting AI-assisted traffic.
Citation Share – Percentage of AI Overviews that link to your domain for tracked keywords. This replaces "average position" as your primary visibility metric.
Snippet Retention Rate – How often you maintain Featured Snippet ownership after Google re-crawls your content. High retention signals content quality and relevance.
Conversation-Assisted ROAS – Revenue generated from users who saw an AIO citation of your content before converting. Tracks the business impact of AI visibility.
The KPIs in the above diagram map to the new marketing flow: seen in the answer → clicked through the noise → stayed authoritative → generated revenue or leads. Traditional rank and CPC still matter, but these KPIs show whether you are visible inside the AI layer—and whether that visibility turns into business.
The first screen now solves most queries. Users gravitate to concise, data-backed statements that the Overview can surface, then decide whether deeper context is worth a click. Lengthy and flowery content is out of step with this compressed journey. Concise and professional content serves both the AIO and site visitors.
Google still relies on E-E-A-T, backlinks, and other page signals to decide which domains qualify for citation. Within that trusted set, the system lifts the passage that resolves the query fastest. Small publishers can appear, but only when their content meets the same quality filters that govern larger sites.
A citation inside the Overview acts as an implicit endorsement; its absence can signal irrelevance. Brand credibility is therefore co-managed by the language model, making accuracy, schema hygiene, and consistent brand references critical.
Rank and click data capture behavior after the Overview. Awareness and preference often form inside the AIO, invisible to legacy tracking. There is an increasing reliance on citation share, zero-click conversions, and LLM brand-mention sentiment to gauge influence.
Major publishers and search platforms are hashing out new rules: payment for AI-generated summaries of their content, clear opt-out options for sensitive material, and paid placements inside the Overview itself. Content strategies need flexibility to accommodate revenue sharing, paid call-outs, or other emerging models.
Early tests already let users buy products, book appointments or generate personalized quotes directly from the Overview. Brands that expose structured APIs or live inventory can participate in these task flows; static, page-bound information risks being bypassed.
AI Overviews don’t just compress the results page, they compress the traditional "customer journey." An effective marketing strategy now centers on owning the content that an AI Overview selects. Smart marketers will seek to shape decisions that form before users ever click through.
Explore additional AI marketing topics.
Data sources include:
https://searchengineland.com/google-ai-overviews-organic-results-overlap-99-445374
https://developers.google.com/search/docs/fundamentals/creating-helpful-content
What percentage of searches now show AI Overviews?
AI Overviews appear in approximately 13.14% of U.S. queries as of March 2025, with Google continuing to expand coverage across more query types.
How much traffic do AI Overviews steal from organic results?
AI Overviews create a 27% zero-click rate on desktop and 75% on mobile. The #1 organic result typically loses 34.5% of its click-through rate when an AIO is present.
What's the difference between SEO, GEO, and LLMO?
SEO optimizes for traditional blue link rankings, GEO focuses on earning citations within AI Overviews, and LLMO shapes how all AI models (ChatGPT, Copilot, etc.) reference your brand across platforms.
Can small companies compete with large brands in AI Overviews?
Yes. AI Overviews select content based on passage-level relevance, not just domain authority. Small companies can win citations with well-structured, concise answer nuggets that directly address user queries.
How do I track if my content appears in AI Overviews?
Monitor Citation Share (percentage of AI Overviews linking to your domain) using tools like BrightEdge or Authoritas. Track this alongside traditional rank and CTR metrics.
Should I still focus on Featured Snippets?
Yes. Featured Snippets often pre-position you for AI Overview citations, though they lose traffic when both appear together. Optimize for both simultaneously.
How long should answer nuggets be for GEO?
Keep answer nuggets between 40-80 words. This length provides enough context for AI models while remaining concise enough for citation selection.
Do AI Overviews hurt paid search performance?
AI Overviews push ads below the fold and can reduce overall click volume, but brands cited in the Overview often see higher ad CTRs due to the credibility boost.
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