AI Search Optimization
68% of US Google searches now end without a click (SparkToro, 2026). AI is answering your customers' questions directly. If your brand isn't showing up in those answers, your competitors are getting the recommendation instead.
of US Google searches end with no click (SparkToro, 2026)
AI platforms we measure
of AI citations come from earned media (Muck Rack, May 2026)
AI search optimization is the practice of improving how your brand appears in AI-generated answers. When someone asks ChatGPT "what's the best travel agency for luxury holidays?" or Google's AI Overview summarises "top CRM platforms for small businesses", AI search optimization determines whether your brand gets mentioned, cited, or recommended.
It's different from traditional SEO. You're not optimising for rankings on a results page. You're optimising for inclusion in an AI-generated answer. The signals that matter are different: structured data, third-party mentions, entity authority, and citation-worthy content.
And the stakes are high. 68% of US Google searches now end without a click (SparkToro, 2026). Your customers are getting answers directly from AI. If your brand isn't part of those answers, you're invisible at the exact moment someone is ready to buy.
In our published study of 100 UK buying questions across six AI platforms, the platforms behaved very differently: Google AI Overviews named the fewest brands per answer (3.3 on average) and Claude the most (6.2). Most brands have never checked which side of that gap they sit on.
Not all AI search is the same. Each platform pulls from different sources, weighs signals differently, and recommends brands for different reasons. Understanding this is the first step to showing up.
Google AI Overviews draw on Google's own search index. Ranking well helps, but it is not enough: Ahrefs found only about 38% of AI Overview citations came from pages in the top 10 organic results (March 2026). Reddit threads, review sites and forums are cited too.
ChatGPT uses a combination of its training data, Bing search results, and browsing. It favours content that directly answers questions with specific, structured information. Third-party mentions carry significant weight. If reviewers and publishers mention your brand, ChatGPT is more likely to recommend it.
Gemini leans on Google's knowledge graph and search index. Strong entity signals, clear brand associations, and structured data all increase your chances. Gemini tends to recommend brands it can confidently associate with a category.
Claude runs its own web searches when a question needs current information, and in our published study it named more brands per answer than any other platform. Brands with a strong, consistent presence across independent sources do best here.
Perplexity actively searches the web in real time and cites its sources. It pulls from recent articles, reviews, and discussions. If your brand is being talked about on credible sites right now, Perplexity is more likely to find it.
The takeaway: you need to be visible across all of them. A brand that dominates on Perplexity but is invisible on ChatGPT is only reaching a fraction of its audience. Each platform requires a slightly different approach, and that's exactly what we map out.
We combine proprietary monitoring technology with 20 years of search strategy expertise.
We agree the buyer questions, markets and competitors, run them across ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews and Google AI Mode, and trace who is recommended, who is only mentioned and which sources the answers lean on. You get an evidence baseline, a prioritised action brief and a leadership readout.
We brief the changes the diagnostic points to: your pages, the third-party sources the answers cite, and the evidence those sources carry about you. Your team or agency implements.
We re-run the same questions on a fixed schedule and report what moved and what did not, with the sources behind each change.
Most AI search tools show you a dashboard. Most agencies give you a list of tactics. SearchIntel interprets the data and briefs the changes; your team or agency implements them, and we re-measure. Here's what that looks like in practice.
We query every major AI platform with your target keywords and record exactly where your brand appears, where it doesn't, and which competitors are getting recommended instead. This isn't a one-time check. We run multiple queries per keyword to account for the variability in AI responses.
We identify the questions your customers are asking that AI is answering without you. These are the gaps where competitors are winning recommendations. We map every gap to a specific content action, so you know exactly what to create and where to publish it.
Structured data helps AI models understand what your business does, where you operate, and what makes you different. We specify the Organisation, Product, Service and Review markup your developers should add, so AI platforms can associate your brand with the right categories.
84% of AI citations come from earned media, not brand websites (Muck Rack, May 2026). Reddit threads, review sites, industry publications, comparison articles. We build a strategy to get your brand mentioned in the places AI models actually pull from. This is where most brands have the biggest gap.
AI answers change constantly. A competitor publishes a new review roundup and suddenly they're getting recommended where you were. We re-run the same questions on a fixed schedule so you can see what shifted, and what to do about it.
AI search optimization isn't for everyone. It matters most for brands where being found at the moment of decision is worth real money. If that's you, this is the section that should resonate.
You're watching organic traffic decline and can't explain why. The answer is that your customers are getting recommendations from AI before they ever reach a search results page. You need visibility into this new channel before your competitors lock it down.
You know traditional SEO isn't enough anymore. You've seen the AI Overviews rolling out. You've noticed traffic dropping on queries where you used to rank #1. You need a strategy that accounts for the answer layer, not just the results page.
You need a strategic narrative for leadership. "AI is answering our customers' questions and we're not in the answer" is a board-level problem. We give you the data, the benchmarks, and the plan to present to your team.
Your pipeline depends on being found. If AI is recommending your competitor instead of you during the research phase, you're losing deals before your sales team even gets a chance. AI search visibility is the new top of funnel.
SearchIntel was founded by Paul Byrne, who has spent 20+ years in search strategy. He led search at MediaCom for Adidas, Shell, and Coca-Cola, and led the global digital transformation of LEGO's search and content programmes at IPG Mediabrands. He worked at Google. He ran search strategy client-side at TripAdvisor and Viator.
That experience matters because AI search isn't just a technology problem. It's a strategy problem. Knowing which signals to prioritise, how to build authority across platforms, and where the real opportunities are: that comes from two decades of understanding how search works and how it evolves.
We've built proprietary monitoring technology that tracks brand visibility across ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews, and Google AI Mode. Our published research sets out the method and the limits. We measure, benchmark, and show you where you stand.
Most tools just show the data. Most agencies just give tactics. We interpret the data and tell you what to change. That's the difference.
See how your brand appears across ChatGPT, Claude, Gemini, Perplexity and Google AI Mode. Takes about 30 seconds.
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