What Search Intelligence Actually Means
Search intelligence is the practice of monitoring, analysing and improving how your brand appears across AI-powered search platforms. It covers ChatGPT, Gemini, Claude and Google AI Overviews. It tells you whether AI recommends your brand, how accurately it describes you, and what your competitors look like in the same answers.
This is different from traditional SEO. SEO tells you where your web pages rank. Search intelligence tells you what AI says about your brand when a customer asks a question.
The distinction matters because AI is now where a growing share of product and service discovery happens. 68% of Google searches end without a click. ChatGPT has over 800 million weekly users. When someone asks "what's the best project management tool?" or "which hotel should I book in Barcelona?", the answer comes from AI. If your brand is not in that answer, you don't exist in that moment.
We analysed 5,600 queries across four AI platforms to understand how this works in practice. The findings shaped everything in this guide.
Why Search Intelligence Matters Now
Three things have changed in the last 18 months that make search intelligence essential.
AI Overviews are everywhere. Google now shows AI-generated answers on the majority of search results. These compressed summaries sit above the organic listings. They answer the question directly, and most users never scroll past them. If your brand is not mentioned in the overview, your website ranking becomes less relevant.
Conversational search is mainstream. ChatGPT, Gemini and Claude are no longer niche tools. They are how millions of people research products, compare services and make decisions. These platforms don't show a list of ten blue links. They give one synthesised answer. Your brand is either part of that answer or it is not.
Traditional metrics don't capture this. Google Analytics shows you traffic. SEO tools show you rankings. Neither shows you what ChatGPT says when someone asks about your category. Search intelligence fills that gap. It gives you the data to understand and influence how AI talks about your brand.
The Three Layers of Search Intelligence
Search intelligence is not one metric. It's a framework built on three layers, each answering a different question.
1. Visibility: Does AI know you exist?
The most basic question. When someone asks AI about your category, does your brand appear at all? Our research found that brand mention rates vary dramatically by platform:
- Gemini mentions brands in 82.5% of responses
- ChatGPT mentions brands in 74.2%
- Claude mentions brands in 70.1%
- Google AI Overviews mentions brands in just 42.5%
A brand that looks visible on Gemini may be completely absent from Google AI Overviews. You can't measure this by checking one platform.
2. Positioning: How does AI describe you?
Being mentioned is step one. What AI says about you is step two. Search intelligence tracks whether your brand is described accurately, whether it's recommended or just listed, and where in the response you appear.
This matters because position within an AI response affects perception. Claude mentions brands earliest, at 8.5% into the response. Google AI Overviews and Gemini mention brands later, around 20% in. ChatGPT sits in the middle at 17.5%. Appearing first signals authority. Appearing last, buried after three competitors, signals an afterthought.
Recommendation rate tells an even sharper story. ChatGPT explicitly recommends brands 8.9% of the time. Claude and Gemini both recommend at 7.3%. Google AI Overviews almost never recommends, at just 0.2%. The difference between being mentioned and being recommended is the difference between awareness and conversion.
3. Context: What triggers your appearance?
The third layer examines which queries surface your brand and which don't. Our data shows that AI platforms change behaviour significantly based on query intent.
When queries shift from general discovery ("best hotels in Paris") to booking intent ("book a hotel in Paris for Saturday"), ChatGPT contracts its response length by 33%. All platforms increase hedging language by 2.7x to 4x for transactional queries. Google AI Overviews uses 4.3x more superlative language ("best", "top", "leading") on comparison queries than on discovery queries.
Search intelligence maps which queries your brand wins, which it loses, and why. That's where strategy starts.
How Each Platform Handles Brand Discovery
One of the most important findings from our research is that each AI platform has a distinct personality. They don't just give different answers. They structure information differently, cite sources at different rates, and show varying levels of willingness to name specific brands.
| Metric | Google AIOs | ChatGPT | Claude | Gemini |
|---|---|---|---|---|
| Average answer length | 83 words | 422 words | 241 words | 679 words |
| Brand mention rate | 42.5% | 74.2% | 70.1% | 82.5% |
| Brands per response | 1.1 | 2.7 | 1.9 | 3.4 |
| Brand position in response | 21% in | 17.5% in | 8.5% in | 20.2% in |
| Recommendation rate | 0.2% | 8.9% | 7.3% | 7.3% |
| Citation rate | 3.1% | 28.6% | 8.7% | 30.4% |
| Output consistency | Varies | CV 19.1% | CV 20% | CV 9.8% |
Several patterns stand out.
Google AI Overviews is the outlier. At 83 words, it gives the shortest answers by a wide margin. It mentions brands less often (42.5%), lists fewer per response (1.1), and almost never recommends (0.2%). It's the hardest platform to get visibility on and the one with the largest audience.
Gemini is the most generous. It writes the longest responses (679 words), mentions the most brands (3.4 per response), and cites sources most often (30.4%). But its output is also the most templated, with a coefficient of variation of just 9.8%. It follows a consistent structure regardless of the query.
ChatGPT is the most likely to recommend. At 8.9%, it has the highest recommendation rate. It also writes substantial responses (422 words) and cites sources frequently (28.6%). For brands that want to be actively recommended rather than just mentioned, ChatGPT is the platform to focus on.
Claude is the most concise and the fastest to mention brands. At 241 words, Claude gives tight, focused answers. When it does mention a brand, it does so early, at just 8.5% into the response. Claude cites sources less often (8.7%), which means visibility depends more on brand authority than on having specific pages indexed.
Search Intelligence vs Traditional SEO
Search intelligence and SEO are not the same thing. They complement each other, but they measure different things, use different signals, and require different strategies.
| Dimension | Traditional SEO | Search Intelligence |
|---|---|---|
| What you track | Page rankings, traffic, clicks | Brand mentions, recommendations, sentiment across AI |
| Where it happens | Google search results | ChatGPT, Gemini, Claude, Google AIOs |
| What drives visibility | Keywords, backlinks, page speed | Third-party mentions, entity authority, content quality |
| Key metric | Position on page 1 | Share of memory across platforms |
| User behaviour | Click a link, visit a website | Get an answer, may never visit a website |
| Competitive insight | Who ranks above you | Who AI recommends instead of you |
The most important difference is the last row. In SEO, your competitor is the page that outranks you. In search intelligence, your competitor is the brand that AI recommends when it could have recommended you. That's a fundamentally different problem to solve.
For a deeper comparison of optimisation approaches, see our guide to GEO vs SEO.
What a Search Intelligence Programme Looks Like
Search intelligence is not a one-off audit. It's an ongoing discipline, similar to how SEO monitoring works but adapted for AI platforms. A typical programme has four phases.
Phase 1: Baseline audit
Measure your current visibility across all four platforms. Test 50 to 100 keywords that your customers actually use. Record which platforms mention you, how often, in what context, and which competitors appear in the same responses. This gives you a visibility score and a competitive benchmark.
Phase 2: Gap analysis
Identify where you are invisible and why. Our research shows that visibility gaps usually come from one of five root causes: weak third-party mentions, missing structured data, thin content on key topics, low citation authority, or poor entity recognition. Each requires a different fix. Read our breakdown of why brands don't show up in AI answers for the full list.
Phase 3: Optimisation
Execute targeted improvements based on the gap analysis. This might mean building out FAQ content that AI can directly cite. It might mean improving your presence on Reddit, review sites and industry publications, since AI pulls heavily from third-party sources. It might mean restructuring your website with clearer entity markup so AI models can understand who you are and what you do.
Phase 4: Ongoing monitoring
AI models update regularly. Your competitors are working on their visibility too. Monthly monitoring tracks your share of memory over time, flags new competitors entering the conversation, and identifies queries where your visibility is shifting. This is where search intelligence becomes a competitive advantage rather than a one-time project.
The Sources AI Relies On
Understanding where AI platforms get their information is central to search intelligence. Our research found clear patterns.
Third-party sources dominate. AI models don't just read your website. They synthesise information from Reddit discussions, review platforms, news articles, industry publications and expert content. A brand with strong third-party mentions will outperform one that only has a well-optimised website.
Citation behaviour varies by platform. Gemini cites sources in 30.4% of responses, making it the most transparent about where it gets information. ChatGPT cites at 28.6%. Claude is more conservative at 8.7%. Google AI Overviews rarely cites, at just 3.1%. This means the path to visibility is different on each platform. On Gemini and ChatGPT, having citable content matters. On Claude and Google AIOs, overall brand authority matters more.
Structured data helps. FAQ schema, organisation schema and product schema give AI models clean, structured information to work with. This doesn't guarantee visibility, but it removes friction. AI can parse structured data more reliably than unstructured prose.
Measuring Search Intelligence
Search intelligence uses a set of metrics that don't exist in traditional analytics. Here are the ones that matter most.
- Share of memory: The percentage of relevant queries where your brand appears in AI responses. This is the headline metric. See our full guide to measuring share of memory.
- Recommendation rate: How often AI actively recommends your brand, not just mentions it. Our data shows this ranges from 0.2% (Google AIOs) to 8.9% (ChatGPT).
- Competitor share: Which brands appear in the same responses as you, and how often they appear instead of you.
- Platform coverage: Whether your visibility is consistent across all four platforms or concentrated on one.
- Sentiment accuracy: Whether AI describes your brand correctly or with outdated or inaccurate information.
- Citation rate: How often AI links back to your content as a source.
For a practical framework on implementing these metrics, see how to measure AI search visibility.
Getting Started
Search intelligence is still early. Most brands haven't started measuring it. That's both a risk and an opportunity.
The risk is clear: if your competitors are building their AI visibility and you are not, they will own the conversation in your category. Our data shows that the brands AI mentions most tend to get reinforced over time. Early advantage compounds.
The opportunity is equally clear: because this is new, the bar for entry is lower than it will ever be. A structured approach to search intelligence today will pay dividends as AI search grows.
Start with three steps:
- Check your current visibility. Use our free AI visibility check to see where your brand stands right now across ChatGPT, Claude and Gemini.
- Understand the competitive landscape. Find out which brands AI recommends in your category and why.
- Build a monitoring habit. AI models change. Your visibility will shift. Track it monthly at minimum.
Search intelligence is not a nice-to-have. It's the next layer of competitive intelligence for any brand that depends on being found. The question is not whether to start. It's how quickly you can build a lead before your competitors do.