Legacy Business

AI Search: The Six Vital Content Traits For Citation

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There is a question that more business owners are starting to ask, and it matters more than most of them realise.

When a potential customer opens ChatGPT, Claude or Perplexity and asks which local solicitor handles commercial leases, which car dealer in Norwich carries approved used BMWs, or which estate agent consistently sells in their road, whose name comes up?

In most categories, the same handful of businesses get cited again and again. Everyone else is invisible.

This is not random. AI engines do not pick names out of the air. They pull from pages that are structured in a very specific way. If your website is not built that way, it will not be quoted, regardless of how long you have been in business or how good your Google ranking is.

The question is: what does a citable page actually look like?

Having studied in detail how AI search works across multiple platforms, six traits appear on every page that earns consistent citations. Miss one and your chances drop. Miss three and you disappear entirely.

Trait one: The heading is the real question

Not a clever marketing line. Not a vague label. The actual question your customer would type.

If someone asks an AI which estate agents in Worthing sell the most family homes, your page heading should reflect exactly that. “Our services” does not get you cited. “Which estate agents sell the most family homes in Worthing?” might.

AI engines match queries to headings before they read a single word of your copy. If the heading does not fit the question, the page is skipped.

Trait two: The first sentence answers the heading directly

No warm-up. No scene-setting. No “it is a great question” preamble.

The answer goes in the first sentence. Two sentences at most. Then you can expand.

Most business websites do the opposite. They spend three paragraphs building context before they say anything useful. By then, the AI has moved on to a competitor who answered in line one.

Trait three: One specific fact that only you own

This is the one that most businesses overlook, and it is probably the most important.

Generic claims do not get pulled. “We have years of experience” earns nothing. “We have sold 47 properties within half a mile of the seafront in the last 18 months, with an average of 11 days to offer” earns citations.

The fact does not need to be dramatic. It needs to be specific, true, and yours alone. A price. A ratio. A timeline. A count. A measured outcome from your own business.

AI engines are looking for something they can lift and use without having to verify it against ten other sources. A first-party number is exactly that. A generic claim is not.

Trait four: A real person behind the page

A named author. A photograph. A bio that says something specific about their experience. Ideally a small piece of markup behind the scenes that tells AI platforms this page was written by an identifiable human being, not generated by a machine.

Claude and Perplexity both weight this signal. A page with a named author who has a verifiable background gets more trust than an identical page attributed to a faceless brand.

This is straightforward to fix if you have not done it. Add your name to the pages that matter. Write three sentences about your actual background. Make it specific. “20 years in automotive retail, including 12 years managing franchised BMW and Audi sites in the south east” is useful. “Passionate about cars” is not.

Trait five: A structure the AI can scan

Short paragraphs. Clear subheadings. The occasional list where it genuinely helps. White space.

A 900-word page with seven tight sections consistently outperforms a 1,400-word page with three sections and one dense block of copy beneath each, because the engine can locate the relevant passage quickly rather than working through a wall of text.

This is not about dumbing down your writing. It is about making it easy to extract. The underlying thinking can be as sharp as you like. The structure needs to let the engine find the answer without having to dig.

Trait six: No filler

Every filler phrase weakens your entire page, not just the sentence it appears in.

“In today’s competitive landscape.” “Navigating the world of.” “We are committed to delivering excellence.” “At the heart of everything we do.”

AI platforms have learned to classify these phrases as low-signal text. When they appear, the surrounding paragraphs lose credibility. The page reads as generic content, produced to fill space rather than answer a question.

Cut them. Every single one.

What this means in practice

Run through your three most important pages, the ones a customer lands on when they are close to making a decision.

Read the first sentence under each subheading. Does it answer the heading directly? If not, rewrite it so it does. Then add one specific first-party fact to each section. Then check whether a named author with a real bio appears on the page.

That is an afternoon’s work. Not a redesign. Not a new content strategy. Just making what content you already have citable.

The businesses that show up when a potential customer asks an AI for a recommendation are not necessarily the biggest, the oldest, or the best-ranked on Google. They are the ones whose pages are easy to quote.

At the moment, most of your competitors have not made that adjustment. That gap will not stay open for long.

Steve Coulter is a GEO and AI search consultant at State of the Art Digital. He works with automotive retailers, estate agents and professional services firms on AI visibility strategy.

AI Search: Learn About AI Agents and PageSpeed

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PageSpeed and AI Agents: What Your Website Now Has to Do

Your website was built for human visitors. AI agents have different expectations entirely.

They do not just crawl your pages. They read them, follow your links, extract information and decide whether your business is worth mentioning in the answer they deliver to a real person.

This piece covers what your site now needs to do to stay visible in that process.

For most of the last decade, website speed was straightforward. Faster pages meant people stayed longer, bounced less and bought more. Google rewarded the fast ones. Slow sites fell behind.

That logic still holds. But there is now a second audience your website has to satisfy, and it has entirely different requirements.

AI assistants, AI search engines and autonomous AI agents are increasingly browsing the web on your customers’ behalf. They do not just look at your pages. They read them, follow your internal links, extract information, compare it with information from other sites and deliver a final answer back to the user.

Whether your business gets mentioned in that answer depends, in part, on whether your website is built in a way that makes sense to a machine.

This is what people mean when they talk about agentic browsing. And it changes what a good website actually needs to do.

Why PageSpeed Still Matters

Google’s PageSpeed Insights tool measures how quickly and reliably your pages load and behave. It draws on real-world data from Chrome users as well as its own laboratory testing.

The three figures that matter most are:

Largest Contentful Paint. How quickly does the main content appear on screen?

Interaction to Next Paint. How fast does the page respond when someone does something?

Cumulative Layout Shift. Does the page jump around while it loads, or stay stable?

These were designed with human visitors in mind. But AI systems have a very similar set of requirements. Pages that load fast, stay stable and render cleanly are easier for AI crawlers to process correctly. Pages that are slow, bloated or dependent on complex JavaScript are more likely to be misread, partially read or ignored.

What an AI Agent Actually Does

A traditional search engine sends a crawler to read your page and add it to an index. That crawler is not trying to understand your business. It is collecting text and signals.

An AI agent does considerably more.

It might land on your homepage, follow a link to a service page, read a case study, extract a specific fact, cross-reference it with something on a competitor’s site and then produce a summary recommendation for the person who asked. All without a human clicking a single link.

This is closer to how a researcher works than how a crawler works. And it means your website has to be navigable, logical and explicit in a way that most sites currently are not.

What Your Website Needs

None of this requires a complete rebuild. Most of it is good web practice that was being neglected long before AI arrived.

Pages that load quickly. AI crawlers have a limited processing budget. Excessive scripts, oversized images and slow servers consume that budget before the page is properly read. Keep things lean.

Layouts that stay still. If your page shifts around while it loads, an AI system has to recalculate where everything is. That increases the chance of misinterpretation. Stable pages are more reliably understood.

A clear content structure. Every page should have one main heading, supported by logical subheadings, concise paragraphs and, where relevant, bullet lists, tables and FAQs. This is not about formatting for its own sake. It is about making it unambiguous what each section is trying to say.

Proper HTML. Semantic HTML elements such as header, main, article, nav and footer are not decorative. They tell machines what role each part of the page plays. An AI system reading a well-structured HTML document has far less guesswork to do than one reading a div-soup layout built entirely for visual effect.

Content that exists in the HTML. If important information is hidden behind a JavaScript widget, loaded on interaction or stored inside an image, there is a reasonable chance an AI system will never see it. Critical content needs to live in the actual page source.

Good internal linking. AI agents follow links. If your most important pages are buried three clicks deep with no logical path to them, they may simply never be found. Connect your content properly.

Schema markup. Structured data tells AI systems explicitly what type of content they are reading, who it is from and what it refers to. It does not replace good content, but it removes ambiguity.

An llms.txt file. This is a relatively new development. An llms.txt file sits on your website and tells AI systems which pages are most important and most trustworthy. Think of it as a curated map of your site, written specifically for AI models rather than human visitors.

The JavaScript Problem

A significant number of modern websites are built on JavaScript frameworks that assemble the page in the browser rather than delivering it ready-made from the server.

Human visitors rarely notice this. Their browsers handle it.

AI crawlers are less forgiving. If a crawler cannot fully execute the JavaScript, it may see a blank page or a stripped-down version of your content. The risk is that your most important information simply does not exist, as far as the AI is concerned.

The practical answer is to ensure that important content is rendered server-side before it reaches the browser. Your developer will know what this means. If they are building or rebuilding your site, it is worth asking the question directly.

A Simple Test

If you want to get a sense of how well your site works for AI systems, try this.

Imagine an AI assistant has been asked to find a business like yours, understand what you offer, identify a specific piece of information and reach your contact or booking page.

Can it do all of that by reading and following the structure of your site? Or would it get stuck, misled or simply run out of useful content to follow?

Most businesses, if they are honest, will find the answer somewhere in between. The gap between where they are and where they need to be is the work.

The Broader Point

Traditional search optimisation was about helping Google find your pages.

AI optimisation is about helping intelligent systems understand your pages, trust them and use them when answering questions on behalf of real people.

PageSpeed Insights remains a useful benchmark. But performance is now only part of the picture. Speed, structure, accessibility, explicit content and clear internal architecture are becoming the baseline for any business that wants to remain visible as AI search becomes the default.

The businesses that get this right early will not just rank better. They will be cited, recommended and surfaced by AI systems in ways that their slower-moving competitors will not.


Steve Coulter is an independent AI search consultant based in the UK. Through State of the Art Digital, he helps business owners understand how AI systems find, read and cite their websites, and what to do when they do not. His clients include car dealers, car dealer groups, estate agency groups and other SME businesses. His retained advisory service gives clients ongoing strategic guidance as AI search continues to change the rules. If you would like to understand where your business stands please contact me.

AI SEARCH: Free Report. Your Business Is Becoming Invisible

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AI search has changed how customers find businesses. Most business owners haven’t noticed yet.

When a potential customer uses Google AI Overviews, ChatGPT, Perplexity etc. to find a product or service, they get a recommendation – not a list of links. If your business isn’t structured in a way that AI systems can read, understand and trust, you won’t be in that recommendation. Someone else will.

I’ve spent the last 18 months developing OPTIMUM, a framework built specifically to audit and improve AI search visibility. The findings across every client audit point to the same problems.

*Your Business Is Becoming Invisible* is a short report that explains what’s happening, why it matters, and what a structured response looks like.

If you’d like a copy, text or e-mail with title: INTEL (see advert)

No automated sequence. No obligation. Just the report.

Your Business Is Becoming Invisible AI SEO Report

AI SEO: Video Is the Untapped AI Citation Asset Most Local Businesses Are Ignoring

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Punch Above Your Weight With This Two-Presence Video Strategy

Most car dealers and estate agents have been producing video for years. Walk-around stock videos, branch and forecourt tours, meet-the-team clips, market update commentaries. The content exists. The problem is almost none of it is configured to be read by an AI.

That distinction matters enormously right now.

AI search platforms – ChatGPT, Perplexity, Gemini, Google AI Overviews – do not watch video. They read the text surrounding it. They parse the title, the description, the transcript, the structured data markup, and the page context the video sits within. If those elements are absent, incomplete, or inconsistent, the video is invisible to every AI system regardless of its production quality or view count.

This is the gap that presents an immediate competitive opportunity for any local business willing to spend a few hours getting the fundamentals right.

Why YouTube Dominates AI Citation, and How That Helps You

YouTube is currently the single most-cited domain across all major AI platforms. Research from early 2026 shows it appears in roughly 16 per cent of LLM-generated answers, well ahead of any other source. This is not because AI systems are watching the videos. It is because YouTube enforces consistent metadata, generates automatic transcripts, and provides structured, machine-readable content at scale.

The implication for local businesses is significant. A YouTube channel is not just a video hosting platform. Configured correctly, it is a citation asset feeding into every major AI system simultaneously. Your video description, your chapter timestamps, your pinned comment and your auto-generated or manually uploaded transcript are all indexable text that AI crawlers can extract and attribute.

The key is understanding that the same optimisation logic applies to your own website. YouTube gives you citation reach. Your own site gives you citation authority and SEO credit. The winning strategy uses both, with a deliberate canonical structure connecting them.

The Canonical Problem Nobody Is Solving

The most common video mistake local businesses make is treating YouTube and their own website as two separate, unconnected things. A video goes on YouTube. Someone embeds it on a web page. Neither has proper metadata. Neither has a transcript. There is no structured data. The two versions compete with each other in search, and neither builds authority.

The correct approach is to establish a canonical video page on your own website and treat everything else as supporting distribution. Each video gets a dedicated page with a clear, keyword-informed title, a substantive description written in full sentences, a complete transcript published as readable text, VideoObject schema implemented in JSON-LD (Javascript Object Notation for Linked Data), and the YouTube embed as the playback mechanism.

The VideoObject schema uses the canonical page URL as its @id, which signals to search engines and AI crawlers that your site owns this content. The YouTube channel amplifies reach and feeds AI citation platforms. Your site gets the SEO equity.

This dual-presence model is the structural backbone of effective video GEO for local businesses.

What AI Systems Are Actually Reading

Understanding what an AI system extracts from a video page clarifies exactly what you need to produce. When ChatGPT, Perplexity or Google’s AI Mode retrieves a page containing a video, it is reading several distinct text layers.

The first is the page title and H1 heading. These should answer a specific, naturally phrased question. Not “Ford Focus Walkround July” but “What specification is a Ford Focus 1.0 EcoBoost? A full walk-around and honest assessment.”

The second is the video description. On YouTube this needs to be at least 200 words and should front-load the most important information. AI systems give disproportionate weight to the first third of any page’s content. The same description, or a fuller version of it, should appear on your canonical web page.

The third layer is the transcript. This is the most underused asset in local business video SEO. A 90-second walk-around video contains 150 to 200 words of spoken content. Published as visible text on the page, that content becomes indexable, citable, and attributable to your business. For a market commentary video from an estate agent, the spoken words represent genuine information gain – the kind of factual, expert content that AI systems prefer to cite.

The fourth layer is structured data. VideoObject schema implemented in JSON-LD tells AI crawlers and search engines precisely what the video contains, when it was published, how long it is, who produced it, and what page should be treated as the canonical source. Without it, AI systems are guessing at context. With it, they have a machine-readable brief. Fabulous entity and topical, semantic signals for AI citation uplift.

The Local Business Advantage

Large national brands have video teams, SEO departments and agency relationships. A used car dealer in West Sussex or a three-branch estate agent in Essex is not competing with them directly. What local businesses have is hyper-specific local expertise and genuine informational authority in a narrow geography.

An estate agent producing a weekly two-minute video on what is happening in their local property market – pricing, stock levels, buyer activity – and publishing it with a proper transcript, VideoObject schema, and a canonical page is building exactly the kind of factual, locally specific, expert-attributed content that AI systems prioritise when answering questions like “What is the housing market like in Worthing right now?” On the canonical URL page add in extra questions and answer such as; “What are the best local Secondary Schools?” and “Where are the best beaches?”

That is an answerable query. The business that has published consistent, well-structured local content over six months will own the AI citation for it. The business that has uploaded unoptimised clips to YouTube or not at all and done nothing else will not.

The gap between those two outcomes is not one of budget or resource. It is one of consistent process.

AI Search Summaries: How Smaller Brands Are Competing

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How To Get Your Brand Into AI Summaries: A Practical ‘EEAT’ Playbook

There is a version of this article that opens with a statistic about zero-click search rates, references a McKinsey report, and tells you that AI is disrupting the landscape.

You will not be reading that version.

Here is the thing that actually matters: AI search systems, whether Google’s AI Overviews, Perplexity, ChatGPT Search, or any of the others gaining users at pace, are not random. They are not black boxes that reward whoever shouts loudest. They have a logic, and that logic is remarkably close to something Google has been telling marketers for years: demonstrate Experience, Expertise, Authoritativeness, and Trustworthiness. (EEAT). The principles did not change. The stakes did.

When an AI system constructs a summary answer to a user’s question, it is making a series of editorial judgements. Which sources understand this topic? Which ones can be trusted? Which ones have said something specific and citable rather than something vague and generic? Your job, as a brand or business, is to make those judgements easy. Here is how.

Start With Positioning, Not Content

The single most common mistake brands make when trying to appear in AI-generated answers is trying to appear in too many of them. They produce content that covers broad territory. They write ultimate guides to entire industries. They want to rank for everything and end up trusted for nothing.

AI systems are not impressed by breadth. They are looking for signal, and signal requires specificity.

Consider the difference between a software company that describes itself as an all-in-one video platform and one that positions itself as the best tool for podcast editing. The first company is competing with every video tool on the internet. The second has a defined audience and a defined set of questions it can answer better than anyone else. When an AI system is asked what is the best tool for editing podcasts, the second company appears in that answer. The first probably does not.

This is not a content decision. It is a positioning decision. Narrow your claim. Own a space. The content follows from that; it does not create it.

Make Content That Is Actually Useful

Helpful content has become such an overused phrase in SEO that it has nearly lost its meaning. So here is what it actually means in the context of AI citation.

AI systems have seen every version of the generic blog post, the thin listicle, and the padding-heavy answer page. They have also seen genuinely useful writing: the forum post that actually solved someone’s problem, the how-to page that answered the tricky edge case, the comparison article that laid out real trade-offs rather than pretending every option was great in its own way.

The content that gets cited is the content that answers real questions with real specificity. Not how do I use this tool, but why does the audio desync when I import from a particular file format and how do I fix it. Not what is content marketing, but what content formats actually drive enquiries for a small professional services firm with a long sales cycle.

Your content plan should be built from questions your customers actually ask, not from keyword volume alone. Talk to your sales team. Read your support tickets. Go through your reviews. The questions are already there. Answer them with enough depth and clarity that someone with the problem right now would genuinely find it useful.

Build Pages AI Can Point To

There is a structural side to this that is often overlooked. AI systems do not just need good content; they need content in forms they can extract, attribute, and cite.

Three content types consistently perform well as AI citation targets.

Comparison pages. Comparison questions are among the most common queries AI systems receive. If you have a well-structured, honest comparison page covering your product against alternatives, you have created something AI systems can use to answer a question asked thousands of times a day. The key word is honest. Comparison pages that declare the author’s product best in every category are not useful. Pages that acknowledge genuine trade-offs are.

How-to content. Step-by-step explanations with clear sequencing and concrete actions are easier for AI systems to cite and summarise than opinion pieces or narrative articles. This does not mean how-to content cannot have a point of view; it means it should also be practical and functional.

Use-case content. Pages that describe specific applications of your product or service in specific situations give AI systems something to work with when a user’s query is about a context rather than a category. How a small accountancy firm uses project management software to handle client onboarding is more citable than a generic features page.

All of this works considerably better when supported by proper structured data. JSON-LD schema is not optional decoration. It is the vocabulary that tells AI systems what your content is, who it is about, and what it claims. If your site lacks structured data, you are asking AI systems to guess. Some will; many will not, when a better-structured competitor exists.

Use Real Visuals

AI systems with visual capabilities can process and reference visual content. More immediately, the people who train, evaluate, and ultimately trust AI systems use visuals as a quality signal.

Real product screenshots, genuine interface recordings, actual before-and-after examples, and video walkthroughs all contribute to perceived authenticity. They also make your content more useful, which loops back to the citation question. Content that helps people understand something is more likely to be cited than content that merely claims something.

There is also a simpler point here. Brands that use generic stock imagery look like every other brand. AI systems have encountered the same stock photo of a handshake or a lightbulb across thousands of websites. Real product visuals, screenshots from actual use, and genuine demonstrations stand apart. They signal that this content is about a real thing, produced by people who have actually used it.

Expand Your Presence Beyond Your Own Site

Your website is one signal. AI systems are reading many others.

Third-party mentions, reviews, press coverage, and independent creator content all contribute to the trust picture an AI system builds around a brand. When Perplexity or ChatGPT Search decides whether to include your brand in a response, it is not only reading your website. It is reading what others have written about you, in contexts you did not control and cannot directly edit.

This means PR is not separate from your visibility strategy; it is part of it. Getting covered in trade publications, being reviewed on independent platforms, appearing in podcast episodes, and being mentioned in the forums where your customers actually spend time all contribute to your perceived trustworthiness in ways AI systems can detect and weigh.

The practical implication is straightforward. Treat off-site presence as a deliberate programme rather than a nice-to-have. Identify the publications, communities, review platforms, and creators your target audience already trusts. Build genuine relationships with them. Create things worth mentioning. Earn the references rather than manufacturing them.

The Underlying Logic

Everything above serves a single purpose: making it easy for AI systems to understand what you do, trust what you say, and cite you as the source of a useful answer.

The businesses doing well in AI-mediated search right now are not necessarily the biggest ones. They are the ones already doing the work that EEAT has always demanded: positioning clearly, creating content with genuine depth, building structural credibility, and maintaining a consistent presence across the sources their audience trusts.

When AI systems can understand your positioning, trust your content, and point to specific pages you have built, the playing field levels considerably. You are not competing on budget. You are competing on clarity, depth, and genuine usefulness.

Those are things any business can build. Most simply have not started yet.

I offer an AI Risk Intelligence Briefing and Retained Advisory service to ensure your brand or business is making the most of the early-mover opportunity from AI Summary inclusion and citation. Please DM for more information and understand what this early adoption advantage is.

Below I’ve summarised my article for partner, board or C-Suite presentations.

Simple Paragraph Summary Bullet Points:

Start With Positioning, Not Content

  • Trying to rank for everything means being trusted for nothing
  • AI systems reward focused, specific positioning over broad claims
  • Decide what question you want to answer better than anyone else
  • Positioning is a business decision; content follows from it

Make Content That Is Actually Useful

  • Generic content has been seen before and AI systems know the difference
  • Answer real, specific questions drawn from real customer language
  • Use support tickets, sales conversations, and reviews to find genuine query patterns
  • Depth and clarity matter more than volume

Build Pages AI Can Point To

  • Honest comparison pages with real trade-offs are high-value citation targets
  • How-to content with clear steps maps naturally to how AI systems construct answers
  • Use-case content tied to specific situations outperforms generic features pages
  • JSON-LD structured data tells AI systems what your content actually is; without it, you are asking them to guess

Use Real Visuals

  • Genuine screenshots, recordings, and product demos outperform stock imagery
  • Real visuals are a trust signal for both AI systems and the people who evaluate them
  • Generic imagery makes your brand indistinguishable from the competition

Expand Beyond Your Own Site

  • AI systems read third-party mentions, reviews, press coverage, and creator content
  • PR is part of your AI visibility strategy, not separate from it
  • Target the publications, communities, and creators your audience already trusts
  • Earn mentions through genuine relationships and content worth referencing

The Underlying Logic

  • Clarity, depth, and usefulness level the playing field against bigger competitors
  • EEAT principles have not changed; the consequences of ignoring them have
  • AI citation is not a budget competition; it is a quality and structure competition
  • Businesses that build this foundation now will have a meaningful head start

Search: Non-Commodity Content. What?

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This is not a drill.

I make no apologies that this is a long read, but a vital one for all business owners.

The rise of AI search summaries and your highly probable non-inclusion is an existential travesty that your present agency has not flagged for you. A major problem compounded by Googles’ latest May 2026 ‘AI Optimisation Guidance’ update that totally prioritises Non-Commodity content. What? I hear you say.

Grab a coffee and learn what will make your business not only preeminent in search, but taking an unassailable early adopter advantage. I’ve used the example of Estate Agency (Real Estate Agency for US friends).

Thank me later.

The End of Commodity Content: Why Estate Agents (& All Other Businesses) Must Build Proprietary Knowledge Assets.

The strategic advantage now available to hyperlocal businesses across every sector is unprecedented. Whether you operate as an estate agent in Tunbridge Wells, a dental practice in Harrogate, or a veterinary surgery in Exeter, the competitive landscape in your immediate geography is about to be reset. Google’s May 2026 shift to answer-optimised search means that the first business in each town to build substantive, non-commodity content will dominate AI citations for their sector. The locksmith, solicitor, or accountant who documents genuine local expertise in structured, citable form will appear in AI Overviews while competitors remain invisible. This is not incremental advantage. This is first-mover monopoly in local search visibility. Every hyperlocal business category in every town is currently wide open: whoever moves first and builds the knowledge assets wins the territory. For estate agencies, dental practices, veterinary surgeons, and every other geographically bound service business, the question is whether you recognise this as the fundamental strategic opportunity it represents, or whether you let a competitor claim it while you continue publishing the same generic content as everyone else.

Google’s announcement in May 2026 represents the most significant shift in search behaviour since the introduction of mobile-first indexing. The mandate is unambiguous: AI Overviews and AI Mode will prioritise answer engines over traditional link farms, and websites that cannot demonstrate genuine expertise through original, substantive content will lose visibility entirely.

For estate agencies, this creates an immediate strategic problem. Most agency websites currently operate as variations on the same template: property listings fed from the same CML data, area guides plagiarised from Wikipedia, service pages that promise “expert local knowledge” without providing any, and blog content recycled from national property portals. None of this will survive contact with generative engine optimisation.

The technical term for what Google now penalises is commodity content: information that exists in functionally identical form across multiple domains. If your area guide for Cheltenham could be republished word-for-word as an area guide for Harrogate by changing only the place names, it has no value to a language model trying to synthesise authoritative answers. Google’s AI will cite the original source or the most comprehensive treatment, not the fifteenth derivative version.

What answer optimisation actually means

Answer engines work by parsing structured content to construct responses to natural language queries. When someone asks “what should I know before buying a Victorian terrace in Clifton”, the AI doesn’t return ten blue links. It synthesises an answer from multiple sources, citing only those that contribute novel, specific, verifiable information.

Traditional SEO optimised for ranking factors: keyword density, backlink profiles, domain authority. GEO optimises for citability: is your content substantive enough to be quoted as a source? Does it contain specific claims that can be verified? Does it offer information that cannot be derived from other published sources?

For estate agencies, this requires a fundamental shift from marketing copy to knowledge publishing. The question is no longer “how do I rank for ‘estate agents Bristol'” but “what do I know about property in Bristol that nobody else has documented?”

The proprietary knowledge problem

Most agencies possess substantial proprietary knowledge. The negotiator who has handled three generations of the same family understands inheritance patterns and family property decisions. The valuer who has appraised every house type in the town knows which streets command premiums and why. The lettings manager who has placed five hundred tenants understands seasonal demand patterns and rental price elasticity.

Almost none of this knowledge is published. It sits in email threads, verbal exchanges, and institutional memory. Meanwhile, the agency website publishes generic content about “our commitment to service excellence” and “comprehensive local knowledge” without ever demonstrating what that knowledge comprises.

The challenge for now and ongoing is making proprietary knowledge externally visible in structured, citable form. This means original research, original photography, original data analysis, and original testimony from sources who cannot be replicated.

Examples of non-commodity content that works

Commission your maintenance contractors to document common issues by property age and type. Get the plumber to explain what causes damp in 1930s semis versus Victorian terraces, which boiler brands fail most frequently, what actually needs replacing versus what can be repaired. This is knowledge derived from hundreds of callouts across your patch. Nobody else has it in this form.

Analyse your own transaction data to identify patterns invisible in national statistics. Document average void periods by property type, most common reasons for offer rejection, the actual gap between asking price and achieved price across different streets. Publish the findings with specific numbers, specific locations, specific time periods. This is proprietary data that cannot be sourced elsewhere.

Create measurement guides showing what physically fits in local property types. Which Victorian terraces can accommodate a standard three-seater sofa up the stairs, typical room dimensions in Edwardian semis for furniture planning, whether king-size beds fit in second bedrooms of common house types. This requires access to hundreds of properties and tedious documentation work. It is also exactly the kind of specific, practical information that answer engines will cite.

Interview long-standing residents about lived experience in the area. The family who have been in the same street for forty years can explain how the high street has changed, which local amenities have closed or opened, what the community rhythm actually feels like. These testimonials should be specific: names, dates, verifiable details. Not “I love living here” but “we moved here in 1987 when the factory was still operating, the high street had three butchers then, now it’s all coffee shops but the bakery on Crown Street is still the same family”.

Document the informal knowledge that demonstrates embeddedness. Which builder works regularly in the conservation area and understands the planning constraints, where you can actually get a plumber at short notice, the tree surgeon who knows the local authority’s approval process. This is concierge-level information that proves you are part of the community fabric rather than simply claiming it.

The controversy trap

The instinct when pursuing distinctive content is to reach for controversy: planning disputes, flooding risks, infrastructure problems, local political divisions. This demonstrates knowledge but introduces doubt at precisely the moment you need to build confidence.

An estate agency exists to facilitate transactions. Content that raises problems without resolving them creates friction in the buying decision. The goal is to prove local expertise while reducing perceived risk, not increasing it.

Better to focus on practical knowledge that helps buyers and sellers make informed decisions: seasonal patterns in your specific market, which streets have the strongest demand from families versus young professionals, what improvements actually increase sale prices based on your transaction data, which solicitors and mortgage brokers your clients report back as being efficient.

The content should answer questions people are genuinely asking but struggling to get answers to. Not “why choose us” but “what do we know that helps you”. The former is marketing. The latter is knowledge publishing.

Why this matters now

Google’s May 2026 mandate is not optional. Nor is your future inclusion in the results of AI Apps like Chat GPT, Claude, Gemini and Perplexity. Agencies and any business that continue to rely on commodity content will lose visibility as AI Overviews and AI Mode become the dominant search interface. The traffic that currently arrives via traditional organic search will increasingly be answered directly by the AI without a click-through. The so-called Zero Click phenomenon, or ‘Position Zero’.

The only websites that will retain visibility are those cited as sources in AI-generated answers. Citation requires original, substantive, structured content that contributes information unavailable elsewhere.

For agencies, this means treating content creation as knowledge asset development rather than marketing overhead. The investment required is significant: staff time to document expertise, original photography, data analysis, commissioned testimony. But the alternative is gradual invisibility as search behaviour shifts away from link-based results.

The agencies that will dominate local markets post-May 2026 are those that have built citable knowledge assets demonstrating genuine expertise. Not those with the best marketing copy, but those with the most substantive published evidence of what they actually know.

This is not a speculative trend. It is a structural shift already underway. The question is whether your agency treats it as an optional nice-to-have or as the fundamental precondition for future visibility.

For more information on how your business can capitalise on this paradigm shift please contact me.

From Your Correspondent: Google Might Be About To Widen The Pool

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For over a decade, SEO has operated within a fixed constraint: Google’s deep learning ranking systems only evaluate the top 20–30 candidate pages because running neural networks on more results is too expensive. That number wasn’t chosen for quality reasons. It was set by hardware budgets and memory costs. Court testimony from Google’s VP of Search confirmed it, and now Google Research has published the algorithm that could remove the constraint. TurboQuant compresses vector representations by 4x whilst maintaining retrieval quality, making it economically viable to evaluate far larger candidate sets. When the ranking window widens, the rules change. Sites with strong content and structured data get a fair hearing against established players with dominant backlink profiles. The moat around incumbent rankings is about to shrink.

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Google has historically ranked pages using a two-stage process that evaluates tens of thousands of candidates before applying deep learning (RankBrain, BERT) to just 20–30 finalists. This narrow window exists because running neural ranking on more pages is too expensive in compute and memory. That constraint was confirmed under oath by Google’s VP of Search, Pandu Nayak, during the DOJ antitrust trial.

Now the hardware economics are shifting. Google has published TurboQuant, a vector compression technique that reduces memory requirements by 4x whilst keeping retrieval quality high. CEO Sundar Pichai has acknowledged severe supply constraints on memory and foundry capacity, but TurboQuant addresses exactly that bottleneck by making retrieval indexing “virtually free” and reducing memory load per vector dramatically.

If deployed, TurboQuant lets Google evaluate a much larger candidate set before final ranking without adding hardware cost. The 20–30 page window was never a design decision. It was a budget ceiling. When the ceiling lifts, the entire competitive surface changes.

Why widening the search pool is good news

A wider candidate set levels the playing field. Under the current constraint, strong content on smaller or newer sites often never reaches the deep learning ranking layer because it gets culled in early retrieval stages dominated by classical signals like domain authority and link equity. The top 20–30 slots tend to go to established players with robust backlink profiles, not necessarily the pages with the best answers.

When Google can afford to evaluate 100 or 200 candidates instead of 20, retrieval-ready content gets a fair hearing. Pages with clear, citable claims, strong entity associations and semantic coherence can enter the ranking window even without legacy domain authority. Sites that have invested in content quality and structured information rather than link-building arms races get a shot they didn’t have before. The moat around incumbent positions shrinks.

For SMEs, local businesses and specialist publishers without big backlink budgets, this matters. If your page is genuinely retrieval-friendly (meaning AI systems can extract, verify and cite it), you’re now competing on content merit in a larger pool rather than being filtered out before ranking even starts. The game shifts from “can I outrank these 20 entrenched sites” to “can I be one of the 100 or 200 pages Google considers worth evaluating”. That’s a much more achievable threshold for quality content.

In practical terms for your consultancy clients: automotive retailers and estate agents with well-structured, citation-ready content (clean JSON-LD, strong NAP consistency, clear expertise signals) will have a better chance of appearing in AI-mediated results and wider ranking windows than they do now, where they’re often squeezed out by aggregator sites with stronger link profiles.

The shift favours signal over legacy authority.

DIGITAL MARKETING: The Evolution Of Search

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Search has evolved beyond rankings and keywords. In the age of AI-driven discovery, brands and businesses no longer compete solely for clicks, they compete for inclusion, understanding and endorsement.

Modern SEO, AEO and GEO now centre on four critical stages of visibility and influence.


1. Discovery – are you visible in the first place?

Before a search engine or AI assistant can recommend your business, it must know you exist.

Technical SEO, structured data, entity optimisation and semantic relevance all matter here. Search engines and generative AI systems require clear, accessible, machine-readable information to surface brands within responses and recommendations.

If your content cannot be crawled, indexed or understood, your expertise never enters the conversation.

“Visibility is no longer about ranking on page one. It is about being present wherever AI systems gather knowledge.”

2. Credibility – are you the option they trust?

AI platforms do not simply retrieve information; they evaluate it.

When multiple businesses cover the same topic, systems increasingly favour brands that demonstrate authority, consistency and expertise. Strong reviews, authoritative backlinks, accurate citations, topical depth and a recognisable digital footprint all contribute to trust signals.

This is where GEO and AEO become essential. The objective is not merely to appear, but to become the source algorithms feel confident using.

“The brands that win attention tomorrow will be those machines perceive as dependable today.”

 

3. Understanding – is your brand narrative clear?

AI systems now interpret and summarise businesses on behalf of users. Often, your company is being described before a visitor reaches your site.

That makes clarity vital.

If your messaging is inconsistent or poorly structured, AI-generated summaries may misrepresent your services, audience or expertise. A confused narrative weakens positioning and reduces relevance in recommendation systems.

“Effective optimisation now means shaping how machines understand your business – not just how humans read it.”

 

4. Influence – are you driving decisions?

The final stage is where visibility becomes commercial value.

The real winners in modern search are not the brands that simply appear in results, but the ones actively recommended when users ask for the best solution, provider or product.

AI search is rapidly becoming a recommendation engine. Businesses must optimise not only for traffic, but for preference and authority.

The future of digital marketing belongs to brands that are consistently surfaced, trusted, understood and recommended across every layer of search and AI discovery.

“Because modern optimisation is no longer just about being found – It is about becoming the answer.”

To learn more about my AI and SEO optimisation product OPTIMUM please contact me.

AI Risk Review Who Gets Seen

AI: Visibility Intelligence & Risk Report Offer

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SEARCH HAS CHANGED. MOST BUSINESS WEBSITES HAVE NOT.

AI systems are now deciding which businesses get seen, recommended and trusted. Yet across industry including; estate agency, publishing and motor retail, OPTIMUM has uncovered the same problems:

Poor SEO. Non-existent AI optimisation. Weak entity signals. Template websites built for a search landscape that no longer exists.

Businesses are losing clicks, leads and authority without even realising it.

OPTIMUM identifies the hidden gaps damaging visibility in Google AI Overviews, ChatGPT, Gemini and AI-driven search.

We help businesses:
• Reduce dependence on portals and third-party platforms
• Strengthen AI discoverability and local authority
• Close keyword and entity gaps competitors are missing
• Capture high-intent traffic before disruptors do

This is not traditional SEO.

This is digital resilience for the AI discovery era.

The ‘OPTIMUM – AI Visibility and Risk Report’ is £500 RRP but currently just £250 which is incredible value for the detailed information surfaced which often uncovers hundreds of thousands of pounds of gross profit missed.

Please contact me for more information.

OPTIMUM
AI Visibility Intelligence for Businesses That Intend to Lead.

CONSULTANCY: AI Risk Report. How Ready Is Your Business?

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AI Risk Review Who Gets Seen

The Businesses Winning in AI Search Aren’t Always the Ones Ranking First

There’s a quiet shift happening in search.

Not an update. Not a tweak. A change in how decisions are made.

Users are no longer scanning pages of results. They’re asking questions and getting answers. Directly. Instantly. Often without clicking at all.

And those answers come from AI.

Which raises a simple question.

If AI is choosing who to recommend… is it choosing you?

The Problem Most Businesses Haven’t Spotted Yet

You can still rank well.

You can still invest in SEO.

You can still appear on page one.

And still lose the click.

Because AI summaries are now taking a growing share of search traffic. They sit above traditional results. They filter choices. They present a shortlist.

If you’re not included in that shortlist, you’re not part of the decision.

That’s the gap.

This Is Not SEO. It’s Something Else

For the past eighteen months I’ve been focused on Generative Engine Optimisation.

Not as an extension of SEO. As a separate discipline.

The premise is straightforward.

Search engines rank.
AI systems select.

Selection is based on different signals. Structure. Clarity. Authority. Consistency. Trust.

Get those wrong and you disappear from AI results, even if your rankings look fine.

What’s notable now is not just that this shift is happening.

It’s the speed.

If anything, the pace has accelerated faster than expected.

Why This Matters Now

AI traffic behaves differently.

It’s not casual browsing. It’s decision-led.

  • Higher intent
  • Better engagement
  • Stronger conversion

Fewer clicks, perhaps. But better ones.

Which means the businesses being cited by AI are not just getting traffic. They’re getting the right traffic.

And at the moment, in most sectors, the field is still open.

Introducing the AI Risk Report and SEO + GEO Audit

This is not another generic audit.

It’s a clear, structured view of how your business performs in both traditional search and AI-driven visibility.

What you get:

  • Executive summary
    A straight answer on where you stand
  • Scored audit
    Key areas rated out of ten so you can see strengths and weaknesses quickly
  • Competitor gap analysis
    Who is being selected instead of you, and why
  • Priority action plan
    What to fix first, in order of impact

All for a fixed fee of £250.

No padding. No filler. Just clarity.

What Happens Next

If you want to act on it, I work with you and your team to implement the changes.

Not theory. Not slides. Actual updates to your site, content and signals that improve your likelihood of being included and cited.

Done properly, this compounds.

The Window Is Still Open

This is the part most people underestimate.

We are early.

Which means in many markets there is no clear leader yet in AI search.

No entrenched winners. No closed lists.

Just a short window where the businesses that move first can define their position.

That window will not stay open.

A Simple Question

If someone asks AI for the best provider in your space tomorrow…

Does your business appear?

If you’re not sure, that’s the place to start.

Short Q and A

What is an AI Risk Report?
A review of whether your business is visible, cited or ignored in AI-generated search results, and what is affecting that position.

How is this different from SEO?
SEO focuses on rankings. GEO focuses on being selected and cited by AI systems before a user clicks.

Can I pay to be included in AI summaries?
No. Inclusion is based on relevance, authority and how clearly your content can be interpreted.

Why am I losing traffic if my rankings are stable?
Because AI is answering queries directly and reducing the need for users to click through.

How quickly can results improve?
Some changes can have an immediate effect. Others, particularly authority signals, build over time.

Find Out Where You Stand

If you want a clear view of your position and what to do about it:

Call: 07407 038877
Email: steve@stevecoulter.co.uk

Or message directly.

Optimum AI by Steve Coulter
Get found. Get cited. Get chosen by AI.

AI Search Summaries? [ANYTOWN] Is Wide Open

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Most UK businesses are still years behind in local SEO, let alone Generative Engine Optimisation (GEO) essential for AI Summary citation which leaves a clear opening for those willing to act now. If you want to become the go-to authority in your town before the competition catches up, this will show you where the real advantage lies and how to take it.

Local SEO and GEO AI in the UK Is Still Wide Open – If You Know What You’re Doing

Spend any time looking at local search results across UK towns and cities and a pattern quickly emerges. Most businesses are visible, but very few are actually competitive in a meaningful way. There is a clear gap between what companies think counts as “local SEO” and what genuinely drives visibility in modern search, especially as AI-led results and answer engines become more prominent.

For many firms, local SEO still means a basic website, a handful of service pages, and a Google Business Profile with a few reviews. That approach might have worked five years ago, but it falls short today. Search systems are now far better at identifying authority, relevance, and real-world signals. They are not just ranking pages. They are deciding which businesses are trustworthy enough to surface, summarise, and cite.

This is where the gap begins.

The Reality Behind “Local Visibility”

What most businesses have is a presence. What very few have is a structured, location-aware digital footprint that reinforces itself across multiple signals.

An effective local strategy today looks more like building a network than a single website. It includes properly developed location or postcode pages, internal linking that reflects real service areas, consistent and growing review signals, and content that demonstrates actual involvement in the local community. It also means being recognisable as an entity, not just a business name on a page.

Much of the current conversation around GEO and AI-driven search is ahead of what the average UK business is doing. While marketers discuss citations, entity relationships, and answer engine optimisation, many local firms are still relying on templates and generic copy. That mismatch creates opportunity.

Why One Business Can Pull Ahead

In smaller and mid-sized UK markets, competition is often thinner than expected. Not because there are fewer businesses, but because so few execute well digitally.

When one company invests properly in its local presence, it can quickly separate itself. A site that covers key boroughs or service areas in depth, backed by strong reviews, relevant content, and clear internal structure, can outperform competitors that have been established for years.

This creates a first serious mover advantage. The business that positions itself as the most useful and locally relevant source tends to become the one search systems rely on. Once that trust is established, it compounds.

Where the Opportunity Is Strongest

The biggest gains tend to sit in service-led sectors where intent is both local and urgent. Trades, legal services, healthcare, home improvement, events, and specialist professional services all fall into this category.

These are areas where people want quick answers and reassurance. They are not browsing casually. They are choosing who to trust.

Smaller towns are particularly interesting. Many have limited digital competition, weaker local media ecosystems, and fewer high-quality backlinks or mentions. That leaves a wide opening for any business willing to invest in doing things properly.

The Limits of “Dominance”

It is important not to oversimplify. This is not just about publishing more content or building more pages.

Google Business Profile strength still matters. So does proximity, brand recognition, links, and real-world reputation. A technically strong site without supporting signals will struggle to fully dominate.

There is also a timing element. What looks like easy ground today is unlikely to stay that way. As more agencies and businesses catch up, the gap will narrow. Over the next one to two years, we can expect a more competitive and structured local landscape.

What Actually Wins

The businesses that succeed will not just be “optimised”. They will be the ones that are clearly the best answer for their area.

That usually comes down to a combination of:

  • Strong, logical location architecture across the site

  • Content that is genuinely useful and locally grounded

  • Consistent, high-quality reviews and supporting media signals

  • Real-world authority that search systems can confidently reference

In simple terms, it is about becoming the most credible local source in your niche.

Right now, much of the UK market is still underdeveloped in this respect. For businesses that recognise the shift and act early, the upside is significant. The window is open, but it will not stay that way forever.

DIGITAL MARKETING: Legacy Business and Mistaken Identity.

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This week by utilising my analysis tool, OPTIMUM v2.2, in my role as a business consultant I can share three real-world cases where the digital tool revealed what conventional Search Engine Optimisation (SEO) audits simply miss – from a digital disruptor poised to overtake an established rival, to a business losing ground in AI Summaries because of another company’s bad reviews. If you think your Google SERPS and review ratings tell the full story, read on.

Was it Sir Richard Branson who said, “Train good managers well and pay them enough so they won’t want to leave“? Sound advice, as it turns out.

When senior managers and directors walk out of a legacy business that has only dipped its toes into the digital world, then immediately set up a rival operation that is leaner, more digitally confident, and energised by the founders’ drive, they do not simply become competitors. They become disruptors, and potentially an existential threat.

This week I ran OPTIMUM v2.2 across two businesses in entirely different sectors. In both cases, the data points in the same direction: the newcomer is on course to overwhelm the incumbent within six to twelve months in all areas of the business.

One of the new entrants scores particularly well across digital marketing, SEO and Generative Engine Optimisation (GEO) which in layman’s terms means AI Summary inclusion. The only reason it sits behind the legacy player in any notional local league table is that its five-star reviews are too recent to have yet shifted the algorithm’s overall rating. That will change in a few months to compound their initial success.

Another case threw up something altogether more abstract. A well-regarded Midlands business, with years of strong Google reviews and solid standing across industry portals, returned an unexpectedly low trust score. The reason? Another firm operating in the same region has a remarkably similar name and a TrustPilot rating of just 1.2 out of 5. The AI systems are conflating the two, and my client is being dragged down by a reputational deficit that has nothing to do with him.

The fix is straightforward in principle: create a TrustPilot profile using the exact business name, address and contact details, build up a body of genuine five-star reviews, and re-run the assessment in a few months. It is a concrete, actionable win that would not have surfaced without running the OPTIMUM Ecosystem tool.

On a broader point: when I run typical local searches, the first few pages of results are dominated by larger players with serious SEO investment or the budget to buy their way to the top. That is not a battle most SMEs can realistically win on Google.

AI Summaries are a different matter. At present, the only route to inclusion in those summaries is through genuine GEO optimisation of your website. There is no shortcut and no media buy. My view is that, right now, every town and city represents an open opportunity for a switched-on business to own the AI Summary space for its sector or niche. Not only can that battle be won, but the businesses that establish authority early will carry that advantage forward. The AI systems will keep referencing those early signals as they generate future responses, and that compounding effect is only going to grow.

That combination of proprietary diagnostic data and hard-won experience is precisely what makes the difference between an interesting report and a result. The tool sees what the algorithms see; the consultancy knows what to do next. If you would like to find out what OPTIMUM v2.2 reveals about your business, your competitors, or your AI Summary visibility, I would be happy to talk.

ESTATE AGENCY: Wake Up, You Have Website Paralysis

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There is a clear and consistent issue across local estate agent websites. They are not built to generate business. They are built to exist.

Most agents rely heavily on portals like Rightmove and Zoopla for leads, treating their own website as a secondary asset. That creates a risk. If portal costs rise or performance drops, many firms have no reliable, owned source of enquiries. The automotive sector has already felt this pressure with Autotrader. Estate agency is heading in the same direction.

At the same time, most websites are under-optimised.

Common problems include thin location pages, duplicated property content, weak internal linking and outdated metadata. More importantly, there is little alignment with how people actually search. Buyers and sellers are asking detailed, intent-driven questions, yet very few agent websites provide meaningful answers.

This is where the real gap sits.

Content is often shallow and self-focused rather than useful. There is little coverage of the full customer journey, from early research through to decision. As a result, agents miss out on valuable organic traffic and fail to build authority in their local market.

Generative search adds another layer. Most sites are not structured in a way that AI systems can easily understand or trust. Without depth, clarity and consistency, they are unlikely to appear in AI-driven results.

Keyword gap analysis typically reveals hundreds of missed opportunities across local, long-tail and high-intent searches. Opportunity gap analysis then shows which of these are actually worth pursuing based on competition and conversion potential.

The bigger issue is strategic. Most estate agent websites are not designed as end to end marketing systems. They attract limited traffic, offer little engagement and convert poorly.

A more effective approach combines technical SEO, structured content, GEO readiness and clear conversion pathways. This turns a website from a passive brochure into an active source of instructions.

The opportunity is significant. Agents who invest in their own digital presence can reduce reliance on portals, improve margins and build a more stable pipeline of leads.

Right now, most are not doing this.

That is where the advantage lies.

To establish where you are today and understand where you could be tomorrow contact me and we can run an OPTIMUM V2 Ecosystem report.

AUTOMOTIVE: How AI Is Changing the Rules of Search

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If your dealership website is seeing fewer visitors than it was a year ago, you’re not imagining it. Some of that declining traffic is a direct result of how artificial intelligence (AI) is reshaping the way people search online and the rules are changing faster than most dealers realise.

Over the last 18 months as a research project I’ve been studying the effect of AI technology on Internet search. New agency disciplines like Generative Engine Optimisation (GEO) Conversational Search (CAI) and Answer Optimisation (AO) all drive AI Search Summary results including the citation links.

The fact is – Customers are increasingly getting the answers they need in the AI Summary at the top of the search results (SERPS) without ever clicking through to your website. That’s not a temporary blip, it’s a structural shift in how search works. There’s every chance you are burning your Pay Per Click (PPC) budget.

Here’s another steer – don’t chase every new AI tool that lands in your inbox, an endless wave of shiny new products promising to revolutionise your digital presence. Instead go back to basics.

Review what you already have, identify the gaps, and fix your foundations first.

UK dealers are being targeted by an ever-growing number of AI marketing vendors, many of whom are selling solutions to problems dealers haven’t fully understood yet – I wrote an article called The Comprehension Gap. Understanding the landscape clearly is the essential first step. Some solutions don’t even need AI to resolve them.

The Language You Need to Know

To make sense of what’s happening, it helps to get comfortable with a handful of key terms that are increasingly shaping how dealers think about their digital presence.

SEO (Search Engine Optimisation) is the practice most dealers are already familiar with – building website content that ranks well in Google keyword searches and earns free, organic traffic. It remains important, but it’s no longer the whole picture. In fact Semrush, a leading analytics provider, recently  quoted a 1/3 drop off in search appearances for popular search terms because of ‘position zero’ AI summaries. Those enquiries are going to the forward thinking supplier who, ahead of the game in the world of GEO, is already being cited in AI search and AI App results – and will benefit from early adopter status forever.

Position Zero refers to the featured AI generated snippet that appears at the very top of Google results, providing a direct answer to a search query without the user needing to click any link. Appearing here means visibility without traffic, which is precisely the problem.

LLMs (Large Language Models) – as explained by Prof. Hannah Fry on the BBC this week – are the AI tools driven by state of the art electronic chips that are increasingly influencing how people search and make decisions. These include Google Gemini, ChatGPT, Claude, and Perplexity, platforms that millions of UK consumers now turn to for recommendations, comparisons, and buying guidance.

Schema Markup (sometimes called Website Schema) is structured data added to a website’s backend that consistently labels content, vehicles, reviews, services – so that search engines can properly understand it. It helps generate richer search results and improves click-through rates. Many dealer websites in the UK lack this entirely.

GEO (Generative Engine Optimisation) is perhaps the most important new concept for dealers to grasp. Where SEO is about ranking in traditional search, GEO is about structuring and creating content so it can be easily understood, cited, and summarised by AI tools. Think of it as SEO for the AI era. Unlike traditional SEO, which tends to return the same results for the same keyword, GEO is highly personalised, the same query from two different buyers can produce completely different AI-generated answers, pulling from reviews, forums, and third-party sources alongside your own website.

Prompt Visibility refers to how frequently and prominently your dealership, brand, or specific information appears in AI-generated responses. If an AI tool is recommending dealerships near a customer, does your name come up – and in what context?

Agentic AI is the next frontier. Unlike AI tools that simply provide information, Agentic AI can independently plan, make decisions, and execute multi-step tasks. In a retail automotive context, this means AI that could guide a buyer through the entire purchase journey, from initial research to booking a test drive, with minimal human involvement. This is not science fiction; early versions of this capability already exist. LLMs were initially created to drive Chatbot conversations.

Hallucinations are incorrect results appearing in AI search summaries that could affect a contact or even a loss of reputation. AI is in the ‘Model T Ford’ era, it is not always correct and you need to be testing search terms for accuracy as part of your reputation management.

What This Means for U.K. Dealers

The practical implications are significant. Every positive customer review matters more than ever, because AI tools draw on that content when forming recommendations. An authentic dealer with consistently strong, genuine reviews is far more likely to appear in AI-generated responses than one whose online reputation is thin or inconsistent.

Critically, responses to reviews also need to feel human and genuine – AI can detect overly automated or templated replies, and this affects how credibly your dealership is represented. You cannot rely on AI in most cases ChatGPT writing your content – it’s great for writer’s block, but rewrite ideas in your personal tone.

Your website content needs to answer real questions clearly and directly. Generic manufacturer copy doesn’t help AI understand what makes your dealership distinct. Pages that explain finance options, compare models, or provide genuinely useful local information are the kind of content that both search engines and AI tools favour.

From a technical perspective, your website needs to be accessible to AI crawlers in the first place. A significant number of dealer sites inadvertently block tools like ChatGPT and Google’s AI systems through robots.txt settings or security configurations – meaning those tools simply cannot recommend them, regardless of how good their stock or pricing is. Does your supplier understand llms.txt and is this included in your website back end? These are now questions you need answers to.

The fundamentals; fast loading websites, clean data, honest content, and a credible presence across all digital platforms haven’t changed. What’s changed is how much they matter, and what gets built on top of them.

Steve Coulter is a four decades Sales and Marketing expert with a career in the Automotive Industry and involved in state of the art Digital Marketing since 1999.

AUTOMOTIVE: Porsche Profits Apply The Big Stoppers

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Porsche, once the golden child of German engineering and luxury performance, has hit an unexpected crisis in 2025. After years of record profits and unmatched prestige, the carmaker has reported a devastating fall in earnings, with operating profit plunging by more than 99 percent. The decline raises urgent questions about Porsche’s electric strategy, global sales slump, and future in an increasingly uncertain automotive market.

There was a time when the air in Zuffenhausen smelled of success and the confidence of endless growth. Porsche was the brand that never stumbled, the company that made perfection seem routine. Yet this year the balance sheets told a very different story.

For the first time in living memory, Porsche has posted a loss. Not a minor dip or a brief misfire, but a full-blown financial skid. In the third quarter of 2025, the company recorded an operational loss of nearly one billion euros. Across the first nine months of the year, profits collapsed from around four billion to just forty million. The figures landed like a crash through the guardrail at La Source.

The roots of Porsche’s decline lie in its costly electric gamble. Determined to lead the luxury EV revolution, the company poured billions into its own battery programme and an ambitious range of electric cars. The goal was clear: by 2030, eighty percent of new Porsches would run silently rather than roar. The market, however, had other ideas.

Buyers loved the Taycan’s design and speed, but hesitated at the price and limited range. High costs and lukewarm demand forced Porsche to retreat. The battery division was scrapped, new electric SUVs cancelled, and the firm took a three billion euro write-down. The pivot back to hybrids and combustion engines restored a little sanity, but the damage was done. Investors saw indecision. Customers saw confusion.

External pressures made things worse. In America, new tariffs on European luxury cars have already cost Porsche hundreds of millions of euros. Prices have risen, and demand has fallen. Across the Pacific, China’s once-booming market for Western prestige cars has cooled sharply. Sales dropped by more than twenty-five percent as domestic electric brands took centre stage.

Europe offered no comfort either. Economic fatigue and tighter emissions laws have hit the high-end market. Even the 911, the timeless heartbeat of Porsche, faces an uncertain future in a world determined to phase out petrol. Volkswagen Group, Porsche’s parent company, has reported its own steep drop in profit, much of it linked to this turmoil in Zuffenhausen.

The response has been fast and severe. Around four thousand jobs have already gone, and restructuring costs have topped three billion euros. Meetings that once celebrated lap times now focus on cost savings. Michael Leiters, Porsche’s new chief executive and a former McLaren man, has inherited the unenviable task of restoring confidence while steering a bruised and bewildered company back to growth.

Behind the scenes, engineers are refocusing. Porsche will rely on its most loyal strengths: craftsmanship, performance, and the feel of quality that no algorithm can reproduce. Future cars will blend petrol and electric power rather than replace one with the other. The idea is to rebuild gradually, balancing innovation with identity.

For decades, Porsche was defined by certainty. Every car, from the 911 Turbo to the Macan, carried the same message of precision and purpose. But the modern world is no longer so simple. Customers expect luxury, performance and sustainability in a single package. Governments demand cleaner cars. Markets demand profit. Somewhere in that storm, Porsche lost its footing.

Yet history suggests the brand knows how to recover. In the early Eighties, Porsche faced a similar reckoning. Sales were weak, costs were high, and purists feared the end of the 911. The company survived by listening to its engineers rather than its accountants. It rediscovered its essence. That may be the lesson Zuffenhausen needs again today.

If Porsche can blend its heritage with a clearer, more measured path to electrification, it could regain its balance. The 911 remains a global icon, and the Taycan, for all its struggles, proved that electric Porsches can still thrill. What the brand needs now is consistency and patience. The next great Porsche story will not be written in spreadsheets but in steering feel, design integrity and engineering bravery.

For now, though, Porsche’s halo has dimmed. The numbers are harsh, the markets unforgiving, and the pressure immense. Yet if any marque can turn a loss into a lesson, it is the one that made imperfection an art form.

What Porsche Could Do Next?

– Refocus the product line: Build hybrids and performance models that maintain the emotional core of the brand while easing customers toward electric power.
– Control production costs: Simplify supply chains, delay unnecessary launches, and invest only in platforms that deliver profit and flexibility.
– Strengthen brand storytelling: Reignite the emotional link between car and driver through heritage design cues and motorsport engagement.
– Win back key markets: Adjust pricing and marketing strategies in the United States and China to match shifting buyer sentiment.
– Prepare for the long term: Develop a steady, sustainable EV roadmap that doesn’t gamble the company’s identity on unproven demand.

If Porsche manages to balance its heart with its head, it will emerge stronger. The figures may be grim today, but the brand’s legacy of resilience remains intact. The brand is used to the smell of victory.