Google

Stop Searching Yourself in ChatGPT

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AI consultants or ‘the loudest voice’, ‘aka the new industry expert’ in a specific business forum seem to be telling business owners the same thing right now.

“Open ChatGPT, type your business name, see what comes back.”

Half the time nothing does, and the point of the exercise is apparently to make you feel bad about that.

It’s a lame party trick dressed up as insight.

It tells you nothing about why you’re missing, and even less about what to do next. It just produces a bit of dread, which is handy if you’re about to sell someone a fix or look clever.

Here’s what’s actually going on underneath. Old-school SEO worked on a fairly crude logic: say the right words often enough, in the right places, and Google would eventually decide you deserved to rank. Keywords, backlinks, meta descriptions, all of it built around repetition being treated as proof. Type it enough times and the machine believes you.

AI search agents don’t work like that. They’re not hunting for the phrase that matches the query, they’re trying to work out whether the things being said about you actually check out. Does your own website agree with what your Google listing says, agree with what a review site says, agree with what a directory says? Are other people online independently backing up the claim, rather than you just repeating it about yourself in twenty different places?

That’s a completely different game. It has more in common with how a journalist stands up a story than with how a search engine used to rank a page. One source saying something is a tip. Three unconnected sources saying the same thing is closer to a fact.

Which is why, if you did get cited somewhere by an AI tool this week, I wouldn’t get too excited about it. It might have nothing to do with anything you’ve done. A particular query happened to fan out in a particular direction, and a page of yours happened to line up with something else on the web that day. That’s luck, not a strategy, and luck doesn’t show up again next month on its own.

That’s really the bit nobody wants to say, because it’s inconvenient for anyone selling a quick fix. Appearing once proves almost nothing. What actually matters is whether the same business turns up again for a different question, on a different platform, a month later. If it doesn’t, that first appearance was noise. A fluke pairing that happened to hold together for five minutes.

So what does actually move the needle, if it’s not the ChatGPT search and it’s not chasing a single mention?

Mostly it comes down to whether the story about your business is consistent everywhere it appears, and not just because you’ve written it the same way on every page you control. It’s whether other people, sites and listings you don’t control are saying the same thing about you unprompted. That agreement between independent sources is roughly what these systems are built to go looking for.

It also helps enormously if what you’re claiming is specific enough to check. Calling yourself a trusted local expert doesn’t give anyone anything to verify, and everybody says it anyway, so it carries no weight. Saying you’ve handled probate sales in a particular postcode for fifteen years is a claim someone, or something, could actually test against other evidence.

Who’s saying it about you matters more than it used to. A named, traceable review sits differently to an anonymous one, and the systems doing this checking are getting better at telling the two apart.

None of that is complicated, and none of it needs a screenshot of ChatGPT to prove or disprove. It’s closer to building a reputation that would survive a sceptical journalist asking around than it is to gaming an algorithm. The old approach rewarded saying things a lot. This one rewards things that are still true when somebody checks.

So by all means search yourself if it makes you feel something – remember to be Incognito mode. Just don’t mistake the result for an answer.

AI Search: What Are Google Preferred Sources?

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Google Preferred Sources: Audience Trust Is Now a Ranking Signal

Google Preferred Sources is not a minor interface update. It is a structural change to how visibility works inside AI search, and it deserves more attention than it has received.

The feature allows users to nominate websites they trust. Once selected, those sites carry a visible badge inside Google search results. It launched in Top Stories, expanded globally in April 2026, and on 27 May 2026 Google extended it into AI Overviews and AI Mode.

Preferred sources now surface with visible markers inside the AI-generated answers themselves, at the exact moment a user is deciding whether to read further or move on.

The numbers are notable. Users have selected more than 345,000 sources, up from around 90,000 at global launch. Google’s own data shows that people click through to preferred sources at twice the rate of other links. Inside an AI Overview, where the generated answer compresses the organic results into a much smaller footprint, that differential is not marginal. It is the difference between being seen and being ignored.

The feature rewards publishers who already command a loyal audience. It does relatively little for newer or smaller sites whose discoverability has been in decline for two years. This is the part of the announcement that sits quietly beneath the positive framing. Preferred Sources is not a rising tide. It reinforces existing authority and presents that reinforcement as user choice.

For SEO and GEO practitioners, the implication is clear. A publisher is no longer competing only with other search results. It is competing with the answer Google has already generated. In that environment, being a recognised and trusted source before the user reaches the search box is a material advantage. Technical SEO remains relevant. It is just no longer sufficient on its own.

Preferred Sources is one more signal pointing in the same direction. Audience trust, topical authority, and citation potential are the metrics that matter in AI search. They are harder to manufacture and harder to reverse-engineer than a keyword strategy, which is precisely why building them now, rather than later, is the work that counts.