Getting Recommended by ChatGPT and AI Search
Some of your customers have stopped searching and started asking. They open an assistant, describe their problem in a sentence, and get back a short list of businesses — often with no results page in between.
That changes the shape of the problem. A search results page gives ten options and lets the person choose. An assistant gives two or three and effectively chooses for them. Being on page one is no longer the same thing as being in the answer.
What Assistants Are Actually Doing
Broadly, they're assembling an answer from sources they can read and reconcile: your website, your Google Business Profile, directories, and whatever else mentions you. Then they name whichever business the sources agree about most clearly.
That last part is the important one. These systems are pattern-matchers, and contradiction is what they handle worst. If your website says one thing about what you do and your profile says another, you are the harder business to summarise — and the harder business to summarise is the one that doesn't get named.
Answer the Question in the First Paragraph
Marketing copy that builds slowly toward a point works on a human reading with intent. It works badly on a machine extracting a fact.
If a page is about a service, the first paragraph should state plainly what the service is, who it's for, and where you provide it. Not a headline about excellence followed by three paragraphs of atmosphere. The extractable answer needs to be near the top, in plain language.
Structured Data Isn't Optional Anymore
Schema markup is how you tell a machine what your pages mean rather than making it guess. Business type, address, service area, hours, services offered, questions and answers.
It has always been good practice for search. It matters more now, because there's a second class of reader that depends on it almost entirely.
Consistency Is the Whole Ballgame
Same business name. Same address format. Same phone number. Same description of what you do. On the site, on the profile, in every directory you can reach.
This is boring work with no visible output, and it's the highest-leverage thing most local businesses could do this month.
Reviews Are Read as Evidence
Assistants lean on review text, not just star ratings, because review text is where the specifics live. A body of recent reviews that mention the actual services you provide and the actual places you provide them is corroboration in a form these systems are good at using.
Which is another reason to collect reviews continuously rather than in occasional bursts.
Don't Abandon What Already Works
None of this replaces local search. Maps and organic results are still where most local discovery happens, and the work that wins there — a fast, well-structured site, a maintained profile, real reviews, consistent details — is largely the same work that gets you named by an assistant.
That's the useful part. This isn't a new discipline bolted onto the old one. It's the same fundamentals, with less tolerance for sloppiness.
If you want to know how you currently come across to an assistant, ask one about your own category in your own town. What comes back, and whether you're in it, is a more useful diagnostic than any report.