AI Search for Local Businesses
When somebody asks an assistant to recommend a business near them, the answer is assembled from three things: the profile and review platforms that describe you, the consistency of your details across the web, and whether your own site says plainly what you do and where. Consistency matters far more than volume here. A business with forty identical listings and thirty reviews will be named ahead of one with two hundred listings that disagree with each other.
Rated 5.0 from 20 Google reviews · A local SEO agency based in Haywards Heath
The three inputs, in order of weight
- Your profile and the platforms that mirror it. Google Business Profile is the anchor because so much else is derived from it, but the assistants also read the directories, review sites and trade listings that carry your details. Categories, opening hours, service area and description all do work here.
- Consistency across everything else. Name, address and phone number identical wherever they appear, including the places you have forgotten about. This is the input most under your control and the one most often neglected.
- Your own website. Saying, in plain words near the top of the page, what you do and the places you do it in. A surprising number of local business sites never state their town in a sentence, only in a footer address.
Why consistency beats volume
An assistant asked to recommend somebody is being asked to vouch. Contradictory information is the fastest way to make it hedge, and a hedge reads as “you might also consider” rather than a name. Two phone numbers across your listings is not a small untidiness, it is a reason for a model to be less certain that the two records describe one business.
The practical exercise is dull and effective. List every place your business appears online. Put the details in a spreadsheet. Find the disagreements. Fix them, oldest first, because the stale records are the ones that contradict. Most local businesses find between five and fifteen inconsistencies and can clear them in a fortnight.
Reviews, and what they are doing here
Reviews function as corroboration rather than as a ranking factor. They are text written by other people, hosted somewhere you do not control, saying what you are like. That is exactly the kind of evidence a model leans on when it has been asked to recommend rather than to describe.
Which means the useful review is a specific one. “Great service” corroborates nothing. A review naming the job, the town and the outcome gives an assistant something to quote and a reason to associate you with that work in that place. When you ask for reviews, ask people to say what you did, which is also a better ask than asking for five stars.
For what it is worth as a first party data point: as at August 2026 our own business held second position in the local pack for “digital marketing agency sussex” on twenty reviews averaging five stars. Twenty is not many. Consistency and specificity were doing the work, not volume.
A local AI visibility checklist
- Google Business Profile complete: primary category correct, service area accurate, description written as a sentence rather than a keyword list.
- Name, address and phone number identical everywhere, including old directory entries.
- The town or towns you serve stated in ordinary prose on the relevant pages, not only in the footer.
- LocalBusiness structured data on the home page and location pages, with the same details as the profile.
- Reviews that name the work and the place, gathered steadily rather than in bursts.
- A page for each place you genuinely serve, and none for the places you do not, because thin location pages are a doorway abuse problem as well as a credibility one.
What not to bother with
Mass directory submission. Buying citations by the hundred was a tactic when volume was the signal, and it now actively works against you, because the cheap directories are where the inconsistencies get introduced. Forty accurate listings beat four hundred, and the four hundred will cost you a weekend of cleanup within two years.
Frequently asked questions
Related guides
This page is one of our AI search and GEO guides. Start with the complete guide to AI search visibility or see our AI search and GEO services.
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Sources
- Google Search Central. Local business structured data. Read 3 September 2026. The LocalBusiness properties worth completing, and Google’s guidance on matching them to your profile.
- Google Search Central. Spam policies for Google web search. Updated 15 May 2026. Doorway abuse, which is what a set of near identical location pages is judged against.
- Ofcom. Adults’ Media Use and Attitudes 2026. 2 April 2026. 54 per cent of UK adults using AI tools, up from 31 per cent a year earlier. This is the number that makes local AI recommendation worth attending to at all.
- Phoenix Marketing. Phoenix Marketing local pack position, first party. August 2026. Second in the local pack for “digital marketing agency sussex” on twenty reviews averaging five stars, as at August 2026.
Every figure on this page was read on the source page listed above. This page is reviewed monthly and the last checked date is updated when it is.
Frequently asked questions
Does our Google Business Profile affect what ChatGPT says?
Indirectly, and substantially. Assistants read the profile data mirrored across the wider web, and the profile is where most of that information originates. A neglected profile produces neglected information everywhere it has been copied to.
How many reviews do we need?
Fewer than you think, and better than you have. Twenty specific reviews naming the work and the town do more than two hundred saying “great service”. Steady accumulation also beats bursts, which look exactly like what they usually are.
What if our address has changed?
Treat it as a project, not a task. The old address will be sitting in directories you have forgotten, and each one left uncorrected is a contradiction. Work through them oldest first and expect it to take a few weeks rather than an afternoon.
Do online directories still matter?
The used ones do, as corroboration. The unused ones never did and now cause harm, because they are where wrong details persist. Aim for a short list of directories a real customer might plausibly look at, all correct.








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