Local businesses
People looking for a craftsperson, a shop or a service near home can ask an AI assistant. Here you will find the questions owners ask about these answers, how TrustInsider measures them and what is worth fixing.
Recent reviews
Among the possible reasons is the simplest one: few reviews, or none recent. When it has to choose a few names for a local question, the assistant needs signals that the business is alive.
Local answers often cite reviews as the reason for the choice, and you can see this in the sources of each answer. Those who have satisfied customers but never ask for a review stay invisible exactly where the question arises. There are European rules on consumer reviews, introduced by the Omnibus directive and transposed by every country.
A sample answer to a search for a cobbler open on Saturdays: the shops named, the reference to reviews as a criterion and the business left out.
QuestionIs there a cobbler open on Saturdays nearby?
AI assistant · sample answer
Nearby you can try two workshops on the main street, both open on Saturday mornings and praised in the most recent reviews for their speed. The shop near the market does not appear, even though it has been repairing shoes for years in the same neighbourhood.
The businesses named become part of the asker’s choice.
Recent reviews are the reason the answer states.
The business without recent reviews is left out of the suggested list.
What to avoid: the business has loyal customers but no recent reviews, and the assistant leaves it out of nearby suggestions. What to do: after every service the customer is invited to leave a review, without picking only the happy ones, and every review gets a reply.
Name, address, phone
The assistant reconstructs a business by putting together directories, listings, website and reviews. If name, address and phone are written differently from one source to another, it may treat them as different businesses.
Small differences are enough: an abbreviation in the name, a missing street number, an old phone number left on a directory. The cure is to write the three details identically on the website, the map listing and local directories, and to carry every change everywhere on the same day.
Name, address and phone of a sample shop as reported by the website, the map listing, a local directory and the assistant’s answer, which mixes the versions.
| Source | Name | Address | Phone |
|---|---|---|---|
| Business website | The official spelling, in full | Street and street number in full | The current number |
| Map listing | The official spelling, in full | Street without the street number | The current number |
| Local directory | A name shortened with an abbreviation | Street and street number in full | The number from a few years ago |
| The assistant’s answer | The directory’s shortened name | The address without the street number | The number from a few years ago |
One clear sentence
Many local business websites tell a story but do not say, in one sentence, what the business does, where and when. That sentence is exactly what the assistant looks for to decide whether to suggest you.
For an owner the point is not to become an expert in artificial intelligence, but to make sure the few things that matter are written clearly: what you do, in which area, on which days, with which services. The Site audit tells you whether the descriptive sentence, the list of services and the structured data are there.
The same sample home page of a neighbourhood workshop: before, it tells a story; after, it states service, area and opening hours at the top, with the structured data below.
| The home page that tells a story | The home page that answers | |
|---|---|---|
| First sentence | Passion and tradition from our family workshop. | We repair shoes and bags in the town centre, Tuesday to Saturday. |
| Services | Mentioned here and there in the gallery photos. | In a short list, one per line, with turnaround times. |
| Area and opening hours | Only in the footer, in small print. | Right below the title, the same as on the listing. |
| Structured data | Missing: the page does not say what type of business it is. | Present, with business type, address and opening hours. |
Listings and directories
For local questions assistants can read map listings, local directories and reviews more than website pages. Knowing which carry weight in your area tells you where to work first.
Sources change from one trade to another: for a restaurant guides and booking platforms matter, for a craftsperson trade directories, for a shop listings and reviews. Cited sources shows, question by question, which pages support the answer.
Four sample steps of a neighbourhood question: the request, the reading of listings and directories, the choice of a few names and the cited source that decided.
The person describes the service they need and their neighbourhood.
The assistant gathers map listings, local directories and reviews.
It suggests the businesses with the clearest and most recent signals.
The page that decided the choice appears among the answer’s sources.
Your location
One view answers a simple question: where you win and where you lose against the businesses around you. For each topic it shows how many answers name you, who leads the topic and how far behind you are.
Every share carries its base: with few answers the reading stays indicative, and the glimpse shows this on a demo brand. From there you go into detail: Reviews follows the ratings of your location, AI visibility measures local questions for your trade and your area, AI claims compares the hours and services in the answers with your pages, Actions tells you what to do first.
Neighbourhood use cases
For some trades there is a use case dedicated to the owner: the typical problem, the questions people ask, what you see in the platform and which actions follow. No promised results, no customer stories.
The dental practice has its own: three listings with three different opening hours and an assistant that picks one, with the rules of health information on what can be written. For other neighbourhood trades, from the pharmacy to the garage, the questions on this page apply, with the different weight reviews and rules carry in each.
Dental practice, pharmacy, garage, hairdresser and plumber placed according to how much reviews matter and how much the trade’s rules do, without numbers.
How much the trade’s rules weigh
How much reviews weigh
Decisive reviews and precise rules on what can be communicated.
Regulated rotas and services, reviews read less than opening details.
Chosen on the trust described by those who have already been.
Reviews and photos of the work make almost the whole choice.
What matters is finding the area served, the right phone number and availability straight away.
Frequently asked questions
Whether you need a website, why discounts are never given in exchange for reviews, what changes compared with a chain and how often to check.
It helps, but on its own it is not enough and sometimes it is not the first thing. The map listing, local directories and reviews count a lot; the website serves to say clearly what you do, where and when.
Yes, if you ask everyone in the same way and consistently: a few recent opinions say more than many old ones. Never link a discount or a benefit to a review: the European rules on consumer reviews and, in Italy for restaurants and tourism, Law 34/2026 rule it out.
The features are the same, the view changes: for a single location everything is on one page, while a network sees the comparison between its locations.
At every panel cycle, and always after a change of opening hours, address or services: that is where a source falls behind.
Related paths
Each role uses the platform with a different goal. From here you compare the other solutions, the path from brand to verification and the methodology behind the numbers.
Marketing, PR, e-commerce, product, agencies, groups and regulated industries: choose your path and discover analyses and interventions for your work.
ReadHow TrustInsider works in six steps: brand, questions, quote, evidence, page-by-page intervention and a check on the same questions.
ReadHow every TrustInsider measure is built: sampling of AI answers, sources and rights, index calculation and declared limits.
ReadHelp with access, credits, collections, integrations and data: guides, FAQs, the site assistant and support requests from your workspace.
Read