The Structured Data Gap That's Keeping Plumbers and Electricians Out of AI Search

Someone types emergency electrician near me at eleven at night and asks ChatGPT to pick one. The assistant names three companies, each with a stated callout fee, a specific service area, and a credential number attached. A fourth company charges less and answers faster, but never gets mentioned, because nothing on its website tells a model what services it offers, where it covers, or what qualifies the person doing the work.

A Site That Looks Professional And One That Reads As Professional Are Not The Same Thing

Most trades websites are built for a person scrolling on a phone: a hero photo of a van, a services list written as flowing sentences, a contact form at the bottom. None of that tells a model what a callout actually costs, which postcodes get covered, or what certification the electrician behind the work actually holds. The facts might be sitting in plain text on the page, but a model reading prose has to guess at them, and a guess is not something ChatGPT will repeat with confidence.

1. What Structured Data Actually Does For A Trades Business

Structured data is a layer added to the page code that states facts explicitly rather than describing them in a sentence: this business is an electrician, this is the area it serves, this is the callout fee, this is the qualification the tradesperson holds. A model reading a page with that layer treats the label as fact. A page without it has to infer meaning from ordinary sentences, and inference is exactly where a plumber or electrician gets left out of the answer.

2. The Three Labels That Actually Move The Needle

Not every label is worth the effort. Three make the real difference for a plumber or electrician. The business type label states plainly whether the site belongs to a plumber, an electrician, or an HVAC company, rather than a generic local business. The service label ties each job type to its own area covered and starting price instead of leaving it buried in one paragraph of copy. The credential label names the qualification and registration number behind the work, the structured version of the certification number that already gets a trades business quoted once a person can see it.

• A business type label naming the site a plumber, an electrician, or an HVAC company, not a generic local business
• A service label for each job type, giving it its own area covered and starting price rather than one paragraph on a services page
• A credential label naming the registration body and number behind the work, such as Gas Safe or NICEIC
• An area served label listing the exact towns and postcodes covered, not the phrase local area

3. Where It Belongs So A Model Actually Finds It

A label placed only on the homepage misses every service page and every area page a model might land on instead. Add the business type label site wide, then add a service label on every page describing a specific job, and an area served label on every page naming a town or postcode. A model reads each page as its own source. It does not follow links across a site to piece together a fact that should have been stated once, in one place, on the page it actually landed on.

A label in the page code is not decoration for search engines. It is the only way to hand a model a fact about a callout fee or a qualification that it would otherwise have to guess at.

The Takeaway

AI search rewards plumbers and electricians who make their facts explicit rather than the ones who simply look reliable in a photo. Three labels, the business type, the service with its area and starting price, and the credential with its registration number, do more for how ChatGPT and Google's AI Overview describe a trades business than another polished services page ever will.