Quick Answer: Structured data is code you add to your pages that labels what your business is and what it does, in a format machines read directly. Entities are the specific things that code names: your company, your services, your location, the industries you serve. AI search engines use both to decide which company handles very specific questions, and whether to name you in the answer. Skip them, and the AI has to guess from your paragraphs. It usually guesses wrong, or skips you.
A plant engineer or buyer used to type “industrial epoxy flooring Michigan” or “5-axis CNC machining aerospace” into Google and scroll a list. Now that same buyer asks ChatGPT or Google’s AI Overview a full question and reads a short answer that names two or three suppliers. If your company isn’t one of the names, the click never happens. The RFQ never lands. You don’t get a second chance on that query.
Getting named in that answer is what Answer Engine Optimization (AEO) is about. Structured data and entities are the two pieces most industrial websites are missing.
- 1 What is structured data, and what does it actually do?
- 2 What are entities, and why do they matter more than keywords?
- 3 Do AI search engines actually use structured data?
- 4 Why does the speed of data retrieval matter in AI chat?
- 5 What schema should an industrial company add first?
- 6 Does schema alone get you cited by ChatGPT?
What is structured data, and what does it actually do?
Google defines structured data as a standardized format for providing information about a page and classifying its content (Google Search Central). In plain terms: it’s a block of code, usually written in JSON-LD, that sits in your page and states the facts a machine would otherwise have to infer.
Think of it like the difference between a photo of a finished part or a coated floor and the spec sheet behind it. A person can look at the photo and guess. The spec sheet states the material, the tolerance, the finish, the standard it meets. No guessing. Structured data is the spec sheet for your web page.
The shared vocabulary for this code is Schema.org, a standard that Google, Microsoft, and other platforms all read. For years, industrial companies that bothered with schema did it for rich results, the star ratings and FAQ dropdowns that show up in Google. Those still matter. But the bigger reason now is simpler: a machine reading your labeled facts doesn’t have to interpret your prose, and it doesn’t make the mistakes that come with interpreting.
What are entities, and why do they matter more than keywords?
An entity is a specific, named thing: your company, a service you offer, a person on your team, a city you operate in, an industry you supply. It isn’t a string of words on a page. It’s a thing with attributes and connections to other things. Think of it as a package of information. If they define an entitity they don’t have to relearn it ever time.
There are dozens of companies in the country called some version of “Industrial Coatings” or “Precision Machining” or “Midwest Supply.” Keywords can’t tell them apart. Entities can. Google’s own documentation says that adding organization structured data helps Google understand your business and disambiguate it from others in search results (Google Search Central: Organization schema). Disambiguation is the whole game when your name is common in your field.
When you define your company as an entity, you connect facts: this company applies epoxy and urethane floor systems, works in food and pharmaceutical plants, meets USDA facility standards, sits in Clinton Township, Michigan, and is run by a named person with 20 years in the field. Or: this shop does 5-axis machining in titanium and Inconel, serves aerospace and defense, holds AS9100. Those aren’t keywords stuffed into a paragraph. They’re linked facts about one specific business. That’s what lets an AI answer a buyer’s question and put your name in the sentence with confidence.
Keywords told a search engine which words appeared on your page. Entities tell an AI what your business is. That’s the shift, and it’s the reason a site that ranked fine in 2019 can be invisible in an AI answer today.
Do AI search engines actually use structured data?
Some do, and they’ve said so on the record. In March 2025, Fabrice Canel, a Principal Product Manager at Microsoft Bing, confirmed on stage at a search conference that schema markup helps Microsoft’s large language models understand content, which feeds Bing and Copilot (reported by Search Engine Land). Google engineers have said their generative systems run better when structured data is present, using it to help ground answers in facts.
Now the honest part, because a marketing manager who believes the hype gets burned. ChatGPT and Perplexity haven’t made equivalent first-party statements, and at least one independent study found no clean correlation between how much schema a site has and how often AI engines cite it. Structured data is a support layer, not a button that ranks you. It removes ambiguity about what you are. It doesn’t manufacture authority you haven’t earned.
So the right way to think about it: schema and entities make sure that when an AI decides to answer a question in your category, it can identify you correctly and pull the right facts. Whether it picks you over a competitor still comes down to whether your content is genuinely the best, clearest answer. Both jobs matter. Neither one alone is enough.
Why does the speed of data retrieval matter in AI chat?
When someone asks an AI assistant a question, the system fetches pages and pulls what it needs in the moment, under a tight time limit. It doesn’t browse the way a person does. It grabs the raw HTML your server returns, reads what’s there, and moves on. It doesn’t wait around for a slow page, and it doesn’t run the scripts that build a lot of modern websites in the browser.
That last point catches a lot of industrial sites off guard. Vercel analyzed real traffic from the major AI crawlers and found the bots behind ChatGPT and Claude fetch your files but don’t execute JavaScript, which means they can’t read content that only appears after the page renders in a browser (Vercel, “The rise of the AI crawler”). If your capabilities list, your service pages, or your specs get loaded by a script after the page opens, a human visitor sees them and the AI sees a blank shell. You can rank fine on Google, which does render JavaScript, and still be invisible to ChatGPT on the same page.
This is where structured data earns its keep twice over. JSON-LD sits in the raw HTML your server sends first, so it’s there in the exact pass the AI makes. It’s already labeled, already a clean set of facts. The machine doesn’t have to load the whole page, wait for scripts, and infer what your business does from your marketing copy. It reads “this company does X, serves industry Y, operates in Z” right away and keeps going.
Speed compounds from there. A slow server, a bloated page, or content locked behind JavaScript all cost you the same way: the fetch returns an incomplete page or your site gets passed over for a faster, cleaner competitor. The AI has the whole web to pull from and no reason to wait on you. The company whose facts load instantly and read cleanly gets named in the answer. The one whose site makes the machine work for it gets left out, and the buyer never learns you existed. That’s a lost RFQ you’ll never see in any report, because the query never reached your site.
What schema should an industrial company add first?
Start with the entities that define your business and the questions your buyers actually ask:
- Organization schema on your home page, with your real address, phone, and links to your verified profiles. This is the anchor entity for your whole site.
- Service or Product schema for each capability, so concrete polishing, epoxy flooring, and moisture mitigation read as distinct services, or so 5-axis machining, Swiss turning, and sheet metal fabrication don’t blur into one vague list.
- Person schema for the owner and any named engineers or estimators, which ties real expertise to your company entity.
- FAQPage schema on pages that answer common procurement questions, since those clean question-and-answer blocks are easy for an AI to lift into an answer.
One rule that trips people up: the structured data has to match what’s actually visible on the page. Google ignores markup that describes things a human visitor can’t see, and mismatches between your code and your content create a trust problem. Don’t claim capabilities in schema that your page doesn’t back up. Building this correctly, mapped to how buyers and engineers actually search, is the core of what an agency that handles industrial SEO should be doing for you, and it’s rarely something a general web developer sets up right.
Does schema alone get you cited by ChatGPT?
No. And the best evidence for what does work comes from the study that named this whole field. Researchers from Princeton, Georgia Tech, the Allen Institute for AI, and IIT Delhi published “GEO: Generative Engine Optimization” and tested nine tactics across 10,000 queries (Aggarwal et al., arXiv:2311.09735, KDD 2024). The tactics that moved the needle weren’t keyword tricks.
“Citations, quotations from relevant sources, and statistics can significantly boost source visibility.” — Aggarwal et al., GEO: Generative Engine Optimization, KDD 2024
Adding specific statistics, credible quotes, and citations to reputable sources raised visibility in AI answers by up to 40% in their tests. Schema labels your content so the machine reads it cleanly. Specific, verifiable, well-sourced content is what earns the citation. You need both. A perfectly marked-up page full of vague marketing fluff gets read correctly and then ignored.
Run the arithmetic on why this is worth doing. If one RFQ or bid is worth $50,000 in revenue and your close rate on qualified quotes is 20%, then getting named in AI answers for even a handful of high-intent queries a month pays for the work many times over. One additional RFQ per month covers the entire cost of getting your entity data and content right.
When you’re ready to have it built correctly, Bootstrap Creative’s industrial SEO and AEO service handles your structured data, entities, and server-rendered content so AI search can identify and cite your company, working directly with Jake Lett and no account managers in between.
