# What each industry can mark up, and what it actually does

What each of the 13 industries in Schema.org can mark up, how much of it the web actually uses, and which rich results Google documents for it.

> Source: https://eduarddziak.com/structured-data/industries/
> Snapshot: July 2026
> Updated: 2026-08-19
> Data: /data/schema-stats.json and /data/schema-stats.csv
> Licence: Apache 2.0, credit requested

## Summary

| Measure | Value |
| --- | --- |
| Classes sitting in a real industry | 578 |
| Classes that are vocabulary machinery | 333 |
| Classes in no industry at all | 26 |
| Industries | 13 |
| Industries with no documented rich result | 4 |
| Terms inside those industries | 187 |
| Snapshot | July 2026 |

## Key findings

- 578 of Schema.org's 937 classes sit in a real industry.
- Medical and health holds 88 types, and exactly one reaches 100,000 websites.
- Four of the thirteen industries have no rich result Google documents at all.
- Those four industries hold 187 vocabulary terms between them.
- Automotive holds 15 types, and not one reaches 100,000 websites.

## Medical and health holds 88 types, and one reaches 100,000 websites

Only the thirteen industries are drawn and only they get a page of their own; the table carries two extra rows, 333 classes of vocabulary machinery and 26 outside any industry, named instead of folded into whichever industry happens to be nearest.

| Industry | Types | Reach 100,000 sites | Under 1,000 sites | Share under 1,000 | Rich results |
| --- | --- | --- | --- | --- | --- |
| [Media and publishing](/structured-data/industries/media-and-publishing/) | 164 | 32 | 61 | 37.20% | 15 |
| [Medical and health](/structured-data/industries/medical-and-health/) | 88 | 1 | 57 | 64.77% | 0 |
| [Places](/structured-data/industries/places/) | 60 | 6 | 37 | 61.67% | 0 |
| [Events and entertainment](/structured-data/industries/events-and-entertainment/) | 48 | 2 | 19 | 39.58% | 1 |
| [Local business, other](/structured-data/industries/local-business-other/) | 45 | 4 | 8 | 17.78% | 1 |
| [Retail and commerce](/structured-data/industries/retail-and-commerce/) | 43 | 6 | 6 | 13.95% | 4 |
| [Travel and lodging](/structured-data/industries/travel-and-lodging/) | 37 | 1 | 14 | 37.84% | 1 |
| [Finance and legal](/structured-data/industries/finance-and-legal/) | 24 | 1 | 10 | 41.67% | 0 |
| [Organizations, other](/structured-data/industries/organizations-other/) | 22 | 3 | 9 | 40.91% | 1 |
| [Automotive](/structured-data/industries/automotive/) | 15 | 0 | 3 | 20.00% | 0 |
| [Food and drink](/structured-data/industries/food-and-drink/) | 14 | 2 | 1 | 7.14% | 1 |
| [Education](/structured-data/industries/education/) | 14 | 3 | 3 | 21.43% | 2 |
| [Jobs and careers](/structured-data/industries/jobs-and-careers/) | 4 | 1 | 0 | 0.00% | 2 |
| Vocabulary machinery, not an industry | 333 | 31 | 208 | 62.46% | 5 |
| Unassigned | 26 | 2 | 19 | 73.08% | 0 |

Medical and health holds 88 types, more than any industry except media and publishing. Exactly one of them reaches a hundred thousand websites. Food and drink holds 14 types and two of those get there. Automotive holds 15, and not one does. So the length of an industry's vocabulary measures how much of it Schema.org has described, not how much of it anybody writes into a page. I expected the big vocabularies to be the used ones. The opposite is closer to the truth. If your industry is one of the long lists, the band beside a term matters more to you than the length of the list.

## Four industries have no rich result at all

The table lists the industries Google documents no rich result for, with the size of their vocabularies.

Between them those four industries hold 187 vocabulary terms. Medical and health is the sharpest of them, with 88 types, one of them on a hundred thousand websites, and nothing Google documents a rich result for. Google documents rich results for what it chooses to show in search. Those choices are not spread evenly across what Schema.org describes. That gap surprised me less than its size did. If you work in one of these four, no rich result is coming for your markup. The reason to write it is the other readers a page has.

That does not make markup in these industries pointless, because a search result is only one of the things that reads a page.

## Every industry

| Industry | Address | What it holds |
| --- | --- | --- |
| Media and publishing | /structured-data/industries/media-and-publishing/ | 164 types, 32 on 100,000 websites or more, 15 documented rich results |
| Medical and health | /structured-data/industries/medical-and-health/ | 88 types, 1 on 100,000 websites or more, 0 documented rich results |
| Places | /structured-data/industries/places/ | 60 types, 6 on 100,000 websites or more, 0 documented rich results |
| Events and entertainment | /structured-data/industries/events-and-entertainment/ | 48 types, 2 on 100,000 websites or more, 1 documented rich result |
| Local business, other | /structured-data/industries/local-business-other/ | 45 types, 4 on 100,000 websites or more, 1 documented rich result |
| Retail and commerce | /structured-data/industries/retail-and-commerce/ | 43 types, 6 on 100,000 websites or more, 4 documented rich results |
| Travel and lodging | /structured-data/industries/travel-and-lodging/ | 37 types, 1 on 100,000 websites or more, 1 documented rich result |
| Finance and legal | /structured-data/industries/finance-and-legal/ | 24 types, 1 on 100,000 websites or more, 0 documented rich results |
| Organizations, other | /structured-data/industries/organizations-other/ | 22 types, 3 on 100,000 websites or more, 1 documented rich result |
| Automotive | /structured-data/industries/automotive/ | 15 types, 0 on 100,000 websites or more, 0 documented rich results |
| Food and drink | /structured-data/industries/food-and-drink/ | 14 types, 2 on 100,000 websites or more, 1 documented rich result |
| Education | /structured-data/industries/education/ | 14 types, 3 on 100,000 websites or more, 2 documented rich results |
| Jobs and careers | /structured-data/industries/jobs-and-careers/ | 4 types, 1 on 100,000 websites or more, 2 documented rich results |

## How this is measured

Two kinds of claim sit side by side on these pages and they are not equally strong. A type reaches its industry one way. By ancestry through rdfs:subClassOf, never by name. Each assignment records the ancestor that produced it. A Google rich result feature is a page on Google's website, not a Schema.org type, so it has no parent to walk and it reaches its industry another way. One recorded judgement per feature, its primary Schema.org type, then assigned by the same ancestry walk. You can check those judgments against Google's own documentation, because the features carry the addresses of the pages they came from.

That walk reads an ordered list of industries, most specific first, because LocalBusiness is a subclass of both Organization and Place and the three cannot all be industries. A type takes the first industry it matches on the way up, so it lands on one page and not on three. The assignment keeps the ancestor that won. I show that ancestor beside the term on the industry pages, so you can see why a type sits where it does and disagree with me if you want to.

Not all of the vocabulary belongs to an industry at all. 333 of the 937 classes describe how markup is structured, not what a business does. Everything under Action, Intangible or DataType is counted there. Another 26 sit outside any industry, mostly datatypes, units of measurement and the bioscience terms. Folding either group into the nearest industry would inflate the industries with terms belonging to none of them, so both keep their own names.

Google rewrites its own documentation without announcing it, so a feature carries the address of the page I read it from and that page's own last-updated date. I read them on 11 August 2026 and the dates on those pages run from 10 December 2025 to 24 July 2026. My recommended gap report stops at 7 July 2026, which is earlier. Review snippet is the whole of the difference. That report lists only the features with at least one thinly used recommended property, and this one has none, so it appears here and not there.

The adoption figures here are bands, not counts. Google sorts the terms into six bands and publishes nothing inside them, so a term you can see on somewhere between one and ten million websites has no public exact number, on this page or anywhere else. A longer list of types does not mean a bigger industry in the economy either. These figures count vocabulary terms, not businesses or websites.

Analysis © Eduard Dziak, licensed under the Apache License 2.0. Please credit eduarddziak.com with a link. Source data: Google and the Schema.org community, Schema.org usage statistics dataset. Rich result requirements: Google Search Central, licensed CC BY 4.0. Term descriptions: Schema.org, licensed CC BY-SA 3.0, each term linking to its own page. Crawl counts: HTTP Archive Web Almanac, licensed Apache License 2.0.