There is a gap between what your maritime website says and what machines understand about it.
Your homepage might read: “Premier marine consultancy serving the global shipping and yachting sectors.” A human reads that and forms a rough picture: marine company, international scope. An AI assistant or search engine reads it and learns almost nothing – because “marine consultancy” could mean a hundred different things, and “global” tells it nothing about where you actually operate.
Schema.org structured data closes that gap. It is a vocabulary, endorsed by Google, Microsoft, Yahoo, and Yandex, that lets you describe your business, people, services, and content in machine-readable format. When implemented correctly, it tells AI systems and search engines exactly what you are, where you operate, who you serve, and what you can do for them.
What Schema.org Actually Is
Schema.org is a shared vocabulary for structured data. The data is added to your website using JSON-LD: a block of code placed in the <head> section of your page’s HTML. It does not affect how your page looks. Visitors never see it. But crawlers and AI systems read it and use it to understand your website at a deeper level than plain HTML allows.
Here is the practical difference. Without Schema.org, your contact page has text saying you are based in Rotterdam. A crawler might extract that accurately, or it might not. With Schema.org, you explicitly declare:
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "North Sea Marine Surveys",
"address": {
"@type": "PostalAddress",
"addressLocality": "Rotterdam",
"addressCountry": "NL"
},
"areaServed": ["North Sea", "Rotterdam port"],
"knowsAbout": ["hull surveys", "P&I surveys", "pre-purchase surveys"]
}The crawler now knows with certainty: this is an Organisation. It is in Rotterdam. It covers the North Sea. It does P&I surveys. No ambiguity, no inference required.
The Five Schema Types That Matter for Maritime Websites
1. Organization – The foundation. Every maritime company website should have an Organization schema on its homepage. Key properties: name, areaServed (specific sea areas, ports, countries), knowsAbout (your maritime specialisations), sameAs (LinkedIn, maritime directory listings). The knowsAbout property is particularly valuable: a buyer asking “who does ISM compliance auditing for tankers” can find you even if your homepage never uses that exact phrase.
2. Person – For captains, surveyors, naval architects, consultants. Key properties: name, jobTitle (be specific: “Master Mariner” rather than “Captain”), worksFor, knowsAbout, sameAs (LinkedIn profile URL). When your personal schema links to your LinkedIn profile and your LinkedIn links back to your website, AI systems build a coherent entity graph of you as a verified professional.
3. Service – Add a Service schema for each specific named service.
{
"@type": "Service",
"name": "Pre-Purchase Yacht Survey",
"description": "Class-independent pre-purchase condition surveys for yachts between 15 and 100 metres. Turnaround 48–72 hours.",
"areaServed": "Mediterranean, Northern Europe",
"serviceType": "Marine Survey"
}4. FAQPage – Wrap your FAQ section in FAQPage schema. Google uses this to generate rich results, and AI systems use it to extract authoritative answers to common buyer questions.
5. Article – For journal or blog posts. AI systems treat authored articles as citable sources. Key properties: headline, author, datePublished, publisher, about.
Implementation: The Technical Process
For WordPress: use the Rank Math SEO plugin. Its Schema module covers most of the types above without requiring you to write raw JSON-LD manually. Workflow: configure Organization schema in Rank Math settings → enable Article schema on all post types → add Service schema via custom schema builder for each service page → enable FAQPage schema on your FAQ section.
For custom-built sites: add JSON-LD blocks directly to the <head> section of your HTML. You can have multiple schema blocks on a single page and they do not conflict.
A Complete Schema Stack: Marine Survey Company Example
[
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Aegean Marine Surveys",
"url": "https://aegeanmarinesurveys.com",
"address": {
"@type": "PostalAddress",
"addressLocality": "Piraeus",
"addressCountry": "GR"
},
"areaServed": ["Eastern Mediterranean", "Black Sea", "Aegean Sea"],
"knowsAbout": ["hull and machinery surveys", "pre-purchase yacht surveys", "P&I surveys", "cargo surveys", "damage surveys"],
"sameAs": ["https://www.linkedin.com/company/aegean-marine-surveys"]
},
{
"@context": "https://schema.org",
"@type": "Service",
"name": "Pre-Purchase Yacht Survey",
"provider": {"@type": "Organization", "name": "Aegean Marine Surveys"},
"description": "Independent pre-purchase condition surveys for sailing and motor yachts up to 50 metres. 48-hour turnaround.",
"areaServed": "Eastern Mediterranean"
}
]Two More Types: FAQ and Article Schema
The organization, service, and location schema above tell a machine what your business is. Two further types tell it what your content is, and they are the ones most maritime sites miss.
FAQPage schema marks up a set of questions and answers so an AI system can lift them directly into an answer. This is the schema most closely tied to AI citation, because a well-formed question and answer is exactly the unit an answer engine wants to quote. A marine surveyor with a page answering the real questions buyers ask, marked up as FAQPage, gives an assistant a clean, attributable source.
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "How long does a pre-purchase yacht survey take?",
"acceptedAnswer": {
"@type": "Answer",
"text": "A pre-purchase condition survey for a yacht under 100 metres takes 48 to 72 hours from attendance to written report."
}
},
{
"@type": "Question",
"name": "Which ports do you cover?",
"acceptedAnswer": {
"@type": "Answer",
"text": "We attend vessels across the Northern European range, with regular coverage of Rotterdam, Antwerp, and Hamburg."
}
}
]
}
Article schema marks up each journal post so search engines and AI systems can attribute it correctly: who wrote it, who published it, and when. For a maritime business building topical authority through content, this is what connects a post to its author and organisation as verifiable entities rather than loose text.
{
"@context": "https://schema.org",
"@type": "Article",
"headline": "Preparing a Bulk Carrier for a Change-of-Flag Survey",
"author": {
"@type": "Person",
"name": "The named surveyor or author"
},
"publisher": {
"@type": "Organization",
"name": "North Sea Marine Surveys"
},
"datePublished": "2026-08-05",
"dateModified": "2026-08-05"
}
The JSON on its own does nothing. It has to sit inside a script tag in the page’s HTML, like this, one block per schema type. Place it in the head or anywhere in the body. Search engines and AI crawlers read it regardless of position.
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [ ... ]
}
</script>
On this site, FAQ schema is generated automatically for every journal post from the questions and answers on the page. The point of showing the raw form is that you can verify it, and add it to service pages and the homepage where a plugin will not.
How to Test Your Implementation
Google Rich Results Test – paste your URL or raw code and see which rich results Google can generate. Schema.org Validator – checks any JSON-LD against the specification and flags errors. Google Search Console – after schema is live a few days, the Enhancements section shows whether Google has detected and indexed your structured data.
Common Mistakes
Using the wrong type. Missing required properties (Article requires headline, author, and datePublished). Inconsistent entity data across schema versus footer. Stale schema not updated when services or locations change. Generic knowsAbout descriptions stuffed with keywords rather than readable claims.
The Return on a Few Hours’ Work
Implementing Schema.org correctly takes two to eight hours. After implementing, run the Maritime AI Visibility Audit to confirm your structured data is registering correctly. For most small maritime businesses, two to three hours builds a solid foundation. Unlike paid advertising, it does not stop working when you stop paying. Unlike social media, it does not depend on an algorithm. It is a permanent signal that tells every machine that reads you exactly who you are – in a sector where most competitors have not built that signal yet.
