Person Schema Markup: Tell Google and AI Exactly Who You Are

Search your own name and you might land on a dentist in another state, a defunct musician, or someone who shares your name and got arrested for something you've never done. Search engines and AI assistants don't know who you are the way a friend does. They're reading unstructured text scattered across the web and making a best guess about which facts belong to which person. Sometimes that guess is wrong, and your name ends up tangled up with somebody else's biography, photo, or bad press. Why Search Engines and AI Have to Guess When you write "Maria Lopez, Pastry Chef at Sweetleaf Bakery" on your own website, a human reader understands instantly who that sentence is about. A crawler reading the same page has to work harder. It sees a string of text, not a verified fact. It doesn't automatically know that the "Maria Lopez" on your About page is the same "Maria Lopez" who has a LinkedIn profile, an Instagram account, and a mention in a local newspaper. If there's another Maria Lopez online — and there almost certainly is — the crawler can mix up details between the two of you, or an AI model summarizing "who is Maria Lopez" can blend facts from both into one confused answer. This is the core problem behind a lot of mistaken-identity situations online: there's no explicit label saying "this specific person is the subject of this specific page." Structured data exists to fix exactly that gap. Instead of hoping a crawler correctly infers facts from paragraphs, you hand it the facts directly, in a format built for machines rather than humans. The stakes of this guessing game are higher than they used to be. It isn't only about where a page ranks in search results anymore. AI chatbots now routinely get asked questions like "who is Maria Lopez" or "tell me about [your name]," and they answer by pulling together whatever text they've encountered about anyone who shares that name. If the available information is thin or ambiguous about who you specifically are, the model fills in the gaps with the nearest match it has — which might be a stranger. Structured data doesn't rewrite an AI model on command, but it does make your own corner of the internet unambiguous, and that matters more as online reputation gets filtered through AI summaries instead of a page of search results. Person Schema and the sameAs Property Schema markup is a shared vocabulary that search engines and many AI crawlers understand. One piece of that vocabulary is the Person type, which lets you explicitly state things like a person's name, job title, location, and employer, directly in the code of a webpage. It's invisible to visitors — it doesn't change how the page looks — but it gives crawlers a clean, structured fact sheet instead of a paragraph to interpret on their own. The most useful property for anyone dealing with online confusion is sameAs. In plain terms, sameAs is how you tell a crawler "this LinkedIn profile, this Twitter/X account, and this website are all the same person." You list the URLs of your other profiles, and that list becomes a signal tying them together as one identity. Instead of a search engine treating your personal site, your LinkedIn page, and your Instagram as three separate, unrelated things it has to guess are connected, you've told it directly that they belong to the same person. This matters a lot when your name isn't unique. If there are five Maria Lopezes with public profiles, sameAs is one of the clearest ways to draw a box around which accounts belong to you specifically, rather than leaving the connection to inference. It's also one of the few signals you control completely — you're not asking anyone's permission to state which profiles are yours, you're simply publishing that fact in a format machines can read. A Working Example You Can Copy Below is a complete, working example for a fictional person — Maria Lopez, a pastry chef with a personal website, a LinkedIn profile, and an Instagram account. This is written in JSON-LD, which is the format search engines and most AI crawlers prefer for structured data. You can adapt it by swapping in your own name, job title, and profile URLs. <script type="application/ld+json"> { "@context": "https://schema.org", "@type": "Person", "name": "Maria Lopez", "jobTitle": "Pastry Chef", "url": "https://marialopezbakes.com", "image": "https://marialopezbakes.com/images/maria-lopez.jpg", "worksFor": { "@type": "Organization", "name": "Sweetleaf Bakery" }, "sameAs": [ "https://www.linkedin.com/in/marialopezbakes", "https://www.instagram.com/marialopezbakes", "https://twitter.com/marialopezbakes" ] } </script> A few notes on what's happening here. @type: "Person" tells the crawler this block of data describes a human being, not a business or a product. name and jobTitle are the basic facts. url points to the page this data lives on, which anchors everything else to that specific website. And sameAs is the list doing the heavy lifting — each URL is another place on the internet where this same Maria Lopez has a presence, so a crawler piecing together "who is Maria Lopez" has a direct, machine-readable trail to follow instead of a guess to make. You don't need every property filled in. If you don't have an employer to list, leave worksFor out entirely rather than putting in a placeholder. The same goes for any field that doesn't apply to you — an empty or made-up value is worse than no value at all, since it adds noise instead of clarity. Where to Actually Put This Code If you manage your own website's code directly, this script block goes in the <head> section of the page that's about you — usually your homepage or an About page. It doesn't need to go on every page of the site, just the one meant to represent you as a person. If your site runs on WordPress, Squarespace, Wix, or a similar platform, you generally won't be editing raw HTML files directly. Most of these platforms have either a built-in field for custom code in the page header, or a plugin that lets you add JSON-LD structured data without touching the rest of your site's code. The exact menu location varies by platform and changes over time, so it's worth checking your platform's current settings or plugin directory rather than following outdated instructions. Once it's added, you can use a structured data testing tool to confirm the markup is valid and being read correctly, rather than just trusting that you copied it right. These tools will flag typos, missing commas, or fields that don't match what the schema expects, which is easy to get wrong when copying by hand. Do I need to know how to code for this to work? Not really. You're not writing new code from scratch — you're copying a template, swapping in your own details, and pasting it into one field. The hardest part for most people is finding where their website platform lets them add custom header code, not writing the JSON-LD itself. Will this immediately stop AI from confusing me with someone else? No single fix works instantly, and schema markup doesn't come with any kind of guarantee — it's a signal, not a switch. AI models are trained on huge amounts of existing text, and that training data isn't rewritten the moment you add a script tag to your site. What schema markup does is make your own, current, correct information easier for new crawls and future lookups to parse and trust over time. It's one piece of a larger effort, not a one-step fix, and it tends to help more the longer it's been in place. What if I have more than one website or profile that represents me? Add the same Person schema, with the same sameAs list, to each site you control. Consistency is the point — if your personal site, your professional portfolio, and a side project all point to the same set of profiles as "this is the same person," that repetition reinforces the signal rather than diluting it. One Piece of a Bigger Picture Person schema markup won't rewrite anything that's already out there about you, and it won't untangle every mix-up instantly. But it's one of the few concrete, doable things you can set up once and leave running — a clear, standing signal about who you actually are, sitting on a page you control. If you're dealing with the broader problem of being confused with someone else online, it's worth reading why AI sometimes confuses you with someone else for the full picture of how these mix-ups happen and what else helps. If you run a local business under your own name — a salon, a private practice, a studio — a similar structured data approach applies to the business itself. Our LocalBusiness schema generator can help you build that version without writing any code. And once you've made a change like this, the natural next step is checking whether it's actually landing. Tailwind's free AI name check lets you see what ChatGPT, Gemini, and Claude currently say when asked about you, so you can keep AI from linking you to the wrong person and track whether your profile is coming through clearly as more of it builds up over time.