Why Your About Page Is One of the Most Underrated Trust Signals
Most e-commerce brands spend enormous energy optimising product pages and category pages, then leave their About page as an afterthought. A few paragraphs about how the company was "founded with a passion" and a team photo that's three years out of date. It is a missed opportunity on two fronts: human credibility and machine understanding.
AI search engines, including ChatGPT, Perplexity, and Gemini, are actively trying to determine which brands are legitimate, established, and worth recommending. They do this partly through signals embedded in your structured data. Your About page, properly marked up with AboutPage schema, is one of the clearest signals you can send that says: this is a real business, here is who we are, and here is why you can trust us.
Without schema markup, an AI model reading your About page sees a wall of text. It has to guess what the page is about, who the organisation is, and how it all connects to your other pages. With AboutPage schema, you are doing the interpretation work for it. You are handing over a structured, machine-readable summary that AI systems can pull from directly when composing responses about your brand.
What AboutPage Schema Actually Does
AboutPage is a type in the Schema.org vocabulary that sits within the WebPage hierarchy. It tells crawlers and language models that the page in question is specifically about describing an organisation, person, or subject. On its own, it is a relatively simple type, but its value comes from what you nest inside it.
The real power is in combining AboutPage with a nested Organization entity. This is where you provide the structured details that AI engines can actually use: your brand name, founding date, description, social profiles, contact information, and area of expertise. Together, these create a machine-readable identity card for your business.
Think of it this way. When someone asks ChatGPT "who are [your brand]?", the model is drawing on everything it has indexed about you. If you have a well-structured AboutPage with a nested Organization, you are giving the model accurate, authoritative source material to work from. If you do not, it is guessing based on whatever fragmented mentions of your brand exist across the web.
The JSON-LD Structure You Need
Here is a practical, annotated example of AboutPage schema implemented in JSON-LD. This is the format Google and most AI crawlers prefer, and it should be placed in a <script type="application/ld+json"> tag in the <head> of your About page.
{
"@context": "https://schema.org",
"@type": "AboutPage",
"name": "About Acme Running Co.",
"url": "https://www.acmerunning.co.uk/about",
"description": "Learn about Acme Running Co., a UK-based running gear brand founded in 2015, committed to helping everyday runners perform better.",
"about": {
"@type": "Organization",
"name": "Acme Running Co.",
"url": "https://www.acmerunning.co.uk",
"logo": "https://www.acmerunning.co.uk/images/logo.png",
"foundingDate": "2015",
"description": "Acme Running Co. designs and sells performance running gear for recreational and competitive runners across the UK.",
"contactPoint": {
"@type": "ContactPoint",
"contactType": "customer support",
"email": "hello@acmerunning.co.uk",
"availableLanguage": "English"
},
"address": {
"@type": "PostalAddress",
"streetAddress": "12 Stride Lane",
"addressLocality": "Manchester",
"postalCode": "M1 2AB",
"addressCountry": "GB"
},
"sameAs": [
"https://www.instagram.com/acmerunningco",
"https://www.linkedin.com/company/acme-running-co",
"https://www.facebook.com/acmerunningco"
]
}
}A few things worth noting here. The about property is doing a lot of work. It links the page itself to the entity the page describes, which is your organisation. The sameAs array is particularly important for AI visibility: it tells the model that your brand's Instagram, LinkedIn, and Facebook profiles are all the same entity. This is how AI engines build a coherent understanding of who you are across the web.
The foundingDate field is worth filling in accurately. Brands with a listed founding date are perceived as more established. It is a small detail that contributes to overall entity trustworthiness in knowledge graphs.
The sameAs Property and Entity Disambiguation
One of the trickier problems AI search engines face is entity disambiguation. If your brand name is common or shares words with other concepts, a model can get confused about which entity it is referring to. The sameAs property is your best tool for solving this.
By listing your Wikidata entry, Companies House profile, Crunchbase page, social profiles, and any other authoritative mentions, you are creating a web of corroborating signals that all point to the same entity. AI models use this information to build confidence that the brand they are describing is the one the user is asking about.
If you have a Wikipedia page, include it. If you are listed on Wikidata (which you can create yourself for free), include that too. Wikidata entries carry significant weight with AI crawlers because they are structured, community-maintained knowledge bases that models have been extensively trained on.
For brands without a Wikipedia page, which is most e-commerce brands, the combination of a Wikidata entry plus consistent social profile URLs in sameAs is the next best thing. It is an area where a structured data strategy, like the kind FlinnSchema approaches differently from standard SEO agencies, can make a meaningful difference to how confidently an AI engine identifies and recommends your brand.
Connecting AboutPage to the Rest of Your Schema Ecosystem
Schema markup works best as a connected system, not isolated snippets on individual pages. Your AboutPage should tie into the broader entity graph you are building across your site.
Link to your WebSite schema
If you have WebSite schema on your homepage (which you should), the Organization entity you define there should share the same @id as the one in your AboutPage. Using a consistent @id, typically your homepage URL, means crawlers can recognise these as the same entity across different pages rather than treating them as separate mentions.
Reference your ContactPoint
Nesting a ContactPoint inside your Organization, as shown in the example above, helps AI engines understand how users can reach you. This is particularly useful for voice and conversational AI queries like "how do I contact [brand]?" You can read more about how ContactPoint schema helps AI route enquiries in a dedicated guide.
Tie in your Brand schema
If you sell products, your product pages should reference a Brand entity. That brand entity should share identifying details with the organisation defined in your AboutPage. Consistency across these references is what allows AI engines to confidently attribute products, reviews, and editorial content to the correct brand.
Common Mistakes Brands Make With AboutPage Schema
Having reviewed hundreds of e-commerce sites, these are the errors that come up most frequently.
Treating it as a formality
Adding a bare @type: "AboutPage" with no nested entities is almost pointless. The type declaration alone does very little. The value is in the structured content you put inside it.
Mismatched information
If your schema says you were founded in 2018 but your About page copy says 2017, and your LinkedIn says 2019, that inconsistency signals unreliability to AI systems. Keep everything aligned. AI models are increasingly good at spotting contradictions across sources and they penalise entities that appear inconsistent.
Forgetting the description field
The description property on your Organization is often lifted almost verbatim by AI engines when summarising a brand. Write it carefully. Be specific about what you do, who you serve, and what makes you distinct. Aim for two to three sentences that you would be happy to see quoted in an AI-generated answer.
Omitting social profiles from sameAs
Many brands add schema without the sameAs array, leaving the organisation floating in isolation. Even if you only have two or three social profiles, include them. Every corroborating URL strengthens the entity signal.
How AI Search Engines Actually Use This Data
It is worth being realistic about how this works in practice. AI language models do not read your schema at query time in the way a search engine crawler does. Instead, the structured data influences how your content is understood and indexed during crawling, which then shapes the training data or retrieval index that the model draws on when answering questions.
Perplexity, for instance, uses a live retrieval layer. When someone asks about your brand, Perplexity fetches current web content and summarises it. If your About page is well-structured with clear schema, the retrieval model is more likely to pull accurate, brand-controlled information rather than a third-party description that may be outdated or inaccurate.
ChatGPT with Browse enabled operates similarly. Gemini's AI Overviews in Google Search use structured data heavily to populate the entity cards that appear in AI summaries. In all three cases, having properly structured AboutPage schema puts you in a stronger position than brands that rely purely on unstructured page text.
If you are unsure how your brand currently appears in AI search responses, a good starting point is a free AI visibility audit, which can surface gaps in your structured data before they become missed opportunities.
Implementing on Shopify and WordPress
The mechanics of adding JSON-LD to your About page differ slightly depending on your platform.
Shopify
On Shopify, your About page is typically a standard page template. You can add JSON-LD directly to the page template in your theme's Liquid files, or use a custom HTML section that you add only to the About page. Avoid plugins that inject generic organisation schema sitewide, as these often produce inconsistent or duplicate markup.
WordPress
In WordPress, most SEO plugins (Yoast, Rank Math) will add some organisation schema automatically, but their output is often generic and lacks the depth needed for meaningful AI visibility. Adding a manual JSON-LD block to your About page using a custom HTML widget or a code-injection plugin gives you full control over the output. You can then check the rendered markup using Google's Rich Results Test to confirm it is parsing correctly.
Frequently Asked Questions
Does AboutPage schema affect Google rankings directly?
Not in a direct, measurable way. Google does not use AboutPage schema to trigger rich results in the same way it does for Product or FAQ schema. However, it contributes to entity understanding in Google's Knowledge Graph, which influences how your brand appears in AI Overviews, Knowledge Panels, and other AI-driven features. The indirect SEO benefit is real, even if it is harder to attribute.
Should I put AboutPage schema on every page or just my About page?
Just your About page. The schema type is specifically designed for pages that describe an entity, and using it sitewide would be semantically incorrect. Your homepage should carry WebSite and Organization schema. Product pages get Product schema. Keeping each schema type on the appropriate page is important for accuracy and avoids confusing crawlers.
What if I do not have a Wikidata entry? Is it worth creating one?
Yes, for most established e-commerce brands it is worth the effort. Wikidata is free to edit, and an entry for your brand that includes founding date, headquarters location, website URL, and social profiles creates a structured knowledge base record that AI systems have been trained on extensively. It takes about 30 minutes to set up and can meaningfully strengthen your entity recognition in AI search. Just make sure the information you submit is accurate and consistent with your website.
How do I know if my AboutPage schema is working?
Start with Google's Rich Results Test (search.google.com/test/rich-results) to confirm your JSON-LD is valid and parsing without errors. Then manually query AI engines with questions like "who is [your brand]?" and "what does [your brand] do?" to see what information they surface and whether it matches your structured data. You can also monitor your brand's appearance in Perplexity by searching your brand name directly. For a more systematic approach, tracking AI visibility over time gives you a clearer picture of whether your schema investments are paying off.