TL;DR

Structured data and schema help search engines, AI platforms and other information retrieval systems to understand your business, products and/or services, and expertise more accurately. Our Structured Data and Schema service audits existing implementations, develops entity-driven schema frameworks, maps your business into relevant knowledge graphs and creates machine-readable connections that improve discoverability, entity recognition and long-term visibility across traditional and AI-powered search.

Pain points

Schema is one of those things in the world of digital marketing that acts as a nudge – there are no clear penalties to not having it (if you remove it from a page, you’re not going to drop out of the index) and the benefits are not of the magnitude of some others (adding it to a page isn’t going to magically allow you to capture a p.1 ranking), but what good structured data does, albeit incrementally, is begin to properly build a recognisable entity of your brand, its products and/or services and its key representatives which can be understood by search engines.

While this is, at the moment, something brands can add to give themselves a boost over competitors that are at a similar level in search, but as we move into an ‘agentic’ or machine learning dominated, increasingly ‘zero-click’ era of search, having this kind of well defined digital entity can be the difference between an ‘AI’ search query referencing you or a competitor.

• Search platforms showing poor or incorrect understanding of your business.
• Important search terms returning rich results in which you can’t appear.
• Schema errors showing in Google Search Console.
• Low or zero appearance of important brand entities for relevant searches.

What we mean by structured data and schema

The vast majority of online information is unstructured text chains – blogs, service pages, product descriptions, comments and much more – because the way humans communicate is mostly structured in non-verbal, non-textual ways. We communicate a lot of information in ways which are not immediately obvious – through gesture, through tone, through cultural and media references, punctuation and pauses – these are often not translated into text.

Take the sentence ‘Buffalo buffalo buffalo Buffalo buffalo’ where the same word is a noun adjunct, a proper noun, and an adjective (if you think this is bad, the actual example often used has three extra buffalo). Something like this (were it not already contextualised online elsewhere) would be impenetrable to any of the current transformers employed by ‘AI’ search platforms. 

Structured data allows us to tag various elements of and entities in the sentence using things like: “@type”: “DefinedTerm”, and “@sameAs” to clearly reference existing elements which exist in authoritative databases – like the WikiData ontology or Wikipedia – to help even the algorithms enjoy the fact that “animals known as buffalo (from the place Bufallo) have a tendency to intimidate other animals known as Buffalo from the place Buffalo”.

While this is illustrative (the sentence has its own Wikipedia page, so will appear in all current ‘AI’ training datasets), it provides the essence of what structured data and schema can do. It takes messy, unstructured and often difficult to parse information and renders it digestible by algorithms. The reason given for its use in the past has tended to be that schema opens up access to a range of rich results in Google (RIP to the FAQ), but the real reason has always been that structured data contextualises your data and connects it to the wider web, allowing your information and your brand to be better understood by machines.

Modern schema should be about building a consistent, machine-readable representation of your business across your entire digital presence – you’re not simply describing a page, but creating connections between your organisation, products, services, people, locations, expertise and external knowledge sources – and that’s the aspect of structured data and schema that will help you across search and discovery platforms.

MMC Digital’s structured data and schema service

Structured data is one of those areas where there’s a huge difference between a basic and strategic implementation. Most sites that have schema (and most do to greater or lesser degrees) will have added a plugin which will generate some Organization and Product schema (perhaps some FAQ markup when it mattered for rich results) and called it a day. That approach, though better than we were a decade ago, misses out on a lot of the value.

We approach structured data as an entity and information architecture exercise, rather than one to capture a rich result. While eligibility for search features is important, the primary focus of this service is making sure search engines, AI systems and other information retrieval platforms understand exactly who you are, what you do, who represents your business, and how all of those things are related.

Clients choosing MMC Digital for structured data and schema support can expect:

• Structured data audit – we review existing schema implementation, validate it against Schema.org standards, identify errors, omissions and conflicting markup, and establish how effectively current implementation communicates to discovery platforms.
• Entity mapping and knowledge graph development – we identify the key entities within your organisation (people, services, products, locations and areas of expertise), then create a structured framework that connects those entities together, and aligns them with recognised external knowledge sources where appropriate.
• Schema architecture planning – rather than treating each page as an isolated asset, we design a connected schema framework which supports the wider understanding of your business, strengthening relationships between your organisation, content, services and your subject matter expertise.
• AI and retrieval optimisation – as search moves beyond traditional ranking systems, we assess how structured data can improve the discoverability, accessibility and contextual understanding of your content by all search platforms, large language models and emerging retrieval systems.
• Implementation support – depending on your requirements, we can provide implementation documentation, liaise with developers, review third-party work or handle implementation directly where access and platform limitations allow.

Like many areas of technical SEO, structured data works best when implemented consistently and thoughtfully across an entire website. Our aim here is to create a durable framework that continues delivering value as search technologies evolve.

What can our structured data and schema service do for your business?

Structured data helps machines understand your business with clarity human visitors take for granted. Search engines, AI assistants and retrieval systems need context to decide when your content is relevant, trustworthy and deserving of recommendation. Schema helps to provide that context. Our Structured Data and Schema service can help you to:

• Improve search engine understanding of your business, services and expertise.
• Strengthen entity recognition and knowledge graph associations.
• Increase eligibility for relevant rich results and enhanced search features.
• Improve the accuracy with which search engines interpret your content.
• Create stronger relationships between your organisation, people, services and content.
• Reduce schema errors, inconsistencies and implementation conflicts.
• Support AI retrieval systems, LLMs and emerging search technologies.
• Build a stronger technical foundation for future SEO and digital marketing activity.

Structured data has always been, but is more than ever about helping machines understand your business like your customers already do: who you are, why you matter, and when you should be recommended.