- SCHEMA MARKUP · STRUCTURED DATA · JSON-LD · HERTFORDSHIRE
Schema markup & structured data in Hertfordshire.
Hand-coded JSON-LD that makes ChatGPT, Gemini, Perplexity, and Google AI Overviews cite your brand. No plugins. No bloat. Real Schema.org markup written for entities — not just rich snippets.
▸ Hertfordshire-Based · Founded 2007 · Hand-Coded JSON-LD · 15+ Years Technical SEO
More AI citations with valid schema
0
x
Schema types with active rich-result support
0
Of clicks go to rich results (Sistrix)
0
%
YOUR HERTFORDSHIRE SCHEMA AGENCY
Hand-coded structured data, written for AI search.
Schema markup is structured code — almost always written in JSON-LD — that explicitly tells search engines and AI engines what your content represents: this is an organisation, that is an article, this person is the author, this is a service offered in Bushey. Schema is the layer between your content and Google’s Knowledge Graph, ChatGPT’s training corpus, Perplexity’s retrieval system, and Gemini’s entity index. Without it, AI systems guess. With it, they know.
Most Hertfordshire businesses still rely on a generic SEO plugin to “handle schema.” That used to be enough. It is not enough in 2026. Plugin-generated markup covers the basics, repeats the same boilerplate across every page, and almost never declares the
sameAs, knowsAbout, or entity relationships AI search engines actually use. Cranberry hand-codes JSON-LD for every property that matters — including the entity properties Google’s Knowledge Graph and AI Overviews depend on.
Pages with properly implemented structured data are cited up to 3× more often in AI-generated search results than pages without it (Demand Local citation analysis, 2026). Around 60% of Google searches now end without a click (Search Engine Land, 2025). The brands appearing inside AI Overviews and ChatGPT answers are the ones with valid Organization schema, FAQPage schema, and a complete sameAs array linking to LinkedIn, Wikidata, and Crunchbase. Run our free AI Visibility Tool to see exactly which schema types you’re missing.
Schema markup is the foundation of our Visibility pillar Strategy without schema is theory. AI SEO without schema is a guess. Structured data is what makes everything else legible — to Google, to ChatGPT, to your buyers.
- Organization.jsonld
// Cranberry hand-coded schema
{
"@context": "https://schema.org",
"@type": "Organization",
"@id": "#org",
"name": "Cranberry Marketing",
"foundingDate": "2008",
"address": {
"@type": "PostalAddress",
"addressLocality": "Watford",
"addressRegion": "Hertfordshire"
},
"sameAs": [
"https://linkedin.com/...",
"https://wikidata.org/...",
"https://crunchbase.com/..."
],
"knowsAbout": [
"GEO", "AI Visibility",
"Schema Markup"
]
}
Validates against
Rich Results Test ✓ Schema.org ✓
CORE SCHEMA TYPES WE IMPLEMENT
The schema types that move the needle. All hand-coded.
Schema.org defines hundreds of types. Five drive 80% of AI search visibility — Organization, Article, FAQPage, BreadcrumbList, and Product or Service. Cranberry hand-codes all of them, plus the entity-rich properties (sameAs, knowsAbout, @id graphs) most plugins ignore.
1. Organization Schema
The single highest-leverage schema type for AI search. Declares your brand as a real entity with name, logo, founding date, contact, and — critically — a sameAs array linking to LinkedIn, Wikidata, Crunchbase, and Companies House for Knowledge Graph entity verification.
2. FAQ Page Schema
The schema type AI engines extract most directly. Marks Question/Answer pairs in JSON-LD so ChatGPT, Perplexity, and Google AI Overviews can quote answers verbatim. Pages with FAQ schema appear in AI Overviews at meaningfully higher rates than equivalent unstructured pages.
3. Article & Blog Posting
Establishes content authorship, publish date, and modification date — the freshness signals AI engines weight heavily. Includes Person schema for the author, references to the publishing Organization, and about/mentions properties that connect content to entities AI already recognises.
4. Loca lBusiness Schema
For Hertfordshire businesses with a physical presence: name, address, geo coordinates, opening hours, areaServed, and price range. The single most important schema type for “near me” searches, Google Business Profile authority, and Google Maps visibility — and increasingly used by AI Overviews for local recommendations.
5. Product & Service Schema
Product schema with offers (price, currency, availability), reviews, SKU, and brand — essential for eCommerce and Google Shopping. Service schema with provider, areaServed, and offer details — essential for service businesses being compared inside AI shopping assistants and answer engines.
6. Breadcrumb List & How To
BreadcrumbList tells search engines and AI how your site is structured. HowTo marks step-by-step content so AI can cite specific steps as guides. Both are simple to implement, both are systematically missing on most Hertfordshire sites, and both improve AI extraction confidence.
Free Schema Audit Tool
Want to see exactly which schema types your site is missing — and where existing markup is broken? Run our free AI Visibility Tool. It checks crawlability, schema validity, entity signals, and Knowledge Graph presence in 60 seconds. No contact details required to start.
Bonus: Entity Properties
The properties most agencies skip: sameAs (the connective tissue between your site and the Knowledge Graph), knowsAbout (topical authority for AI Mode), @id graph references (entity relationships across pages), and speakable (passages flagged for AI synthesis). These are where AI citation rate is won or lost.
HOW SCHEMA WORKS FOR AI
The three stages between your code and an AI citation.
Every AI citation passes through three sequential schema-dependent stages. Fail any one of them and your brand doesn’t appear in the answer. Cranberry audits and engineers all three.
01
Entity Verification
When ChatGPT or Google AI is asked about a company, product, or topic, it first checks for structured entity declarations. Organization schema with name, URL, logo, founding date, and a complete sameAs array tells AI engines who you are — and lets them cross-reference against Wikidata, LinkedIn, Crunchbase, and Companies House. Without this, AI can’t confidently cite you.
- Organization Schema
- Same As links
- Wikidata entry
- @id graph
02
Fact Extraction
Once the AI confirms who you are, it parses your JSON-LD to pull specific data points: prices from Product schema, steps from HowTo schema, answers from FAQPage schema, opening hours from LocalBusiness schema. This structured extraction is faster and more reliable than scraping prose. Pages without schema force AI to guess — and AI prefers to skip rather than hallucinate
- FAQPage schema
- Product/Service schema
- How To steps
- Article freshness
03
Citation Selection
Among multiple sources that pass stages 1 and 2, AI engines prefer the source with the cleanest, most accurate, and most validated structured data. Knowledge Graph confirmation, Person schema for authors, knowsAbout topical authority, and consistent freshness signals all tilt the citation decision. Schema is the deciding signal at the margin — and the margin is where citations are won.
- Person + author schema
- knows About property
- datePublished / dateModified
- speakable markup
Most agencies stop at stage 1. Cranberry hand-codes for all three — because the difference between being “indexed” and being “cited” is the difference between visibility and traffic.
PLATFORM-BY-PLATFORM
Five AI search engines. Five ways they use your schema.
Every major AI engine parses JSON-LD — but they weight different schema properties for different reasons. ChatGPT leans on Organization and sameAs. Perplexity favours FAQPage and freshness. Google AI Overviews demand validated rich-result schema. Cranberry implements for all five.
ChatGPT
800M+ weekly users · Citation source
When ChatGPT browses live, it parses JSON-LD to confirm entity identity before citing. Organization schema with a complete sameAs array (LinkedIn, Wikidata, Crunchbase, Companies House) is the strongest signal that you are who you say you are.
7-9 sources cited per response — schema-validated entities preferred — Seer Interactive
Organization + sameAs
Person schema for authors
knowsAbout property
Wikidata cross-reference
Perplexity
22M+ users · Real-time citations
Perplexity rewards recency and structured Q&A. FAQPage schema with answers under 80 words is the format Perplexity quotes most cleanly. Article schema with datePublished + dateModified tells it what’s fresh.
4-8 citations per response · clickable inline links — schema speeds extraction
FAQPage schema
Article datePublished
BreadcrumbList
HowTo step extraction
Claude
Anthropic · Long-context AI
Claude prioritises factual accuracy and citation-rich documentation. Article schema with explicit author Person schema, references to publishing Organization, and about/mentions properties for entity linking are exactly what Claude looks for when selecting trusted sources.
2-7 domains cited per response — clean schema is a tie-breaker
Person schema (authors)
about / mentions
Article + publisher
Long-form schema depth
Gemini & AI Mode
Google · 9 domains cited per query
Gemini inherits heavily from Google’s index and Knowledge Graph — which means schema feeds directly into how Gemini understands your brand. Organization sameAs links, LocalBusiness schema, and validated entity data drive Knowledge Panel accuracy and AI Mode citation rate.
9 domains cited per query · Knowledge Graph entities favoured
LocalBusiness schema
Knowledge Graph sameAs
Service areaServed
Strong rich-result base
Google AI Overviews
Above the fold on Google
AI Overviews demand the strictest schema validation. Google’s March 2026 update tightened content-schema alignment — markup must match the primary content topic exactly. FAQPage, HowTo, and validated Product schema drive most AI Overview citations.
31 schema types still actively support rich-result eligibility
FAQPage schema
HowTo schema
Strict validation
Content-schema match
Copilot & Others
Bonus coverage
Microsoft’s AI search blends Bing’s index with GPT-4. Lower volume, high intent — and heavily reliant on the same Schema.org vocabulary. We also implement schema patterns that work for emerging engines (Grok, You.com, Brave Leo, DeepSeek) to future-proof the work.
Cross-engine Schema.org standard — write once, parsed everywhere
Bing Webmaster Tools
Schema.org standard
Cross-engine validation
Future-proof markup
PLUGIN VS HAND-CODED
Why most "schema markup" is leaving money on the table.
90% of websites with schema use plugin-generated markup (Yoast, Rank Math, Schema Pro). It covers the basics — and stops there. Here’s what’s missing, and what hand-coded JSON-LD adds.
PLUGIN-GENERATED
Most agencies stop here
- Generic Organization schema — no sameAs array, no knowsAbout, no founder Person reference
- WebPage schema only — same boilerplate copied across every page on the site
- No entity @id graph — pages don't reference each other; AI can't traverse relationships
- Auto-generated FAQ schema — often missing answers, often broken when content updates
- No Service schema with provider, areaServed, or offer details
- No Person schema for authors — kills E-E-A-T signals AI checks
- No validation routine — silent breakage when WordPress, Yoast, or your theme updates
CRANBERRY HAND-CODED
What we actually deliver
- Full Organization schema with sameAs (LinkedIn, Wikidata, Crunchbase, Companies House) and knowsAbout topical authority
- Page-specific schema — Service, Product, Article, FAQPage, HowTo — each one engineered for its page type
- @id graph references connecting Organization → WebSite → WebPage → Article → Person across the site
- Hand-written FAQ Page schema matching visible content exactly, answers under 80 words, citation-ready
- Service schema with area Served — pulls Hertfordshire-specific entities into AI Mode local recommendations
- Person schema for every author — jobTitle, sameAs (LinkedIn), worksFor, knowsAbout — full E-E-A-T graph
- Validated against Rich Results Test + Schema Markup Validator before deployment, monitored monthly
SCHEMA TYPES BY AI-SEARCH IMPACT
The schema priority list for AI citation.
Not all schema types carry equal weight. Here’s the priority order Cranberry uses, based on citation analysis across Google AI Overviews, ChatGPT, Perplexity, Claude, and Gemini.
| Schema Type | Why it matters for AI | Priority |
|---|---|---|
| Organization (sameAs) | The single highest-leverage schema type. sameAs links to LinkedIn, Wikidata, Crunchbase, Companies House and help AI verify your entity identity in the Knowledge Graph. | Critical |
| FAQPage | The schema AI engines extract most directly. Question/Answer pairs in JSON-LD are quoted by ChatGPT, Perplexity, Gemini and Google AI. | Critical |
| Person (authors) | Establishes E-E-A-T. Author schema with jobTitle, worksFor, sameAs and knowsAbout strengthens trust signals. | Critical |
| LocalBusiness | Essential for local businesses. Address, geo, openingHours and areaServed help drive local recommendations and map visibility. | High |
| Service | Defines provider, areaServed and offers properties. Helps AI understand exactly what services you provide. | High |
| Product (with offers) | Essential for eCommerce. Price, currency, availability, AggregateRating and Review data improve shopping visibility. | High |
| Article / BlogPosting | datePublished, dateModified, headline, author and publisher create stronger freshness and authority signals. | High |
| BreadcrumbList | Helps AI understand site structure. Easy to implement and useful for citation pathways and rich results. | Medium |
| HowTo | Step-by-step content marked up so AI can cite specific actions and instructions directly. | Medium |
| VideoObject | Makes embedded video content machine-readable through transcript, thumbnail and duration data. | Medium |
| Investment | Site-wide hand-coded schema implementation, validation, monitoring and documentation as a fixed-fee engagement. | From £750 |
Industry-specific schema unlocks more.
Regulated verticals such as healthcare, legal, financial services and other
specialist industries benefit from dedicated schema types. Run our
free schema audit to discover what your site
is missing and plan a complete implementation strategy.
WHERE SCHEMA FITS
Schema markup is the technical foundation of the Visibility pillar.
Cranberry organises every service around three pillars. Schema is the layer that makes the entire Visibility pillar function — without it, AI engines can’t reliably understand who you are, what you do, or whether to cite you.
1. Clarity
FOUNDATION
Branding, messaging, web structure. Schema markup needs clear visible content to mirror — Clarity is what your structured data declares.
YOU ARE HERE
2. Visibility
MACHINE-READABLE
Schema is the API between your site and every AI system that reads it. Without it, GEO and AI SEO are guesswork. With it, AI engines parse your site deterministically.
3. Growth
CONVERT
AI traffic converts at 9× the rate of Google organic (Seer Interactive). Clean schema is the cheapest, highest-leverage way to start capturing it.
WHY CRANBERRY
What sets us apart from a Yoast SEO plugin.
01
Hand-coded JSON-LD. Zero plugin dependency.
Every line of structured data we ship is hand-written, validated, and version-controlled. Plugins like Yoast, Rank Math, and Schema Pro generate the same boilerplate across thousands of sites — and skip the entity properties (sameAs, knowsAbout, @id graphs) AI search engines actually use. We write JSON-LD in your CMS or theme directly, so it survives plugin updates and works whether you’re on WordPress, Shopify, Webflow, or custom-built. The only “plugin” you need afterwards is one to inject the code — not generate it.
02
Built for AI search, not just rich snippets.
Most agencies still treat schema as a “rich result” play — chasing star ratings and FAQ dropdowns. That’s a 2019 strategy. In 2026, the highest-leverage schema work is entity disambiguation for AI Overviews, ChatGPT, and Perplexity: Organization with full sameAs, Person schema for authors, knowsAbout for topical authority, @id graph references across pages. Cranberry implements both layers — visible rich results and the invisible entity layer that drives AI citation rate.
03
Free Schema Audit Tool.
See exactly which schema types your site is missing — and where existing markup is broken — before you spend a penny. Run the free tool → Sixty seconds. Branded report. No sales call.
04
Hertfordshire's only schema specialist.
Most local SEO agencies in Hertfordshire don’t offer schema markup as a named service. Cranberry does — based in Watford, founded 2008, with 15+ years of technical SEO across UK, USA, KSA, UAE, and Pakistan markets.
05
Validated & monitored.
Every implementation passes Google’s Rich Results Test and the Schema.org Markup Validator before deployment. Then we monitor monthly via Search Console — because plugin updates and content edits silently break schema all the time.
CLIENT RESULTS
Real businesses. Real results.
LOCAL SEO + WEB DESIGN
Moroccan Garden
ILFORD, UK · SHISHA LOUNGE
Traffic uplift / 3 months
0
%
More users / year
400
%
Returning users
0
%
LOCAL SEO + CONTENT
Dunk Burgerz
LUTON, UK · HALAL SMASH BURGERS
Monthly Orders
0
x
"Smash Burgers Luton"
#
Organic Views
0
%
SEO + WEB DESIGN
Reveal Medical Centre
DUBAI · DENTAL & DERMATOLOGY
Competitive Terms
#
0
Sustained Rankings
yrs
Booking Enquiries
0
+
GET IN TOUCH
See your schema gaps. Then fix them.
Run our free AI Visibility Tool first — it scans your site for schema validity, missing types, broken FAQPage markup, and missing entity properties in 60 seconds. Or book a call with founder Faraz to scope a hand-coded JSON-LD implementation across your site.
Submit your Query:
Your details will never be shared. We promise a spam-free experience.
OUR SCHEMA IMPLEMENTATION PROCESS
Six steps from audit to validated deployment.
Every Cranberry schema engagement follows the same structured workflow. Transparent, time-boxed, and fully documented at every stage — typically 2-4 weeks from kickoff to live.
INDUSTRIES SERVED
Schema markup for every category where AI search matters.
Some industries see disproportionate value from hand-coded structured data — typically those with complex offerings, regulated environments, or commercial intent buyers AI search engines now influence directly. These are the verticals where Cranberry has shipped the strongest schema implementations.
Hospitality & F&B
E-commerce
Law
Dental & Medical
B2B Trade
Property
Health & Fitness
Healthcare IT
Professional Services
Beauty & Aesthetics
Trading
Pet Products
Jewellery
Recruitment
Education
If your industry isn’t listed, book a call — chances are we’ve worked with someone close to it.
TESTIMONIALS
What clients say about working with us.
I am the co-founder of FRX, a Dubai-based Life Science and Biotech company engaging with a wide range of players within the healthcare industry. I have worked with Faraz and the Cranberry Marketing team for our Website Design and Development and they delivered this project in a very efficient and timely manner, carefully analysing and integrating our feedback in the process.
Pauline Ogrodzki
I used Cranberry Marketing for 2 projects which includes website design and development. I'm very pleased with the results as the workflow and communication is great. They are also good value even with additional changes, they did not charge much extra. I recommend them.
Hass
Faraz and Cranberry are the best. We initially appointed them in 2014/2015 to help redesign our corporate branding. They did a wonderful job that was fresh, crisp and in line with our vision. They then went on to design our website as well, which they have redesigned several times since.
They are intensely focused and take their work commitments very seriously. If you’re looking for a team that will deliver your vision and be a long time partner and solution, Cranberry is that team.
Saad
Our company had used the services of cranberry for 5 years: hosting and emails. Their support was great and attended to our tech issues (though little) promptly.
Mazin Gabora
Fantastic quality of work from the Cranberry Team for us here in Watford. Have been a critical part of the maturity of our legal business and we are very pleased with the outcome of our website design and layout.
Abid Riaz
Tealand’s online presence has transformed thanks to Cranberry Marketing’s efforts. Not only did they build us a stunning e-commerce store, but their local SEO efforts have made sure we’re easily discoverable in Dubai. The combination of a beautiful site and higher visibility has done wonders for our sales!
Hrach Avetisyan
Working with Cranberry Marketing has been great for us. Their local SEO expertise has significantly improved our visibility in Ilford. We’ve seen more shisha enthusiasts finding us online, and our website traffic has noticeably increased. Highly recommend their SEO & Web Design services!
Amer A
RHS Heating Ltd owes much of its recent success to Cranberry Marketing. They designed a professional website for us and continue to handle our local SEO. We’re getting more inquiries than ever before, and the site has been a great tool for showcasing our services. Couldn’t be happier!
Tahir Mehmmod
Amazing Service from Cranberry marketing. They helped my company to design and build our website and they also pushed SEO marketing. The service from Faraz and his team was 5 Star and i would suggest anyone in doubt to use them. Prices also very fair! Thank you and i will be in touch for further web development projects.
Sean K
I was looking for an SEO agency in Watford and I'm so glad I found Cranberry Marketing. We signed up for their SEO services, and they built our website. It's better than we ever imagined. The team is friendly, knowledgeable, and really knows their stuff. Within just two months we’ve seen an increase in leads and views. We're really happy with their work. I highly recommend Cranberry Marketing to anyone who wants to boost their digital marketing.
Arkley Scaffolding
OUR CLIENTS
Brands that trust Cranberry to drive their growth.
FAQs
Schema markup questions our clients ask.
The fifteen questions Hertfordshire businesses ask most when they realise plugin-generated schema isn’t enough. Don’t see yours? Just ask.
Still have questions? Book a call →
What is schema markup?
Schema markup is structured code — almost always written in JSON-LD format — that you add to a website’s HTML to explicitly tell search engines and AI engines what the page’s content represents. It uses the standardised vocabulary at Schema.org, originally launched in 2011 by Google, Microsoft, Yahoo, and Yandex. With schema, you label content as an Organization, Article, Product, FAQPage, Person, LocalBusiness, or one of hundreds of other types — and search engines no longer have to guess what your page is about.
What is the difference between schema markup and structured data?
The two terms are used interchangeably in practice. Structured data is the broader concept — any data organised in a predictable, machine-readable format. Schema markup specifically refers to structured data that uses the Schema.org vocabulary. When SEOs and AI search engineers say “add schema” or “add structured data” to a page, they almost always mean the same thing: implement Schema.org JSON-LD.
What is JSON-LD and why do you use it?
JSON-LD (JavaScript Object Notation for Linked Data) is the format Google explicitly recommends for schema markup. It lives in a single <script type="application/ld+json"> tag in your page head — separate from your HTML, easy to maintain, and clean for AI systems to parse. The two older formats (Microdata and RDFa) clutter your HTML attributes and are rarely used for new implementations in 2026. Cranberry uses JSON-LD exclusively.
Is schema markup a Google ranking factor?
Google has confirmed schema is not a direct ranking factor. But that misses the point. Schema drives rich-result eligibility (which gets 58% of clicks per Sistrix), Knowledge Graph entity recognition, AI Overview citations, and ChatGPT/Perplexity/Claude citation rate. The effect on visibility and traffic is significant — pages with proper structured data are cited up to 3× more often in AI-generated results than equivalent unstructured pages. The label “ranking factor” is a 2018 frame; in 2026 schema is best understood as the API between your site and every search system that reads it.
Why is plugin-generated schema not enough?
SEO plugins like Yoast, Rank Math, and Schema Pro generate generic schema that covers the basics — Organization, WebPage, Article — and stops there. They almost never include the entity properties that AI search engines actually use: sameAs arrays linking to LinkedIn, Wikidata, Crunchbase, and Companies House; knowsAbout for topical authority; @id graph references connecting Organization to WebSite to WebPage to Article to Person. Plugins also produce identical boilerplate across every page, fail silently when content updates, and rarely declare Person schema for authors — which kills the E-E-A-T signals AI engines explicitly check.
Which schema types matter most for AI search?
Five schema types cover roughly 80% of AI-search citation lift: (1) Organization with full sameAs array — the entity anchor; (2) FAQPage — the format AI engines extract most directly; (3) Person — for authors and key team members, drives E-E-A-T; (4) Article or BlogPosting with datePublished and dateModified — the freshness signal; (5) Product, Service, or LocalBusiness — depending on your business model. After those, BreadcrumbList, HowTo, and VideoObject add meaningful incremental impact.
What is the sameAs property and why does it matter so much?
The sameAs property is an array of URLs you add to your Organization or Person schema, each pointing to an authoritative external profile of the same entity — your LinkedIn page, your Wikidata entry, your Crunchbase profile, your Companies House listing, your verified social profiles. Google uses sameAs to cross-reference and verify entity identity in the Knowledge Graph. AI engines use the same logic. The more sameAs identifiers you provide — and the more those sources agree on your details — the higher your entity confidence score. It is the single highest-leverage under-used schema element in 2026.
Does schema markup help with ChatGPT, Gemini, and Perplexity citations?
Yes — significantly. ChatGPT (when browsing), Perplexity, Claude, and Google AI Overviews all parse JSON-LD when evaluating which sources to cite. Pages with well-formed Organization, Article, FAQPage, and Person schema are cited at meaningfully higher rates than equivalent unstructured pages. Schema reduces ambiguity, lets AI confidently extract facts cleanly, and provides the entity verification AI engines need before they’ll quote you. Run our free AI Visibility Tool to see how schema gaps are affecting your AI citation rate right now.
How much does a schema markup implementation cost?
From £750 for a one-off implementation on a small business site (5-10 page templates, Organization + key page types). Mid-sized engagements typically run £1,500-£3,500 depending on site size, the number of templates needing schema, and whether industry-specific types (MedicalWebPage, LegalService, FinancialService) are required. Large eCommerce or multi-location implementations run £3,500+ with quarterly monitoring. The free AI Visibility Tool is £0 and shows you exactly what’s missing before you spend a penny.
How long does schema implementation take?
Typically 2-4 weeks from kickoff to live. Week 1: full schema audit and entity modelling. Week 2: hand-coded JSON-LD templates per page type. Week 3: validation against Rich Results Test and Schema Markup Validator on staging. Week 4: deployment, Search Console verification, and documentation handover. Larger sites or implementations involving custom CMS work can extend to 4-6 weeks. We commit to deadlines — if we miss, we keep working at no extra cost until it ships.
Will schema markup work on WordPress, Shopify, or Webflow?
Yes — and on custom CMS too. Cranberry implements schema on whichever platform your site is built. WordPress: we add JSON-LD via the theme functions or a lightweight code snippet, working alongside Yoast or Rank Math without conflicts. Shopify: we modify the theme.liquid templates directly, with Product schema pulled dynamically from your store data. Webflow: embedded code blocks per template. Custom CMS or headless: we hand the JSON-LD templates to your dev team with documented integration points. Schema doesn’t depend on a specific stack — it’s just code in the page head.
What happens if my schema breaks after a plugin or theme update?
This is the silent killer of plugin-generated schema. WordPress core updates, Yoast updates, theme updates, and even content edits routinely break structured data — and there’s no built-in alert. Cranberry’s hand-coded implementation lives in your theme or via tag manager, so it doesn’t depend on plugin behaviour. We also set up monthly Search Console enhancement monitoring to catch any breakage early. If something breaks during the 90-day guarantee window, we fix it free.
What is entity SEO and how does schema fit in?
Entity SEO is the practice of ensuring search engines and AI systems recognise your brand as a distinct entity in their internal knowledge graphs — not just a string of keywords. Schema is the primary mechanism that makes entity SEO possible. Organization schema with a complete sameAs array tells Google’s Knowledge Graph who you are. Person schema with sameAs and knowsAbout tells AI which authors are trusted experts. @id references connect entities across pages. Without schema, entity SEO is guesswork. With it, AI systems can confidently traverse your site as a structured graph.
Why are my rich results not showing in Google Search?
Three common reasons. (1) Validation failures: a syntax error or missing required property invalidates the entire block — check Google’s Rich Results Test. (2) Content-schema mismatch: Google’s March 2026 update tightened the rule that schema must match visible page content. Marking up content users can’t see causes Google to ignore the schema (and can trigger manual actions). (3) Eligibility tightened: Google removed FAQ rich results for most domains and HowTo for non-experts in 2024 — but the underlying schema is still used internally for AI Overviews and Knowledge Graph signals. The schema is still valuable; the visible rich result is just gone for those types.
What's the first step?
Run our free AI Visibility & Schema Audit Tool first — branded report into your inbox in 60 seconds, identifying which schema types are present, which are missing, which are broken, and which entity properties (sameAs, knowsAbout) need attention. No contact details required to start. If the results show meaningful gaps and you’d like a hand-coded implementation, book a 30-minute discovery call with founder Faraz to scope the work. We respond within 1 business day.
EXPLORE MORE
What pairs with schema markup.
Four services most clients combine with hand-coded schema for a complete AI-search programme.
Run an instant audit. See which schema types you have, which you’re missing, and which are broken. 60 seconds. Branded report.
Schema is the technical foundation. GEO strategy is the documented plan. Get the 30/60/90-day roadmap your dev team can execute against.
Schema plus content plus entity work plus digital PR — the full retainer that turns AI visibility into AI traffic and pipeline.
Crawlability, Core Web Vitals, render-blocking JS, sitemap hygiene. The foundation schema sits on top of — fixed during the same engagement.
Get your schema right. Become AI-citable.
Run the free schema and AI Visibility audit to see exactly where your structured data is falling short. Or book a discovery call with founder Faraz to scope a hand-coded JSON-LD implementation across your site — usually live within 2-4 weeks.
60 seconds. Branded report. No sales call required.