AI Search Visibility
Schema Markup
Schema architecture designed for Google rich results and citation in ChatGPT, Perplexity, Claude, and Google AI Overviews. Validated implementations, written documentation, measurable outcomes.
Deliverables
Schema audit document
Full current-state review, gap analysis, and prioritised recommendations.
Entity graph architecture
A coherent design for how your organisation, content, products, and people connect through schema.
JSON-LD implementations
Production-ready markup, validated against Schema.org, written to fit your stack.
Citation tracking setup
Baseline measurement and ongoing tracking for AI Search citations across ChatGPT, Perplexity, Claude, and Google AI Overviews.
Written documentation
Handover docs your team can maintain after the engagement closes. No black boxes.
Post-launch validation
Schema validation report and rich results testing after deployment. Everything verified before sign-off.
Process
Discovery call
Thirty minutes. We walk through your stack, your content types, your goals, and your current schema state. By the end I know what scope makes sense.
Audit
Two to three weeks. Full review of existing schema, validation errors, entity graph gaps, and AI Search citation visibility. Output is a documented report with prioritised recommendations.
Architecture design
Designing the entity graph and JSON-LD structure for your site. I sketch the relationships between Organization, Person, Product, Article, FAQ, and whatever else applies to your content.
Implementation
Writing the JSON-LD, validating it, and either deploying it myself or handing it to your engineering team with deployment instructions.
Validation and handover
Post-deployment validation, rich results testing, citation tracking baseline, and a documented handover. Your team can run with it from there.
Packages
Schema Audit
From £1,500
Find the gaps before fixing them
2 to 3 weeks
- Full review of current schema implementation
- Validation error report with priorities
- Entity graph gap analysis
- AI Search citation baseline measurement
- Written recommendations with implementation effort estimates
Schema Implementation
From £4,500
Audit + architecture + deployed schema
4 to 6 weeks
- Everything in the audit package
- Entity graph architecture design
- JSON-LD code written and validated
- Deployment (myself or alongside your team)
- Post-launch validation and rich results testing
- Handover documentation
Ongoing Maintenance
From £800/month
Schema that stays current as you scale
Quarterly cadence
- Quarterly schema reviews and updates
- Schema design for new content types and pages
- AI Search citation monitoring and reporting
- Validation checks after major site changes
- Direct Slack or email access for schema questions
Case Studies
Halewood Editorial
Schema migration for AI Search citation
Editorial site had basic Article schema and was invisible to AI Search citation. Designed the richer Article + Author + Organization entity graph with explicit sameAs links to Wikipedia, LinkedIn, and authoritative sources. Added citation-friendly markup on long-form pieces.
Outcome: Citation appearances in ChatGPT and Perplexity went from rare to weekly within the tracking window.
Cendric
Product and Organization schema design
B2B SaaS needed Product, Organization, and SoftwareApplication schema designed and shipped for their pricing pages and feature pages. Built the entity graph linking products to organisation to FAQ structures.
Outcome: Pricing page rich results restored. Citation appearances tripled in three months.
Aldernode
Product schema with entity work
E-commerce brand had Product schema set up by a Yoast plugin but missing key fields and lacking the Brand and Offer structures that AI Search engines actually use. Built proper Product + Brand + Organization graph with explicit attributes for all 1,200 SKUs.
Outcome: Rich result eligibility across the catalogue, AI citation tracking showing weekly mentions across product categories.
FAQs
How long does a typical schema engagement take?
Audit-only: two to three weeks. Full implementation: four to six weeks for most sites, eight to twelve weeks for enterprise scale. Ongoing maintenance runs on a quarterly cadence with monthly check-ins.
Will this work with my CMS?
Yes. I work with WordPress, headless setups, custom builds, and most CMS platforms. JSON-LD is platform-agnostic. What changes is where it lives in your codebase. I handle that during discovery.
Do I need to give you developer access?
For audit-only engagements, no. For implementation work, either developer access or a developer counterpart on your side. I write the JSON-LD; someone needs to deploy it. We agree the workflow during discovery.
What if my current schema is a mess?
Expected for most clients. The audit identifies what stays, what gets fixed, what gets removed. The implementation engagement includes refactoring as needed at no extra charge.
How do you measure success?
Three layers. First, "validation": schema validates against Schema.org with no errors. Second, rich results: visible Google rich result eligibility where appropriate. Third, "citation": tracked appearances in ChatGPT, Perplexity, Claude, and Google AI Overviews. All three reported in the final deliverable.
Do you guarantee specific outcomes?
No. Anyone guaranteeing specific Google or AI Search outcomes is selling something. What I guarantee is the work itself: validated schema, clear documentation, audit reports you can point at. The outcomes depend on factors outside any consultant’s control like content quality, domain authority, competitive landscape.
Do I keep the documentation and code?
Yes. Everything I deliver is yours: JSON-LD code, audit documents, architecture diagrams, deployment instructions. Your team can run with it after the engagement closes.
Can you train my team?
Yes, if that fits the scope. Most engagements include at least a handover session. Some clients want deeper training so the team can maintain and extend the schema themselves. We scope this during discovery.