Schema Markup & Structured Data
Schema Markup Services
Hand-built structured data that earns rich results and gets read by AI search.
Most schema markup services start and end with a plugin. Mine start with your revenue pages: product, review, and organization markup written by hand, validated against what is on the page, and wired into your templates so it keeps working after every redesign. That is the difference between markup that merely exists and markup that earns review stars, price snippets, and citations in AI answers.
Why hand-built schema markup services beat plugin output
Schema plugins emit the same generic markup on every page. They guess at fields, duplicate blocks your theme already outputs, and routinely claim things the page does not say: a rating with no visible reviews, a price that disagrees with the product template, an FAQ block with no matching questions anywhere on the page. Google cross-checks structured data against visible content, and when the two conflict the result is predictable. No rich results. In the worst cases, a manual action for spammy structured markup.
I build schema by hand against the rendered page. Every property corresponds to something a user can see. Every required and recommended field for the target rich result is accounted for. Conflicting markup from themes, plugins, and apps is stripped out rather than layered over. The outcome is real eligibility: review stars, product snippets with price and availability, FAQ and breadcrumb enhancements, and merchant listing results that reflect your actual catalog.
A structured data consultant, not another plugin license
This is consulting work, not software. I audit everything your stack currently emits, map the entity model behind your business, then build markup at the template level on WordPress and Shopify so it applies across the entire catalog and survives theme updates, template changes, and content edits. When a release quietly breaks markup, your Search Console enhancement reports flag it and I fix it before rankings feel the damage. I have spent years doing this for ecommerce catalogs and enterprise sites where a broken Offer field means lost revenue, not just a validator warning.
The same discipline now matters well beyond Google. AI search systems lean on structured data to understand who you are, what you sell, and whether you are worth citing. Clean entity markup, consistent organization data, and product markup that agrees with your pages are quickly becoming the difference between being quoted in an AI answer and being invisible in one.
What the work includes
Every project is scoped to your platform, your catalog, and the rich results your pages can realistically win. Most include the following.
Structured data audit
A full inventory of what your theme, plugins, and apps currently emit, where markup conflicts with page content, and which rich results you are leaving on the table.
Product and review markup
Hand-built Product, Offer, and Review structured data built for merchant listings, review stars, and accurate price and availability snippets.
Organization and entity markup
Organization, brand, and person markup that consolidates your entity so search engines and AI systems know exactly who you are.
Template-level engineering
Schema wired into WordPress and Shopify templates and data layers so markup scales across the catalog and survives redesigns.
AI search readability
Structured data and content formatting tuned for the crawlers behind ChatGPT, Perplexity, and Google AI Overviews. GEO and AEO, grounded in markup.
Monitoring and recovery
Search Console enhancement tracking, regression checks after releases, and diagnosis and recovery when rich results disappear.
How the work runs, from audit to live markup
- Audit the rendered pages. I crawl what Google sees, not what your CMS thinks it publishes, and inventory every source of markup your theme, plugins, and apps emit. You get a page-by-page map of conflicts, missing fields, and the rich results each template could qualify for.
- Blueprint the entity model. One document defines your Organization, brands, products, and people, how they connect, and the exact properties each template needs. This becomes the spec your developers and I build against.
- Build and validate before launch. JSON-LD is written at the template level, tested in Google’s Rich Results Test and the Schema Markup Validator on staging, and only then deployed, with recrawl requests filed for priority pages.
- Monitor and defend. I check Search Console enhancement reports after every release, so a template change that silently drops markup gets caught early instead of after rankings slide.
CASE STUDIES
Results from real engagements
Hiring a schema markup consultant: common questions
We already use Yoast or Rank Math. Is that not enough?
Those plugins output competent baseline markup: website, article, breadcrumbs. They cannot know your business. They will not model your product variants, your review pipeline, or how your entities connect, and they frequently collide with markup your theme or other apps also emit. I regularly audit sites where the theme, an SEO plugin, and a page builder each output their own version of the same schema, and Google trusts none of them. Baseline plugins are a starting point. Rich results at scale come from markup that matches your actual pages.
How fast will we see rich results?
The honest answer: eligibility begins as soon as valid markup is live and recrawled, but Google decides when and whether to display rich results, and no consultant can guarantee them. What I control is everything on your side of that decision: valid, complete, conflict-free markup that matches on-page content and meets every documented requirement. I track eligibility and impressions in Search Console so you can see exactly what is qualifying and what is displaying, page by page.
What does this cost?
It depends on platform, template complexity, and catalog size, so I do not quote blind. Most work starts with a fixed-scope structured data audit that produces the complete build plan, priced on its own. You then know exactly what the full build involves before committing to it, and you own the audit findings either way. Ongoing monitoring is available as a retainer once the build is live.
Do you work on WordPress and Shopify?
Yes, both, at a deep level, plus custom and headless stacks. On WordPress I work at the theme and template layer rather than stacking plugins. On Shopify I build markup into Liquid templates and metafields so it holds across the whole catalog. Headless and custom builds get JSON-LD built directly into the rendering layer.
What does schema have to do with AI search visibility?
Structured data is one of the clearest signals AI systems have about who you are and what your pages claim. Clean entity and product markup makes your content easier to parse, attribute, and cite. It is not the whole GEO picture, since content structure and authority matter too, but it is the layer most sites get wrong and the one I make sure is right.
Is this a one-time project or part of a retainer?
Both models work. A focused project covers the audit, the build, deployment, and validation. Most clients keep me on retainer because schema is not static: templates change, catalogs grow, Google revises its requirements, and AI crawlers keep evolving. Ongoing work means your markup keeps pace instead of quietly rotting after the next redesign.