Structured Data for B2B Websites

Most schema markup guidance defaults to ecommerce examples — Product, Review, Offer, the types that map cleanly onto a retail catalog. A B2B website selling software, professional services, or industrial products doesn't fit that template neatly, and the result is that B2B structured data is a genuinely underserved topic relative to how much content exists on B2C and ecommerce schema. This article covers the types that actually matter for a B2B site, in rough order of priority.

For a B2B site, Organization schema (or the more specific ProfessionalService subtype, covered in the Organization schema article in this series) is the foundational entity almost everything else references — more central here than for a typical ecommerce site, because a B2B buying decision usually involves evaluating the vendor as much as the specific product or service. A complete Organization node with a real sameAs array, founder references, and accurate description does more disambiguation work for a B2B site's core value proposition than any other single schema type.

Where an ecommerce site uses Product schema, a services business should use Service schema — covering serviceType, provider (referencing the Organization by @id), and areaServed where geographic scope matters. This is the type most B2B implementations skip entirely, defaulting instead to generic page content with no structured equivalent of "here is specifically what we sell and to whom." A services page without Service schema is leaving the same disambiguation gap a product page without Product schema would leave on an ecommerce site.

A B2B SaaS product should carry SoftwareApplication schema (or the more specific WebApplication subtype), with applicationCategory, operatingSystem where relevant, and offers for pricing tiers via nested Offer objects. This is the closest B2B equivalent to ecommerce Product schema, and it's worth implementing with the same rigor — accurate pricing, accurate feature claims, kept in sync with what the product actually does rather than a stale marketing description from launch.

B2B buying decisions lean heavily on credibility signals tied to real people — the team behind the company, named case study subjects, individual testimonials attributed to a real person and role rather than an anonymous quote. Person schema, connected by @id to the Organization and to any Article or Review content they're associated with, is where a B2B site should invest more than the generic guidance suggests, since it directly supports the E-E-A-T mechanics covered throughout this series in a context — professional services, enterprise software — where buyer trust in specific people is unusually important to the purchase decision.

B2B review volume is typically far lower than B2C — a handful of genuine client testimonials rather than hundreds of product reviews — which makes fabricated or inflated aggregateRating data both more tempting (thin real data) and more damaging if flagged (a small, checkable number of reviews is easier for anyone to audit than thousands). Only implement Review or aggregateRating schema for testimonials and reviews that are genuinely verifiable, and prefer named, attributable testimonials over anonymous quotes wherever client permission allows it — this is exactly the kind of Person-schema-backed credibility signal that compounds with the E-E-A-T value covered above.

B2B marketing leans heavily on webinars, conferences, and speaking engagements in a way B2C marketing typically doesn't, and Event schema (with startDate, location or the online-event equivalent, and organizer referencing the Organization) is correspondingly more relevant for a B2B site than for most consumer-facing businesses. This ties directly into the Person schema recommendation above where a named speaker or presenter is involved — connect the Event's performer or organizer property to the same Person @id used elsewhere on the site.

A B2B company's careers page is a genuine content asset with its own structured data type — JobPosting, covering title, description, hiringOrganization, and jobLocation. This is one of the more mechanically valuable schema types for actual rich-result eligibility (Google's job search features are broadly available, unlike the narrowed FAQ and HowTo eligibility covered elsewhere in this series), and it's frequently skipped entirely on B2B sites where the careers page is treated as an afterthought rather than real content.

Covered in more depth in the dedicated FAQ schema article in this series, but worth noting specifically for B2B: genuine procurement, integration, and security questions (data handling, compliance certifications, implementation timelines) are exactly the kind of real, non-manufactured FAQ content that's worth marking up for the retrieval-and-entity-resolution value that persists even without guaranteed rich-result eligibility.

The underlying schema.org vocabulary and JSON-LD implementation pattern don't change between B2B and B2C — the same @id and @graph connection principle covered throughout this series applies identically. What changes is which types carry the most weight and which risks matter most. A B2C ecommerce site lives or dies on Product and Review schema at high volume; a B2B site lives or dies on Organization, Person, and Service schema carrying real credibility signal at lower volume but higher individual stakes per page, since a single enterprise buying decision can be worth more than thousands of individual consumer transactions. Structured data effort on a B2B site is better spent going deep on fewer, more consequential pages — a services page, a handful of named case studies, a careers page — than replicating an ecommerce-style schema template built for volume across a catalog that doesn't exist on a B2B site the same way.

Organization or ProfessionalService schema, complete with a real sameAs array, on every page via @id reference. Service schema on every core service or product page, with an accurate serviceType and provider reference. SoftwareApplication schema on any SaaS product page, kept in sync with actual current pricing and features. Person schema for every named team member appearing in case studies, testimonials, or bylined content, connected to Organization via worksFor. Article or BlogPosting schema on all published content, following the pattern covered in the Article schema guide in this series. JobPosting schema on every open role, not just a generic careers page description. Event schema for any webinar, conference talk, or other public speaking engagement. And FAQ schema only where genuine procurement or implementation questions exist — not manufactured to fill out a template.

The same misuse patterns covered throughout this series apply with extra weight in B2B: fabricated review data, schema-only FAQ content invented to qualify for a format, and Person schema for fictional or unauthorized team members are all more damaging in a B2B context specifically because B2B buyers doing real due diligence — checking LinkedIn profiles, verifying case study claims, confirming a named team member actually exists — are more likely to catch and be put off by exactly this kind of gap between schema claims and reality than a typical consumer researching a lower-consideration purchase.