BigCommerce B2B SEO Agency

BigCommerce B2B Edition layers buyer-portal functionality (company hierarchies, customer groups, price lists, quote workflows, requisition lists, sales rep impersonation, draft orders) on top of standard BigCommerce. SEO has to span two surfaces: (1) the public-facing catalog and content that ranks in Google and AI engines and (2) the authenticated buyer portal that doesn't. We architect the indexable / gated boundary, structure marketing-surface SEO around B2B buyer intent, and emit appropriate meta-robots per route so anonymous Googlebot sees public catalog only.

Yes — 1Digital® Agency is a BigCommerce Elite Partner (the top partner tier) and BigDev Certified, with continuous BigCommerce work since 2012. We've shipped B2B Edition rollouts, customer-group-driven catalog SEO, quote workflows, and multi-storefront B2B configurations across distributors, manufacturers, and wholesale brands. Trusted by 400+ brands with a 4.9/5 rating across 941+ verified reviews.

Customer groups in B2B Edition gate price visibility, catalog access, and shipping options per company segment. SEO consequences: (1) per-group prices must not bleed into anonymous Product schema — the public Product / Offer schema reflects either MSRP or a representative price, never a customer-group-specific price; (2) gated SKUs (visible only to specific groups) carry noindex per route via Stencil template logic or Catalyst metadata; (3) public categories with mixed gated/public products list public products only to anonymous crawlers. We use BigCommerce's customer-group context APIs to emit conditional schema and meta-robots per request.

Price lists assign per-customer-group or per-company pricing. For SEO, the rule is that JSON-LD Offer.price must always be the publicly visible price — never an authenticated-only price list. Two patterns: (1) emit Offer schema with the public catalog price; price-list discounts appear only in authenticated UI and are absent from indexable HTML; (2) for catalogs where MSRP is the public price and all real pricing is gated, emit Offer with priceSpecification noting the price is "subject to authentication" so the schema accurately represents the public-facing price model. We default to pattern (1) and only use (2) for genuinely MSRP-only catalogs.

Quote-only products (no add-to-cart, "Request a Quote" CTA) are common in B2B for high-ticket, custom-spec, or regulated SKUs. SEO patterns: (1) emit Product schema without Offer.price; instead use Offer.priceSpecification with "QuoteOnly" semantics or omit Offer entirely; (2) page content focuses on buyer-intent specs (capacities, dimensions, certifications, compliance) and links to quote-form CTA; (3) FAQ schema covers "what's the lead time", "what's the MOQ", "do you ship to my country" — the questions buyers actually ask. We've ranked quote-only PDPs against catalog-priced competitors by leaning into spec depth and intent-matched content.

BigCommerce Multi-Storefront lets one BigCommerce account run multiple storefronts on different domains, sharing or splitting catalogs. For B2B, the common patterns are: (1) one storefront per brand or region with shared catalog; (2) one DTC storefront + one B2B storefront from the same catalog; (3) per-distributor storefronts under one parent brand. SEO topology: hreflang where storefronts serve different regions, canonical pinning to prevent cross-store cannibalization when content is identical, and per-storefront sitemap with appropriate robots policies. We architect the canonical-and-hreflang topology per Multi-Storefront configuration.

B2B catalogs typically have deeper specs than DTC (voltage, gauge, certifications, compliance, material grade). Faceted nav generates more parameter combinations, and most should not be indexed. Pattern: canonical-pin filter URLs to the base category; selectively promote high-intent combinations (e.g. "stainless-steel + food-grade + 304-series") to indexable landing pages with their own meta, content, breadcrumb schema, and an in-page H1 that matches the filter. Customer-group-aware filters add complexity — visible facets change per group, so canonical strategy must respect group context.

Both. Stencil (Cornerstone + Handlebars) is the classic templated stack; Catalyst is the Next.js + React headless stack. Stencil B2B SEO covers handlebars template logic for customer-group-aware rendering, Page Builder section schema, and Big Open Data Layer (BODL) instrumentation. Catalyst B2B SEO covers Next.js metadata, GraphQL Storefront API caching, RSC vs client component boundaries for gated content, and Makeswift-driven content schema. We ship on both stacks.

Company hierarchies (parent company → subsidiaries → branches → users) are an authenticated-only surface in BigCommerce B2B — Google doesn't see them, by design. SEO impact is indirect: the marketing surface must convert top-of-funnel buyer intent into a "Request Access" or "Apply for Account" CTA that leads to the gated hierarchy. We build the public-side content engine — landing pages by industry vertical, by spec, by region — and tune the gated portal for buyer experience without indexation.

Phase 1: indexable/gated boundary audit, customer-group-aware schema review, price-list and Offer schema sanity check, quote-only PDP indexation review, Multi-Storefront topology, faceted-nav indexation, BODL data layer health, Core Web Vitals on Stencil or Catalyst. Phase 2: corrective work — meta-robots per route, canonical pinning, schema rebuild, faceted-nav rules, landing-page promotion for buyer-intent filter combinations. Phase 3: buyer-intent keyword mapping, content briefs (industry, spec, compliance angles), AI-engine optimization with llms.txt, and citation tracking across ChatGPT Shopping, Perplexity Shop, Google AI Overviews, Gemini, Microsoft Copilot.