SEO for B2B ecommerce platforms, wholesale distributors, marketplaces, and industrial catalogs. Built for large SKU libraries, procurement-driven buyers, and the AI search tools purchasing teams now use to research products and suppliers.
B2B ecommerce is fundamentally different from retail. Procurement teams and engineers search by part number, brand, cross-reference, and application. They want spec data, compatibility information, and pricing structures that fit how they buy. Catalog depth, faceted navigation, and technical product content carry the rankings, not the glossy retail copy most platforms ship with.
The technical side compounds the problem. Catalogs with tens of thousands of SKUs, faceted navigation that explodes the URL surface, and Product schema that ships blank or incomplete. Add the LLM answer layer, where ChatGPT and Perplexity now pull product recommendations from structured catalogs and brand mentions, and most B2B wholesalers are invisible in both surfaces.
Amazon Business, Alibaba, and vertical marketplaces frequently outrank B2B catalogs for the part-number and product-family queries that should be your highest-intent traffic. Margin you built the product for flows to a marketplace that took none of the development risk.
Coupa, SAP Ariba, and enterprise procurement platforms route buyers through pre-curated supplier lists. Brands not integrated and not ranking for the product queries those buyers run outside the platform get squeezed out of the evaluation entirely.
A buyer searching a specific SKU, application, or spec combination is ready to request a quote right now. Sites that do not index the long tail cleanly watch that demand flow to distributors, marketplaces, or competitors that bothered to structure their catalogs.
LLMs recommending suppliers lean on brand mentions in trade press and industrial forums, not catalog pages. Wholesalers that publish thousands of SKUs but never earn mentions outside their own site stay invisible in AI-driven recommendations.
Product taxonomy, faceted navigation, and URL structure that lets thousands or tens of thousands of SKUs index cleanly. Category hubs, brand pages, and application pages built so every high-intent query has a landing page with real content behind it.
Crawl budget work on large catalogs, Product and Offer schema across the SKU library, pagination and canonical handling, and site speed on JavaScript-heavy ecommerce platforms. Migrations and replatforms handled so organic traffic does not drop during the switch.
Buying guides, spec comparison pages, compatibility charts, and procurement content that answer the real questions a purchasing manager runs before issuing a PO. Not blog content. Pages buyers use to decide.
Links from industry publications, manufacturer partners, and the trade sites your buyers already read. Structured data and brand signals that get your catalog surfaced in ChatGPT, Perplexity, Gemini, and Google AI Overviews when a buyer researches a product category.
Engagement includes
A B2B ecommerce platform, a traditional distributor, a vertical marketplace, and an industrial catalog all index and rank differently. Same four-pillar methodology, tuned for the structure and buyer pattern of each channel.
Shopify Plus, BigCommerce, Magento, and custom stacks. Faceted navigation, canonical handling, and Product schema are what most sites get wrong. Procurement-oriented buying guides fill the long tail.
Compete on breadth, availability, and regional coverage. Location pages, brand hubs, and cross-reference content move revenue. Most distributor sites have none of it.
Seller listings cannibalize each other without canonical rules, internal linking, and structured data that aggregates signal at the category level.
Spec tables, cross-reference data, and CAD datasheets converted from locked PDFs to indexable HTML. Surfaces individual SKUs for specific engineering queries.
Client result
Distribution
+47%
Organic sessions, QoQ
55
AI search citations
+72%
Search impressions, QoQ
Read the case study →
Client result
Manufacturing
17x
Organic sessions
1,800+
AI search citations
30x
Search impressions
Read the case study →
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I have worked with Jeremy and his company since 2018 and I can not say enough good things about how he operates as a business owner. His team works with us and for us to capitalize on the many different ways social media and SEO can produce more sales for my company.
John R.
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The LATT SEO team has been terrific to work with. We hired them for their SEO expertise and we have had measurable success over the last few years with hard work and focus in both SEO and various digital marketing efforts. Where many agencies fail is in the execution, but that is not the case with this team.
Kathy S.
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Jeremy is an SEO subject matter expert who delivered a quick and comprehensive analysis that surpassed our expectations. We hope we get an opportunity to work with him in the future.
Chris B.
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Excellent job. Very knowledgeable. Diagnosed the problem quickly and provided a very comprehensive plan for getting my site back to the top of Google.
Brad W.
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My consultation with Jeremy was above and beyond. I appreciated his genuine enthusiasm for my project and tactical advice.
Allison M.
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Total pro. Very efficient. Hire him.
Brian K.
Wholesale SEO is search engine optimization built for B2B ecommerce platforms, wholesale distributors, and B2B marketplaces. It focuses on the keywords, catalog architecture, and technical infrastructure needed to reach professional buyers researching products by part number, brand, application, or specification. The work differs from retail SEO because the buyer is a procurement professional, the sales cycle is longer, and the content has to carry enough technical depth that a purchaser can verify fit before requesting a quote.
B2B buyers search by part number, brand, cross-reference, and application. They want spec sheets, compatibility information, and pricing structures that match their procurement workflow. Retail SEO optimizes for browse-and-buy behavior on consumer products. Wholesale SEO has to handle large catalogs (often tens of thousands of SKUs), faceted navigation that does not implode crawl budget, and content that speaks to a purchasing manager rather than an end consumer.
Technical fixes and indexation improvements typically show measurable impact within 90 to 120 days. Category and content work builds over a longer arc, with meaningful traffic and keyword movement between months four and six. Pipeline impact (quote requests and ecommerce revenue attributable to organic search) typically materializes between six and nine months.
AI search tools like ChatGPT, Perplexity, and Google AI Overviews are increasingly used by procurement teams and engineers to find parts, cross-reference products, and shortlist suppliers. These systems pull from structured product data and brand signals across authoritative sources. Wholesalers who invest in AI search optimization now (via schema, structured catalogs, and mentions in the publications LLMs train on) capture a growing share of product research queries before competitors catch up.
One call. We ask about your catalog, your buyers, and your current SEO state. We tell you honestly whether we can move the needle.
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