Ecommerce SEO that gets your products found in AI search.

Ecommerce SEO is the work of making an online store's categories, products and supporting content discoverable in search. It combines technical foundations such as crawling, indexing and structured data with commercial decisions about which categories and products deserve visibility, and content that answers the questions buyers ask before they purchase.

A content site has dozens of pages; a store can have thousands of URLs generated by filters, variants, pagination and search. Ecommerce SEO therefore spends far more effort on architecture, index control, product data quality and template-level fixes that repeat across the whole catalogue, rather than optimising individual pages one at a time.

Yes. AI answers and overviews draw on indexed pages, structured product information and third-party references. Products are more likely to be surfaced when the entity behind the brand is clear, product attributes are complete and machine-readable, and independent sources describe the product in the same terms buyers use.

Technical and index-control fixes usually show measurable movement within the first few months because they unblock pages that already have demand. Category and product content built for new demand compounds over a longer horizon. Timelines depend on catalogue size, competition and how much of the current architecture has to change.

A crawl and render review, index coverage and canonicalisation analysis, faceted navigation and pagination handling, internal link distribution, product and category template review, structured data validation, content and demand gaps, plus a prioritised roadmap of what to fix first.

Yes. The strategy is the same, but the execution changes with the platform: template and URL constraints on Shopify, faceted navigation and crawl budget on Magento, and plugin and theme architecture on WooCommerce. Each platform has its own detailed page describing how the work is done.