Prepare Your Brand for Agentic Commerce, the Future of AI-Powered Shopping

Agentic commerce refers to shopping experiences where AI-powered agents can help users discover, compare and evaluate products based on their needs. For ecommerce brands, this makes clear product information, structured data and accurate catalogue content increasingly important.

Shopify stores can prepare for agentic commerce by improving product data, attributes, structured data, feeds, category information and supporting content. This helps external AI systems better understand what products are available and how they relate to shopper queries.

An agentic commerce readiness audit reviews areas such as product catalogue structure, product attributes, schema markup, identifiers, content completeness, taxonomy and data consistency. The goal is to identify gaps that may make products harder for AI systems to understand.

Structured product data gives machines clearer information about products, variants, prices, availability, attributes and other details. Well-organised data can make it easier for search engines, shopping platforms and AI systems to interpret ecommerce catalogue information.

Important information can include product names, descriptions, categories, variants, materials, dimensions, sizing, compatibility, identifiers, availability, images, shipping information and other verified product attributes that help explain what a product is and who it is suitable for.

Generative Engine Optimisation focuses on making website and product information easier for AI-powered discovery systems to understand. This can include clearer product content, useful FAQs, structured information, category context and content that answers natural-language shopping questions.

Not necessarily. Many improvements can be made within an existing Shopify or Shopify Plus store by reviewing catalogue data, structured data, feeds, product content and technical implementation. The required work depends on the current store setup and identified data gaps.

Improving product data and machine-readable information can help AI systems better understand a store and its products, but it does not guarantee inclusion or visibility in any specific AI platform such as ChatGPT, Google Gemini or Microsoft Copilot.

Product feeds and schema markup provide structured information about ecommerce products. Accurate feeds, relevant schema and consistent catalogue data can help external systems interpret product details, pricing, availability, variants and other important attributes.

Periodic reviews can be useful because AI shopping platforms, ecommerce technologies and product-data requirements continue to change. Ongoing work may include reviewing catalogue quality, updating structured data, checking feeds, improving content and addressing newly identified data gaps.