Shoppers are asking AI to recommend stores and products. Most Shopify stores are completely invisible. Find out where yours stands — free, in 60 seconds.
Run your free Shopify AI audit →Shoppers increasingly begin their buying journey not with a Google search, but with a conversational question to an AI. They're asking ChatGPT and Perplexity things like:
These queries represent shoppers who have already decided to buy. They're not browsing for inspiration — they want a recommendation so they can click through and purchase. When AI answers these questions, it names specific stores or products. If your Shopify store isn't among them, those shoppers will go to whoever is.
The Shopify default problem: Most Shopify themes include minimal, often incomplete structured data. Shopify handles basic Product schema, but critical AI visibility signals — brand entity schema, aggregateRating, detailed product attributes, and an llms.txt file — are almost never present out of the box. Your competitors' stores are just as invisible. The first to fix this wins.
The good news is that fixing AI visibility for a Shopify store is very achievable, often without expensive developer time. The signals AI engines need are knowable, implementable, and most of your competitors haven't started yet.
Shopify's default theme schema outputs basic Product markup, but it typically omits fields that AI engines rely on heavily: aggregateRating from your review platform, brand as a structured entity, detailed offers with currency and availability, and product-specific attributes like colour, material, or size options. AI engines that can't confidently describe your product won't confidently recommend it.
Beyond individual product pages, AI engines need to understand your store as an entity. An Organization or OnlineStore schema block on your homepage — including your brand name, founding date, area served, return policy URL, and social media profiles — gives AI engines the context to recommend your store for brand-level queries ("best UK shop for X") rather than only product-level ones.
AI engines treat review volume and verified ratings as a proxy for trustworthiness. For Shopify stores, this means: importing reviews into your Product schema via your review app (Okendo, Yotpo, Judge.me, Stamped), ensuring your Trustpilot or Google Reviews profile is active and current, and ideally having some press or editorial mentions on product review sites or blogs. Stores with no verifiable external review presence are rarely cited by AI.
An llms.txt file at your store root gives AI crawlers a direct, human-written summary of your brand: what you sell, who you sell to, what makes you different, where you ship, and any trust credentials (B Corp, press coverage, awards). For e-commerce specifically, including your top product categories, your best-selling lines, and your unique selling proposition in llms.txt dramatically improves the likelihood of being cited in product-category queries.
Ensure your robots.txt isn't inadvertently blocking AI crawlers. Check that your Shopify store's sitemap is accessible and up to date. Trust badges, security certificates, and clear returns/shipping policies — when present in structured or accessible form — also function as authority signals for e-commerce AI recommendations.
Add a custom JSON-LD snippet to your Shopify theme's product.liquid or theme.liquid file that enriches the default Product schema. Include aggregateRating pulled from your review app's data, a brand property with its own Organization subtype, and complete offers details. Alternatively, use a structured data app like Schema Plus or JSON-LD for SEO to manage this without touching code.
In your Shopify theme's theme.liquid file (inside the <head> tag), add a JSON-LD block with @type: "Organization" or "OnlineStore" including your brand name, URL, logo, social profiles, founding date, areas served, and return policy URL. This entity-level schema is the missing piece that allows AI to recommend your store for brand-level queries.
Set up automated post-purchase review request emails (via Klaviyo, Shopify Email, or your review app). Aim for at least 50 verified reviews before expecting AI visibility. If you're below that threshold, run a proactive review collection campaign with your existing customers. The content of reviews matters too — encourage customers to mention the specific product type and use case in their feedback.
Upload a plain-text file to your Shopify store root (via Settings → Files, then reference it in your theme, or use a Shopify app to serve static files). Include: your brand name, what you sell, who you sell to, where you ship, your top product categories, your price range, what makes you different, any press or awards, and your returns policy summary. Keep it under 500 words and write it for a language model, not a human reader.
AI engines often surface category-level recommendations ("best UK shop for X") rather than individual products. Create collection pages that include a substantial editorial introduction (200+ words) describing what makes your selection unique, who it's for, and what distinguishes your curation. Add Collection or ItemList schema to these pages. This dramatically improves your visibility for category-level AI queries.
GetVisus audits your Shopify store's AI visibility across structured data, entity signals, reviews, and crawlability — then gives you a prioritised fix list. Free, no sign-up required.
Run your free Shopify AI audit →