SEO for retail businesses: How to get recommendations on ChatGPT and Google AI Shopping

   In 2026, e-commerce is changing radically change the way customers find and buy products online.. It's no longer enough to rank well in Google: conversational AI assistants such as ChatGPT and Google Gemini are changing the rules of the game.

   Instead of keyword searches, users are doing natural questions, and these systems not only suggest products, but can even create shopping carts and complete payment within the chat itself.

   For big brands and retailers, this means that visibility no longer depends on traditional SEO alone. The crucial thing now is to be listed and recommended by these generative engines, because the “shop” interface of the future is the conversation itself.

  When discovery, comparison and payment of products can be carried out within ChatGPT o Gemini, The customer journey no longer behaves as a flow of clicks, but as a flow of inference: a sequence of questions, constraints, shortlists and wizard-mediated decisions.

   The result is a realignment of measurement: attribution models that assume “session → product page → payment”.” shall not be valid.

What is Generative Retail Optimisation (GEO)?

   The Generative Optimisation (GEO) is to prepare your catalogue, product pages and branding data in such a way that it will AI models can find, interpret and recommend them with confidence. when users submit queries.

   It's not just about using keywords, it's about making sure that the content of your shop:

Sea understandable and reliable for AI assistants

• Clear and consistent product information (SKU, price, availability, sizes, returns, etc.).

• Structured data (schema) that serve as a “summary” for the algorithms.

• Content explaining why a product is the best choice (pros/cons, use cases, comparisons).

Have evidence of practical value

   AI assistants work best with content that contains verifiable evidence, not just basic descriptions. This includes:

• Detailed specification sheets.

• Compatibility matrices or guides (e.g. sizes or accessories).

• Well-structured user opinions that act as case studies.

From “Ranking” to “AI Shelf Space”.”

 Before: Classic SEO

   It sought to ranking as high as possible in Google for certain keywords, to get clicks and then convince the user on the website.

 Now: GEO for AI

What is important is be part of the AI response, including before the user visits your website. This means:

Instead of “appearing first on Google”, the aim is to that the wizard includes your product in the list of recommendations. when a customer raises a problem or need.

How to prepare your business for the future of conversational shopping

1️⃣ Optimise your catalogue with quality data

At large retailers, inconsistencies between feeds, APIs and product pages can block the ability of retailers to IA to recommend. That is why it is convenient:

• Homogenise key attributes by category.

• Ensure that the product feed is accurate, up-to-date and conflict-free.

• Implement structured Product + Offer brands to make the data easy to read.

2️⃣ Gives clear reasons to buy

   AI assistants are more successful in recommending products when they are able to justify a choice. It therefore includes:

• Lists of pros and cons.

• Alternatives and comparable products.

• Use cases and testimonies that respond to specific questions.

3️⃣ Change your success metrics

When checkout can occur inside the chat, clicks are no longer the best metric. Instead, measure:

• Recommendation ratehow often your products appear in responses.

• Inclusion rate: percentage of prompts where you are at least mentioned.

• AI Share of Shelfyour participation against competitors in the AI suggestions.

    What this means for marketing teams.

  Eligibility for recommendations becomes conditional. It is not only optimised for being the “best”, but also for to be the best option in various micro-contexts (budget, location, urgency, compatibility, previous behaviour).

The role of personalisation

   Personalisation is pushing this change even further. Assistants can tailor recommendations according to:

• Purchase history.

• User preferences.

• Specific context of the prompt.

   This favours to those who have their own quality and well-structured data, as large retailers with connected user and transaction histories.

Conclusion: SEO is still alive... but it is evolving.

    Generative Optimisation does not completely replace traditional SEO, but it does does redefine what it means to appear in the new digital landscape.. Before, you wanted to be on the first page of Google. Now, you need to be present within the AI responses.

    Investing in GEO means preparing your data, improving the way your products respond to real questions and get great conversational assistants to trust your brand and recommend it to others..