Earlier this month, Microsoft released a playbook designed to help retailers boost their visibility within AI search, browsers, and assistants. Titled "A guide to AEO and GEO" (PDF), this resource comes from the heads of Microsoft Shopping and Copilot, as well as Microsoft Advertising. It offers and confirms actionable tips well worth reviewing. Understanding GEO vs. AEO The surge of AI platforms has led to the emergence of many vague acronyms. This guide seeks to clarify two of them: - GEO (Generative Engine Optimization): Focuses on optimizing content for generative AI search environments (such as LLM-powered engines) to ensure it is discoverable, trustworthy, and authoritative. - AEO (Answer/Agentic Engine Optimization): Focuses on optimizing content for AI agents and assistants like Copilot or ChatGPT, enabling these tools to find, comprehend, and effectively present answers. Emphasis on Intent-Driven Product Data One of the guide’s most valuable sections reinforces insights from my article about optimizing product feeds specifically for AI. It stresses that product feeds and on-page descriptions should clearly target use cases—for example, describing shoes as “best for day hikes above 40 degrees. ” Additional recommendations include: - Using detailed, descriptive product page titles. - Front-loading product descriptions with benefits: specifying the intended user, the problem solved, and what makes the product superior. - Incorporating Q&As. - Providing comparison tables. - Adding detailed alt text for product images. - Suggesting complementary products aligned with user intent. - Including transcripts for videos. The Role of Social Proof The guide highlights the critical role of factual trust indicators such as verified customer reviews, certifications, sustainability badges, and partnerships.

It cautions against exaggerated or unverifiable claims, noting that “AI systems penalize low-trust language. ” It advises consistently embedding social proof across your website and all marketing channels while thoroughly verifying any subjective assertions. For instance, if claiming a product is the best in its category, specify the basis, such as “according to [XYZ’s] tests. ” The Importance of Structured Data According to the guide, structured data markup—like Schema. org—is essential for AI visibility. However, I have found no concrete evidence supporting this claim. The guide does not clarify how large language models utilize Schema markup. To my understanding, AI training data does not retain Schema, and AI bots mainly crawl text-only content. That said, structured data may help with live searches because traditional search engines recognize it, and LLMs often depend on those platforms for information. The guide’s structured data suggestions include: - Schema types: Product, Offer, AggregateRating, Review, Brand, ItemList, and FAQ. - Dynamic fields: price, availability, color, size, SKU, GTIN, and dateModified. - Using ItemList markup for collections and category pages to better define product groupings. While these points are useful, Microsoft’s "A guide to AEO and GEO" doesn’t present groundbreaking insights. Its recommendations largely align with established SEO best practices and echo the perspectives of industry experts.