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Microsoft published a playbook early this month to help retailers increase visibility in AI search, browsers, and assistants.
“A guide to AEO and GEO” (PDF) from the heads of Microsoft Shopping and Copilot, and Microsoft Advertising, includes and confirms actionable tips worth the read.
Microsoft’s new guide aims to help retailers increase AI visibility.
GEO vs. AEO
The rise of AI platforms has created a proliferation of ill-defined acronyms. The guide attempts to clarify two of them:
- GEO. Generative engine optimization. “Optimizes content for generative AI search environments (like LLM-powered engines) to make it discoverable, trustworthy, and authoritative.”
- AEO. Answer/Agentic Engine Optimization. “Optimizes content for AI agents and assistants (like Copilot or ChatGPT) so they can find, understand, and present answers effectively.”
I question the need for new acronyms, as the concepts have existed for years in traditional search engine optimization. “GEO” is synonymous with “EEAT” — Experience, Expertise, Authoritativeness, Trustworthiness — Google’s term for instructing human quality raters.
“AEO” is akin to optimizing for featured snippets in traditional search results.
The key difference is that GEO and AEO focus on a product’s pre-training data to impact exposure in AI answers.
And GEO extends beyond a site’s content to include external resources such as reviews, Reddit mentions, product-comparison articles, and similar.
Intent-driven product data
To me, the most useful part of the guide reinforces my article on optimizing product feeds for AI. Product feeds and on-page descriptions should clearly address use cases, such as shoes “best for day hikes above 40 degrees.”
The guide also recommends:
- Product page titles that are detailed and descriptive,
- Front-loading product descriptions with benefits: who it’s for, the problem it solves, and how it’s better,
- Q&As,
- Comparison tables,
- Detailed alt text for product images,
- Complementary products that match the intent,
- Transcripts for videos.
Social proof
The guide emphasizes the importance of factual entities such as verified customer reviews, certifications, sustainability badges, and partnerships. It warns against using exaggerated or unverifiable claims, stating, “AI systems penalize low-trust language.”
It advises applying social proof consistently across your site and all channels, and verifying any subjective claims about your business or product. For example, if you assert a product is the best in a category, include why, such as “according to [XYZ’s] tests.”
Structured data
Per the guide, structured data markup, such as Schema.org, is key for AI visibility.
However, I’ve seen no evidence to support that recommendation. The guide does not explain how LLMs use Schema. To my knowledge, AI training data does not store Schema markup, and AI bots crawl text-only content.
Yet for live searches, Schema may be helpful because traditional search engines support it, and LLMs rely on those platforms.
Nonetheless, the guide recommends:
- Schema Types: Product, Offer, AggregateRating, Review, Brand, ItemList, and FAQ.
- Dynamic fields: price, availability, color, size, SKU, GTIN, and dateModified.
- ItemList markup for collections and category pages to clarify product groupings.
While helpful, Microsoft’s “A guide to AEO and GEO” doesn’t introduce anything new. The recommendations align with longstanding SEO tactics and reinforce the views of industry pros.