Microsoft’s Advertising team released on January 15 a PDF guide called “From discovery to influence: A guide to AEO and GEO“, which offers practical data strategies to help retailers compete in AI search, AI assistants, and AI browsers.
The message is clear: we’re moving from traditional SEO, which drove clicks, to a new era focused on influence, clarity, and credibility.
Read the full document here.
Here is the essential breakdown of what you need to know from the report:
1. The Core Concepts: AEO vs. GEO
Microsoft identifies two new disciplines that determine visibility in LLM-powered ecosystems:
- Answer/Agentic Engine Optimization (AEO): Optimizing content so AI assistants (like Copilot or ChatGPT) and autonomous agents can find, understand, and present answers effectively.
- Generative Engine Optimization (GEO): Focusing on making content discoverable, trustworthy, and authoritative specifically for generative AI search environments.
2. How AI “Reasons” Through Your Data
When a user asks a question, such as “Find the best trail shoes under $150,” the AI enters a Reasoning Phase. To provide a recommendation, it synthesizes three types of data:
- Crawled Data: General brand reputation and category knowledge learned from the web.
- Product Feeds: Hard facts like real-time pricing, stock availability, and technical specs (GORE-TEX, waterproof ratings).
- Live Website Data: Real-time info an AI Agent “sees” when it visits your site, such as current promotions, delivery estimates, and detailed reviews.
3. The Crucial “AI-Readiness” Strategy
The guide outlines three actionable pillars to ensure your brand isn’t just seen, but recommended:
- Technical Foundations: Retailers must make catalogs machine-readable by deploying specific Schema types (Product, Offer, Review, FAQ) and maintaining perfect real-time synchronization between product feeds and on-site data.
- Intent-Driven Content: Descriptions should be front-loaded with benefits (who it’s for, what problem it solves) and clear use-case context (e.g., “best for day hikes above 40 degrees”).
- The Trust Factor: AI prioritizes credibility. Retailers should highlight review volume, surface sustainability certifications, and avoid exaggerated or unverifiable claims, which can lead to penalties by AI systems.
The Bottom Line
The shopping journey is transforming into an “invisible” research process happening inside AI conversations.
Success now depends on data discipline, ensuring your brand’s story is accurate, comprehensive, and trustworthy enough for an AI to act on your behalf.
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