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NEW: Microsoft just revealed how to get traffic from ChatGPT.

NEW: Microsoft just revealed how to get traffic from ChatGPT.

Microsoft just released an official "Here Is How To Get Traffic From ChatGPT" Guide.

It has gotten surprisingly little attention. Let's go over it together.

This week Microsoft dropped “From discovery to influence: A guide to AEO and GEO – Practical data strategies to empower retailers for AI search, AI assistants and AI browsers.”

Everything here is drawn directly from the document and its diagrams with some of my personal takes layered on top for clarity and execution value. I'll also reference the pages in the pdf in case you want to go read it yourself.

1. Microsoft’s central message in the doc is that retail competition is shifting from “being found” to “being chosen.”

They argue that traditional SEO was optimized for:

  • Ranking
  • Clicks
  • Page visits
  • Whereas AI-driven shopping replaces that with:

  • Answers
  • Recommendations
  • Agent-led decisions
  • They're arguing that visibility is now earned by how clearly AI systems understand your products, trust your brand and can act on your data.

    This is where "AEO" and "GEO" come in. (I hate both of these acronyms and prefer to just call it all AI search optimization, but this is their doc so I'll go with their language.)

    This is also why we’ve seen brands struggle even with strong traditional SEO, but immediately improve AI visibility once they pair technical SEO with structured, intent-driven content and authoritative signals like those included in SEO Stuff’s Gold Plan
    https://seo-stuff.com/gold-plan-package

    2. Microsoft also broke down the difference (to them) between AEO and GEO.

    Microsoft makes it a very clean distinction:

    Answer / Agentic Engine Optimization (AEO) in their estimation optimizes content and data so AI assistants and agents (Copilot, ChatGPT, Gemini) can:

  • Find it
  • Understand it
  • Summarize it
  • Recommend it
  • Act on it
  • This is about clarity and machine-readability.

    Generative Engine Optimization (GEO)

    Optimizes content so generative AI search systems trust it as:

  • Authoritative
  • Credible
  • Citable
  • This is about credibility, reputation and justification.

    Microsoft is explicit that SEO still matters, but it is now the foundation and not the endpoint.

    In practice, this is why execution now requires both properly structured pages and volume at scale, something SEO Stuff intentionally designed the Premium Content Bundle to solve
    https://seo-stuff.com/premium-content-bundle

    3. Microsoft then delved into the AI shopping ecosystem (how discovery actually works now).

    One of the most interesting sections is Microsoft’s breakdown of AI browsers, assistants and agents (pages 5–7).

    These are not separate systems and they overlap constantly:

    AI Browsers

    Edge, Chrome or similar with embedded AI

    They can “see” the live page you are on and interpret it in real time.

    AI Assistants

    Copilot, ChatGPT, Gemini

    They answer questions, summarize options and recommend products.

    AI Agents
    They:

  • Navigate websites
  • Add items to carts
  • Apply promo codes
  • Calculate shipping
  • Complete purchases
  • The key insight:

    The question is not “which AI surface am I optimizing for?” The question is what data can AI access, trust, and use?

    This is exactly where most sites break. The data exists, but it isn’t structured, consistent or surfaced in a way AI can reliably act on.

    4. Microsoft then went into how AI actually decides what to recommend.

    Microsoft outlines a multi-stage reasoning process used by Copilot and Bing AI (pages 7–8).

    AI does not rely on one data source, but rather fuses:

    1. Crawled web data

  • Brand reputation
  • Category authority
  • Expert mentions
  • Historical understanding
  • 2. Product feeds and APIs

  • Price
  • Availability
  • Variants
  • Inventory
  • Key specs
  • This is where competitive advantage often comes from, and where most brands are under-optimized.

    3. Live website data

  • Real-time pricing
  • Promotions
  • Reviews
  • Media
  • Checkout functionality
  • If your live site fails, the agent fails, even if feeds were perfect.

    An example Microsoft gives is rain jacket under $200.

    AI reasoning includes:

  • “Patagonia and North Face make quality jackets” (general knowledge)
  • “Hiking jackets need to be lightweight and waterproof” (category understanding)
  • “Brand X is known for hiking equipment” (brand positioning)
  • “Your model is $179 and in stock” (feeds)
  • “Competitor is $199 and backordered” (feeds)
  • Your product makes the top recommendations because feeds + availability + price + context align.

    This is why content that simply “ranks” but doesn’t explain, compare or justify rarely shows up in AI answers without additional supporting assets.

    5. Microsoft then really breaks down the journey from SEO to AEO to GEO.

    They summarize the transition pretty clearly (page 6):

    SEO = matching keywords
    “Waterproof rain jacket”

    AEO = descriptive clarity
    “Lightweight, packable waterproof rain jacket with ventilation and reflective piping”

    GEO = justification and trust
    “Best-rated by Outdoor Magazine, 4.8 stars, 180-day returns, 3-year warranty”

    So basically AEO drives understanding and GEO drives confidence and you need both to be recommended.

    This is why brands pairing long-form, intent-driven content with authoritative backlinks and mentions often outperform those relying on SEO alone.

    6. Then Microsoft talks about 3 data layers you must control.

    They tress that retailers must show up in 3 distinct data planes (page 10):

    1. Crawled data

  • What AI learned during training
  • What it finds via real-time web search
  • This shapes baseline brand perception.

    SEO still matters here.

    2. Product feeds and APIs

  • Structured data you actively provide
  • This is where precision and control live
  • Feeds drive:

  • Comparisons
  • Rankings
  • Recommendations
  • This is where many retailers under-invest.

    3. Live website data

  • What AI agents see when they actually visit
  • Includes:

  • Reviews
  • Media
  • Dynamic pricing
  • Checkout capability
  • If agents cannot transact, influence stops at recommendation.

    7. Here are the 3 action pillars Microsoft prescribes.

    This is the most legit part of the document (pages 11–14).

    Pillar 1: Technical foundations and structured data

    AI requires structure and consistency, not creativity.

    Microsoft explicitly calls for:

  • Machine-readable catalogs
  • Dynamic fields: Price Availability Size Color SKU GTIN dateModified
  • ItemList markup for categories
  • Localized pricing and language via: inLanguage priceCurrency
  • Required schema types:

  • Product
  • Offer
  • AggregateRating
  • Review
  • Brand
  • ItemList
  • FAQ
  • They also highlight this:

    "Never serve different HTML to bots than to users."

    Pillar 2: Intent-driven content enrichment

    AI interprets intent over keywords.

    Microsoft recommends:

  • Front-loading descriptions with: Who it is for What problem it solves Why it is better
  • Use-case framing: “Best for day hikes above 40 degrees”
  • Headings that mirror real questions
  • Modular, citable content blocks
  • They explicitly encourage:

  • Q&A sections
  • Comparison content
  • Feature lists
  • “Goes well with” product relationships
  • Video transcripts
  • Detailed image alt text with ImageObject schema
  • This is content designed for extraction as opposed to reading.

    This is also why scale matters. One or two pages won’t move the needle. Systems that produce dozens of structured, intent-mapped articles tend to win, which is exactly what the Premium Content Bundle is built around
    https://seo-stuff.com/premium-content-bundle

    Pillar 3: Trust and credibility signals (GEO)

    AI systems prioritize verifiable truth.

    Microsoft highlights:

    Verified social proof

  • Verified reviews
  • Review volume
  • Sentiment extraction (“highly rated for comfort and fit”)
  • Review and AggregateRating schema
  • Authoritative brand identity

  • Expert reviews
  • Press mentions
  • Certifications
  • Sustainability badges
  • Official brand links
  • Content integrity

  • Avoid exaggerated claims
  • Maintain consistent brand voice
  • Provide structured FAQs and help content
  • This also stood out:

    "AI penalizes low-trust language."

    Interesting, but obviously open to interpretation.

    8. Microsoft then closed with a fairly straight forward message.

    Retailers already have most of the signals AI uses to rank and recommend.

    The winners in AI commerce will be the brands that:

  • Treat data as a product
  • Treat feeds as strategic assets
  • Treat content as machine-readable infrastructure
  • Treat trust as a measurable ranking factor
  • This is what Microsoft calls “AI ranking readiness.”

    9. If I had to reduce this entire PDF to one core idea...

    If AI cannot clearly understand your products, justify recommending them and act on your data in real time, you will not be a legit presence in AI-driven commerce.

    This document is Microsoft formally telling retailers that:

  • SEO alone is good, but not fully enough
  • Feeds are now a competitive moat
  • Trust is algorithmic
  • AI assistants are the new gatekeepers of demand
  • Luckily, SEO Stuff solves for all of this. Want to increase your traffic + sales from traditional search and AI search?

    Just RT this + reply with "ChatGPT Guide" and I'll DM you some "unconfirmed" tricks we've been using to get traffic from ChatGPT in as quickly as 30 days. (Must be following me to get the DM).

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