âIf we have data, letâs look at data. If all we have are opinions, letâs go with mine.â
â Jim Barksdale
Todayâs #Martech minute peeks into your social media stats. Follow this page to help bring clarity to the complex world of #marketingtechnology đ
Microsoft recently dropped an official âHere Is How To Get Traffic From ChatGPTâ guide.
It has gotten surprisingly little attention.
Letâs go over it together.
A few weeks back Microsoft dropped âFrom discovery to influence: A guide to AEO and GEO - Practical data strategies to empower retailers for AI search, AI assistants and AI browsers.â
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.
Iâll also reference the pages in the PDF in case you want to go read it yourself.
That said, if you don't care and just want someone to get the ChatGPT traffic for you, let SEO Stuff do the heavy lifting:
https://t.co/eh1auroJF7
Microsoftâs central message in the doc is that retail competition is shifting from âbeing foundâ to âbeing chosen.â
They argue that traditional SEO was optimized for:
Ranking
Clicks
Page visits
Whereas AI-driven shopping replaces that with:
Answers
Recommendations
Agent-led decisions
Theyâre 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 âAEOâ and âGEOâ come in.
(I hate both of these acronyms and prefer to just call it all AI search optimization, but this is their doc so Iâll go with their language.)
This is also why weâve 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 Stuffâs Gold Plan.
https://t.co/yEFyM0Ze7W
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.
(Want to know if your site is AI-search ready? Check here: https://t.co/Pn764BHwyL)
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://t.co/wA30K3XNYQ
Microsoft then delved into the AI shopping ecosystem and how discovery actually works now.
One of the most interesting sections is Microsoftâs breakdown of AI browsers, assistants, and agents (pages 5â7).
These are not separate systems and they overlap constantly.
AI BROWSERS
Edge, Chrome, or similar with embedded AI
They can âseeâ 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 âwhich AI surface am I optimizing for?â
The question is what data can AI access, trust, and use?
This is exactly where most sites break.
The data exists, but it isnât structured, consistent, or surfaced in a way AI can reliably act on.
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 7â8).
AI does not rely on one data source, but rather fuses:
CRAWLED WEB DATA
Brand reputation
Category authority
Expert mentions
Historical understanding
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.
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 ârain jacket under $200.â
AI reasoning includes:
âPatagonia and North Face make quality jacketsâ (general knowledge)
âHiking jackets need to be lightweight and waterproofâ (category understanding)
âBrand X is known for hiking equipmentâ (brand positioning)
âYour model is $179 and in stockâ (feeds)
âCompetitor is $199 and backorderedâ (feeds)
Your product makes the top recommendations because feeds, availability, price, and context align.
This is why content that simply âranksâ but doesnât explain, compare, or justify rarely shows up in AI answers without additional supporting assets.
Microsoft then really breaks down the journey from SEO to AEO to GEO.
They summarize the transition pretty clearly (page 6):
SEO = matching keywords
âWaterproof rain jacketâ
AEO = descriptive clarity
âLightweight, packable waterproof rain jacket with ventilation and reflective pipingâ
GEO = justification and trust
âBest-rated by Outdoor Magazine, 4.8 stars, 180-day returns, 3-year warrantyâ
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.
Then Microsoft talks about three data layers you must control.
They stress that retailers must show up in three distinct data planes (page 10):
CRAWLED DATA
What AI learned during training
What it finds via real-time web search
This shapes baseline brand perception.
SEO still matters here.
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.
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.
Here are the three action pillars Microsoft prescribes.
This is the most legit part of the document (pages 11â14).
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:
âNever serve different HTML to bots than to users.â
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:
âBest for day hikes above 40 degreesâ
Headings that mirror real questions
Modular, citable content blocks
THEY EXPLICTELY ENCOURAGE:
Q&A sections
Comparison content
Feature lists
âGoes well withâ 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 wonât 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://t.co/wA30K3XNYQ
Pillar 3: Trust and credibility signals (GEO)
AI systems prioritize verifiable truth.
Microsoft highlights:
VERIFIED SOCIAL PROOF
Verified reviews
Review volume
Sentiment extraction (âhighly rated for comfort and fitâ)
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:
âAI penalizes low-trust language.â
Interesting, but obviously open to interpretation.
Microsoft then closed with a fairly straightforward 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 âAI ranking readiness.â
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 and sales from traditional search and AI search?
Just RT this and reply with âChatGPT Guideâ and Iâll DM you some âunconfirmedâ tricks weâve been using to get traffic from ChatGPT in as quickly as 30 days.
(Must be following me to get the DM.)
đ Missed calls are quietly costing businesses more than they realize.
According to Curious Thing AI, companies miss nearly 40% of customer calls on average.
Every unanswered call is a customer choosing someone else.
đĄ Learn more - https://t.co/YiKoaTzjS6
Missed calls = missed opportunities.
But what if every missed call automatically got a friendly text back - even booking appointments while you sleep?
đ˛ Book your free 15-minute audit today with MarTech Media.
https://t.co/ZHENIBu6JA
âď¸ Automation helps you look like a pro, even if youâre a one-person show.
According to Forbes, these 20 AI tools help small business owners save time, simplify marketing, and scale smarter.
đĄ The secret isnât doing more - itâs automating smarter.
đ https://t.co/YiKoaTzjS6
đ Missed calls are quietly costing businesses more than they realize.
According to Curious Thing AI, companies miss nearly 40% of customer calls on average.
Every unanswered call is a customer choosing someone else.
đĄ Learn more - https://t.co/YiKoaTzjS6
Automation may be the difference between being busy and being profitable. đź
Smart systems donât replace people â they empower them to focus on what moves the needle.
đĄ Want to work smarter, not harder?
Missed calls = missed opportunities.
But what if every missed call automatically got a friendly text back - even booking appointments while you sleep?
đ˛ Book your free 15-minute audit today with MarTech Media.
https://t.co/ZHENIBu6JA
âď¸ Automation helps you look like a pro, even if youâre a one-person show.
According to Forbes, these 20 AI tools help small business owners save time, simplify marketing, and scale smarter.
đĄ The secret isnât doing more - itâs automating smarter.
đ https://t.co/YiKoaTzjS6
đ Missed calls are quietly costing businesses more than they realize.
According to Curious Thing AI, companies miss nearly 40% of customer calls on average.
Every unanswered call is a customer choosing someone else.
đĄ Learn more - https://t.co/YiKoaTzjS6
Missed calls = missed opportunities.
But what if every missed call automatically got a friendly text back - even booking appointments while you sleep?
đ˛ Book your free 15-minute audit today with MarTech Media.
https://t.co/ZHENIBu6JA
Automation may be the difference between being busy and being profitable. đź
Smart systems donât replace people â they empower them to focus on what moves the needle.
đĄ Want to work smarter, not harder?