For more than two decades, online visibility has revolved around Search Engine Optimisation (SEO).
Brands optimised websites to rank for keywords in search engines. If your page appeared near the top, customers were more likely to click and buy.
Discovery behaviour is now shifting.
Consumers are increasingly asking AI assistants for recommendations instead of browsing search results. Tools such as ChatGPT, Gemini, and Perplexity can analyse products, compare options, and generate answers to complex buying questions.
This shift is creating a new optimisation discipline: Generative Engine Optimisation (GEO).
The traditional SEO model
Search engines index pages and rank them using signals such as:
- keyword relevance
- backlinks
- page authority
- content quality
- technical crawlability
When a user searches for a query like best standing desk, they get a list of links and perform the comparison themselves.
In this model, the user does the comparison work.
The rise of AI-assisted product discovery
AI assistants change this process.
Instead of returning ten links, they analyse information and produce a direct recommendation.
A typical journey now looks like:
Question -> AI analysis -> Recommendation -> Click -> Purchase
In this model, the AI performs the comparison work before the user sees results.
Why this changes optimisation strategy
In traditional SEO, visibility depends on ranking position.
In AI discovery, visibility depends on whether the assistant can:
- understand the product
- evaluate its attributes
- determine relevance to the user’s question
This is the core focus of GEO.
What is GEO?
Generative Engine Optimisation (GEO) is the process of structuring product information so AI systems can interpret and recommend it.
Where SEO focuses on ranking pages, GEO focuses on AI-readable product meaning.
Key GEO elements include:
- structured product attributes
- machine-readable data formats
- intent-aligned discovery pages
- semantic relationships between products
SEO vs GEO: key differences
| SEO | GEO | |
|---|---|---|
| Primary system | Search engines | AI assistants |
| Output | Ranked search results | AI-generated recommendations |
| Optimisation target | Pages | Products and structured data |
| Evaluation process | Performed by the user | Performed by the AI |
| Key signals | Keywords, links, authority | Attributes, context, relationships |
| Discovery format | Lists of links | Synthesised answers |
SEO optimises for visibility in search results.
GEO optimises for inclusion in AI recommendations.
How AI systems evaluate products
Large language models do not simply match keywords. They evaluate fit.
For a query like best running shoes for flat feet, AI systems may evaluate:
- stability
- arch support
- cushioning
- price range
- trust context
Products with clear structured attributes are easier to recommend.
Does GEO replace SEO?
No.
Search engines remain a major traffic source. GEO complements SEO rather than replacing it.
The channel mix is expanding across search engines, AI assistants, social platforms, and marketplaces.
The future of ecommerce visibility
Discovery has evolved through web directories, search engines, and now AI-assisted discovery.
The next winners will be brands whose product information is clear, structured, and machine-readable.
That is the goal of GEO.
Frequently asked questions
What is the difference between SEO and GEO?
SEO helps webpages rank in search results. GEO helps products appear in AI-generated recommendations.
Is GEO only relevant for ecommerce?
GEO concepts apply broadly, but ecommerce is currently one of the clearest use cases.
Do I still need SEO if I use GEO?
Yes. SEO remains foundational. GEO adds an AI discovery layer.
How can brands prepare for GEO?
Start by improving product attribute structure, schema coverage, and intent-aligned discovery content.
About Geoffy
Geoffy is a Generative Engine Optimisation platform that helps ecommerce brands structure catalogues for AI discovery through intent-aligned pages and machine-readable outputs.