E-Commerce AI Visibility: GEO Entity and Citation Strategy — Example Project

The Challenge

A home-goods retailer selling Scandinavian-inspired furniture had solid SEO — page 1 for dozens of target keywords — but was invisible to AI search. When someone asked ChatGPT “what’s the best minimalist furniture brand?”, the brand wasn’t mentioned.

Our Approach

AI Crawl Audit

First, we identified the gaps:

No llms.txt file
robots.txt blocked GPTBot
Product pages lacked structured data
Content wasn’t structured for citation

GEO Implementation

llms.txt Creation

We created a comprehensive llms.txt file describing:

Company overview and founding story
Product categories and specialties
Design philosophy and materials
Contact and booking information

robots.txt Updates

Allowed AI crawlers:

User-agent: GPTBot
Allow: /

User-agent: Claude-Web
Allow: /

User-agent: PerplexityBot
Allow: /

Content Restructuring

Rewrote product descriptions and category pages to be citation-friendly:

Clear, factual product specifications
Comparison tables with measurable attributes
Expert quotes and design rationale
Statistical data about materials and sustainability

Schema Enhancement

Added Product, Organization, and FAQPage schema across all key pages.

What the build delivers

Deliverable	Detail
`llms.txt`	Company, catalog, materials, contact — machine-readable
`robots.txt`	GPTBot, Claude-Web, PerplexityBot explicitly allowed
Schema	`Product`, `Organization`, `FAQPage` on key pages
Citation-ready copy	Specs, comparison tables, sourced material data
Page speed	Lighthouse 97, LCP 0.5s

Whether and how fast a brand gets cited depends on the model, the query and the authority already pointing at the site. We track citations per engagement instead of promising a number here.

Related reading:

Our AI Search Optimization Service — Full GEO implementation
How to Get Cited in ChatGPT — Step-by-step guide
llms.txt Explained — The file we set up for this type of client