Get Named When Buyers Ask AI
Whom to Source From
Sourcing research increasingly starts inside ChatGPT, Perplexity, Gemini and Google’s AI Overviews. Those answers name two or three suppliers and cite a handful of sources — the ones a model can parse, verify and trust. We make your site one of them.
The Answer Box Does Not Have Ten Slots
A search results page can hold a thousand suppliers. A generated answer names three. Ranking on page one no longer means being considered.
The first screen is no longer a list of links
When a buyer asks an assistant to shortlist reliable suppliers in your category, the reply names a few companies and links a few pages. Everyone else is absent from the conversation entirely — even companies sitting at position one on Google.
Your site is written for people, not for retrieval
Models quote pages they can decompose: a clear claim, a labelled specification, a dated certification, one question per heading. Brochure copy and stock photography leave nothing extractable, so the model skips you.
You cannot see whether you are being quoted
Rankings are visible. AI answers are personalised, unstable and invisible to ranking tools. Without a fixed prompt set and a sampling routine, you cannot tell whether you are winning or losing share of the answer.
What We Actually Change
GEO is not a plugin or a submission form. It is the sum of what a model can find, parse, verify and repeat about your company — engineered on purpose.
Answer-shaped content architecture
Every product line gets pages that answer the questions procurement actually asks before it quotes: capacity, tolerance, MOQ, lead time, certification, export experience.
- One question per heading, answered in the first sentence
- Specifications in tables, not in prose
- Named, dated proof: certifications, audit reports, line capacity
- Comparison pages that models quote when buyers ask “X vs Y”
Entity and schema foundations
Models resolve entities, not keywords. Your company facts have to agree everywhere before an answer will state them as fact.
- Schema.org markup: Organization, Product, FAQPage, Service
- Consistent company facts across site, LinkedIn, directories and Wikidata
- Product entities linked to the factory that makes them
- Author and about pages that establish who is speaking
Crawl and retrieval access
Being readable is a technical precondition. Most Chinese factory sites fail it before content is even considered.
- llms.txt and clean robots rules for GPTBot, OAI-SearchBot, PerplexityBot, ClaudeBot
- Server-rendered content — nothing important locked inside JavaScript
- Stable canonical URLs and one clear page per topic
- Page weight cut so crawlers do not time out mid-parse
Citation monitoring and iteration
What gets measured gets fixed. Every month we ask the same buying-intent questions and record who was named instead of you.
- A fixed prompt set of 30–50 real sourcing questions
- Sampling across ChatGPT, Perplexity, Gemini, Copilot and AI Overviews
- Share-of-answer reporting, month over month
- A prioritised fix list for every gap a competitor is filling
Four Steps From Invisible to Cited
We start by measuring what the engines currently say about your category. Everything after that is closing a specific gap.
Baseline audit
Run 30–50 buying-intent prompts across five AI engines. Record which companies are named, which URLs are cited, and where you appear at all.
Fact and entity clean-up
Standardise capacity, certification, contact and product facts so every source a model reads tells the same story about your factory.
Build and publish
Restructure priority pages, add schema and llms.txt, and publish the specification and comparison content models prefer to quote.
Measure and iterate
Re-run the prompt set monthly, report share of answer, and rewrite the pages where competitors are still the cited source.
Three Exporters, Three Bottlenecks
Client names are under NDA. Sector and market are accurate; what you see is the deliverable, not a mock-up.
A catalogue rebuilt around buyer questions
Eighteen pages rewritten so each one answers a question asked before a sample request: MOQ, fabric testing, lead time, packaging.
Cutting crawl waste, rewriting for intent
120 indexed URLs consolidated to 46, and the forty pages that carry buyer intent rewritten around tolerance, material and lead time.
One visual system across four channels
Logo, palette and layout rebuilt to survive the same test everywhere: a search ad, a product page, a retargeting banner and a vertical clip.
Common Questions About GEO
The things clients ask most, answered directly.
How is GEO different from SEO?
SEO competes for positions on a results page; GEO competes to be one of the few sources an answer is built from. The technical base overlaps, but the content unit is different: instead of keyword-targeted pages you need extractable answers, verifiable facts and a consistent company entity.
Can you guarantee we will be cited by ChatGPT?
No — and any agency that guarantees it is guessing. What can be controlled is access, structure, factual consistency and topic coverage. We report share of answer every month so progress is visible rather than asserted.
How long before results show?
Retrieval indexes refresh within weeks; model familiarity compounds over months. Most clients see the first new citations four to eight weeks after the technical and content fixes go live.
Do we have to rebuild the website?
Usually not. Most of the work is restructuring existing pages, adding schema and publishing the answer pages that are missing. A rebuild only makes sense when the content sits somewhere it cannot be marked up or crawled.
Does GEO replace Google SEO?
No. The same pages feed both channels. Treat GEO as a second use of the content asset you are already paying for — one that becomes visible inside AI answers instead of only on a results page.
Find Out What AI Says About Your Factory
Send us your product category and main export markets. We will run the prompt set, send you the answers we got, and show where competitors were cited instead of you.