Quick answer
Identify the market, buying question and AI interface where your supplier is absent, then inspect the public evidence relevant to that request. Appearing in a Chinese answer but missing from an English answer establishes a difference between samples. It does not establish a translation problem or bias against Chinese suppliers. Compare buyer requirements, candidate suppliers, recommendation reasons and visible sources before choosing what to investigate.
Details
Make “we are missing overseas” a testable observation
Use actual buyer wording from overseas sales to define the product category, application and purchasing constraints. Category questions test supplier discovery. Named-brand questions test recognition and factual accuracy; record them separately.
An illustrative prompt structure is “Which suppliers suit [application] and meet [confirmed purchasing requirements]?” The brackets are conditions to fill in, not a customer example. Adding your brand to every discovery prompt changes what the test measures.
Retain the exact prompt, language, target market, interface, search setting, time, full answer and displayed citations. Mark an unconfirmed location or model version as unknown. Naming a country in the prompt does not establish that the system ran from that country.
Investigate differences without assigning a cause prematurely
| Observation | What to check next | What it does not establish |
|---|---|---|
| Chinese and English questions produce different suppliers | Whether the questions express the same application and constraints | Translation quality caused the difference |
| Only local suppliers appear | Local delivery requirements, stated reasons and visible evidence | Chinese suppliers were excluded because of their origin |
| The answer cites an old catalogue or unrelated page | Whether current, readable English evidence answers the buying requirement | Publishing another English article will secure inclusion |
| The brand is recognised in a named query but absent from discovery | Evidence of suitability for the use case, beyond a company description | Recognition has solved the recommendation gap |
These are investigation paths. Absence does not prove that the supplier was never retrieved or reveal why it was omitted. If sources are not displayed, record that limitation instead of inventing a source trail.
Turn the finding into a focused next action
Use a record with the buyer requirement, the answer's selection reason, the verifiable public evidence and the unresolved gap. If prompts describe different needs, repair the test design. If facts conflict, confirm the valid version. If approved facts do not answer the buyer's question, prepare a focused page change.
Language suitability and actual availability in a market are separate checks. After an approved change is confirmed publicly readable, repeat the original questions under comparable conditions and continue reporting markets separately. See the existing cross-border guide and retesting guide.
Common questions
Q: How do we diagnose AI search visibility for Chinese exporters?
A: Start with a retained answer to a specific buyer question in a defined market and interface. Compare the buyer's requirements with the suppliers, reasons and sources shown, and record unresolved explanations as hypotheses.
Q: ChatGPT finds us in Chinese but not in English. Is translation the problem?
A: That difference alone cannot establish the cause. Check whether the prompts describe the same buying need, then compare interfaces, search conditions and relevant public evidence. Recognition in one language does not establish discovery in another.
Q: Does a local-only supplier shortlist prove bias against Chinese exporters?
A: It shows which suppliers appeared in that sample. Inspect local requirements, stated reasons and visible sources, and repeat the observation before drawing broader conclusions about exclusion.
Q: How do we get recommended by ChatGPT as a B2B supplier?
A: Establish a baseline with unbranded buyer questions, then identify gaps in inclusion, accuracy and reasons. Prepare changes grounded in approved public evidence and retest them. No page change guarantees a recommendation in a particular answer.