AI Search Visibility by Country: How to Check What Users See

Search no longer ends with ten links. Google shows AI Overviews above the results for many queries, and chat assistants with web search answer questions in a single paragraph and cite a few sources. Those answers are what a growing number of people read about your brand, and they are not the same in every country.

This guide gives a repeatable way to check what AI search says in each of your markets: which surfaces to look at, how to build a prompt list, how to control language and account state, where a connection from the target country helps, how to log runs and compare countries. It is written for SEO, brand and market teams that work lawfully with public answers.

1.Why AI answers differ between countries

An answer from an AI search feature is built from several inputs, and most of them change from market to market:

• The search results behind the answer. Features that search the web start from results that search engines localise by country and language.
• The language of the prompt. A question in Ukrainian and the same question in English often lead to different sources.
• Local sources. Local media, marketplaces and directories carry weight in their own market and may not exist in another.
• Availability. A feature may appear in one country or language earlier than in another. Check Google’s help pages for the current list.
• Chance. The same prompt asked twice can give different answers, even from one place.

Platforms do not publish exactly how much weight each location signal gets, so treat location as a hypothesis to test, not a fact to assume. That is why a method matters more than a tool.

2.Which surfaces to check

Classic results stay worth tracking, because AI features draw on them. Our page on SEO and SERP tracking by location covers that side, and ad verification covers ads and landing pages in each market.

3.A repeatable method

1. Fix the prompt list. Write 20 to 50 prompts that real customers ask, and do not change the wording between runs.
2. Run each prompt several times per country. Five runs is a sensible start. One answer is a single case, not a pattern.
3. Save the raw answer. Keep the text, the cited URLs and, if you can, a screenshot. Summaries lose the details you will need later.
4. Compare countries. Look at the rates per country and at the sources that differ.
5. Repeat on a schedule. A weekly or monthly rhythm shows trends, and the same time of day reduces noise.

4.Build the prompt list

Mix four kinds of prompts, and write each in the language people in that market use:

Translate prompts the way a native speaker would ask, not word for word. A translated English prompt can miss the phrases people really use.

5.Control language, account and time

Location is only one input. To make runs comparable, fix the rest:

• Account state. A signed-in session can use history and memory. Use a clean browser profile, signed out, or the same test account for every run, and log which one it was.
• Language settings. Set the browser and interface language of the market you test. In Playwright that is locale and timezone_id on the browser context.
• Model and mode. Different modes and model versions answer differently. Write down which one you used.
• Time. Run all countries in the same time window, because answers change over days.

6.Where a proxy fits, and what it does not change

Search features localise by signals such as the network location of the connection, the language settings and the account. A proxy supplies the first: a connection that leaves from the country you want to look from. Many people search from phones on mobile networks, so a 4G mobile proxy in the country fits mobile results, while a datacenter proxy suits quick checks from a server. Mobile versus datacenter proxies explains the difference.

Confirm the vantage point before you start. This call returns the IP address and the country the server sees:

curl -x http://USERNAME:PASSWORD@HOST:PORT https://xameleon.cloud/api/tools/ip
# {"ip":"203.0.113.25","country":"UA"}

The gl and hl parameters of Google search URLs set the country and the interface language of the results page, which is useful for a quick comparison. They are not the same as being in the country, so use them next to a local connection and not instead of it.

A proxy does not change the model, your account, your cookies, your language settings or the chat memory. It also does not make a service available where its provider does not offer it, and it is not a way to open extra accounts. Follow every provider’s terms. This guide is about checking public answers for your own brand and markets.

7.Log every run

One line per run is enough. The columns below let you filter by country, engine and language later, and prove what you saw:

import datetime
import json

def log_run(path: str, *, engine: str, country: str, language: str, prompt: str,
            answer: str, cited_urls: list[str], logged_in: bool = False, note: str = "") -> None:
    row = {
        "ts": datetime.datetime.now(datetime.timezone.utc).isoformat(timespec="seconds"),
        "engine": engine,          # for example "ai-overviews", "assistant-a"
        "country": country,        # the country of the connection, checked with the IP endpoint
        "language": language,
        "prompt": prompt,
        "answer": answer,          # the full text, not a summary
        "cited_urls": cited_urls,
        "logged_in": logged_in,
        "note": note,
    }
    with open(path, "a", encoding="utf-8") as f:
        f.write(json.dumps(row, ensure_ascii=False) + "\n")

Fill it from your own notes, from an export, or from an official API that returns the answer and its sources. We do not publish code that automates consumer chat or search pages, because most of their terms restrict it.

8.Compare countries

Once the log has enough rows, a short script gives the rates per country and engine:

import json
from collections import defaultdict

BRAND = "examplebrand"
DOMAIN = "example.com"

stats = defaultdict(lambda: {"runs": 0, "mentioned": 0, "cited": 0})
with open("runs.jsonl", encoding="utf-8") as f:
    for line in f:
        row = json.loads(line)
        s = stats[(row["country"], row["engine"])]
        s["runs"] += 1
        s["mentioned"] += BRAND in row["answer"].lower()
        s["cited"] += any(DOMAIN in url for url in row["cited_urls"])

for (country, engine), s in sorted(stats.items()):
    print(f"{country:3} {engine:14} runs={s['runs']:3}  "
          f"mention={s['mentioned'] / s['runs']:.0%}  cited={s['cited'] / s['runs']:.0%}")

Read the numbers with the sample size in mind. With five runs per prompt, a difference of one run is noise, while a difference across dozens of prompts is a signal.

9.Metrics that mean something

When a country shows a gap, read the cited sources first. They tell you which pages and sites shape the answer there, and so where to improve your own content, your listings and your brand protection checks.

10.Stay within the terms of the services

• Read the terms. Search engines and AI assistants usually restrict automated queries to their consumer pages. Do not build bots against them.
• Prefer official routes. Use the provider’s API where it returns what you need, or a monitoring tool that the provider allows. An API answer can differ from what the consumer product shows, so say which one you measured.
• Keep volumes small. A prompt list of dozens, run a few times a week, is monitoring. Thousands of automated queries are not.
• Use one honest identity. Your own accounts, one per person, signed in only when the test needs it.

Our Acceptable Use Policy and the guide to secure and responsible proxy use apply to every account. If you do script a check where the terms allow it, the Python proxies guide and proxies for AI agents show how to connect the proxy, and the API lets you change the IP between runs from your own code.

11.Common mistakes

12.FAQs

Do AI answers differ by country?

They can. Features that search the web start from localised results, prompts differ by language and local sources vary, and answers also change between identical runs. Measure it for your markets with repeated runs instead of assuming.

How do I check Google AI Overviews for another country?

Look at the results page from a connection in that country, with the browser language of that market and a clean profile, and record whether an overview appears, its text and its cited links. Compare several queries and several runs.

How many runs do I need per prompt?

Start with five per prompt and country. Increase it if the results flip between runs. The more prompts you have, the more a pattern means.

Do I need a proxy to check AI search by country?

It helps when you want to see what a visitor in a country sees and you are not in that country. A proxy supplies the network location only, so keep the account, language and time constant. See mobile proxies and datacenter proxies.

Which metrics matter most?

Mention rate for category prompts, citation rate, wrong facts and share of voice. Compare countries on the same prompt set.

What is generative engine optimization?

GEO means improving how your content appears in AI-generated answers: clear pages, accurate facts, good structure and sources that others cite. Checking by country shows where the work is needed. For the data side, read web scraping for AI training data and RAG.

Still have questions about mobile proxies? Visit our FAQ page for detailed answers, or contact our support team — we're here to help.