A daily tip for building a website for international trade: How to get AI to recommend your website?

As more and more overseas buyers begin to rely on AI platforms such as ChatGPT, DeepSeek, Doubao, and Wenxin Yiyan to obtain supplier information, a reality is quietly changing:

Before customers even click on Google, your website has already been "pre-screened" by AI.

The problem is—

Are you on AI's "candidate list"?

Recommended reading: Essential for foreign trade brands going global: GEO generative engine optimization guide to improve AI search visibility

I. A harsh reality: Your website may have been excluded by AI from the very beginning.

In the past two years, I have come into contact with many foreign trade companies, and they all have one thing in common:

• The official website is not cheap.

• The page also looks "quite professional".

• The product is indeed impressive.

But the result was:

• AI never mentions you

• Customers never find you "on the way".

• Inquiries are increasingly reliant on platforms and existing customers.

The problem isn't with the product itself, but rather with "whether your website is worth recommending in the eyes of AI."

Second, let's start with the conclusion: Why does AI "not recommend" most foreign trade websites?

From the perspective of AI's working mechanism, it doesn't "watch ads" or "listen to your self-praise." It makes judgments on three core things:

1. Are you a professional information source in this field?

2. Does your content answer real procurement questions?

3. Does your website possess long-term, stable credibility?

In reality, many foreign trade websites have fallen into the opposite category.

III. Three common "AI-unfriendly" pitfalls on foreign trade websites

Pitfall 1: The official website is just a "display page," not the "answer page."

Many official websites have this structure:

• About Us

• Products

• Contact

The page content is highly homogenized:

“We are a professional manufacturer with 20 years experience…”

It works fine for humans, but it has absolutely no value for AI.

AI doesn't want "who you are," but rather:

• What problem are you solving?

• How deep is your understanding of the industry?

• Do you possess professional judgment that can be cited?

Pitfall 2: Blindly stuffing keywords can actually lower trust levels.

There is another type of company that has begun to "realize the importance of SEO," and so:

• 20 keywords crammed into one page

• Buying external links everywhere

• Content repetition, patchwork

What was the result?

In AI systems, these types of websites are often classified as:

"Low-reliability information sources"

"Clear signs of optimization"

"Lack of genuine industry insights"

Not only is it not recommended, but it is also "downgraded and ignored".

Pitfall 3: Fragmented content; AI "can't understand your strengths".

You may have written quite a bit:

• An industry article

• Several product introductions

• Several news updates

But the problem is:

• No theme focus

• No logical connection

• No continuous output

From the AI's perspective, you are "speaking occasionally" rather than "speaking consistently".

IV. A Different Perspective: How Does AI "Select" Recommended Objects?

If you look at it from an AI perspective, you'll find a very clear logic:

AI prefers to recommend people who "provide answers to questions consistently, systematically, and reliably over a long period."

Especially in B2B procurement scenarios, the most frequent questions AI is asked are not about brands, but rather about other issues:

• How to choose XXX supplier?

• What certifications are required for XXX?

• Common risks when sourcing XXX?

• Difference between XXX material A and B?

Those who can consistently, professionally, and systematically answer these questions are more likely to be remembered.

V. Scenario Breakdown: The Real Path of AI Recommending Suppliers

Let's break down a real-world procurement scenario:

Overseas buyers can input the following into the AI:

“Reliable XXX suppliers in Asia”

AI won't "make up a company randomly," but will make a comprehensive judgment:

1. Which websites consistently produce content related to this industry?

2. Which content is cited multiple times and has a clear structure?

3. Which companies possess a clear positioning and credible signals?

What is ultimately given is often not "the advertiser," but rather:

"Those few companies that seem to know the most about it."

VI. Case Study: How can a traditional foreign trade company enter the AI ​​recommendation field of vision?

Company Background

• Industry: Industrial B2B

• Problem: The website has received no inquiries for many years.

• Advantages: Solid technical skills and rich experience

Step 1: Without changing the design, change the "content roles" first.

The first thing they did was not to rebuild the website, but to make one thing clear:

The official website should start answering "procurement questions" instead of just showcasing products.

Therefore, the system outputs content centered around the core product, such as:

• 《How to evaluate XXX quality》

• "XXX certifications explained"

• "Top sourcing mistakes buyers make"

Step Two: Content no longer exists as "single articles," but rather as "thematic clusters."

Each core issue:

• At least 3–5 pieces of extended content

• Clearly define the hierarchy logic

• Standardized professional terminology

result:

When AI is understanding, it can clearly determine that they are "long-term contributors in a specific niche".

Step 3: Naturally embed enterprise information into the "solution context"

Instead of writing "How awesome we are", it should be:

• Using real-life examples

• Parameter description

• From an engineering perspective

Make businesses "part of the answer".

VII. A 5-Step Implementation Path that Can Be Replicated by Ordinary Foreign Trade Enterprises

Step 1: Compile a "List of Common AI Procurement Questions"

Not keywords, but the complete question:

• Selection

• risk

• standard

• Application scenarios

Step 2: Write the standard answer using "industry-specific language".

There are only four principles:

• No exaggeration

• Not empty

• No word piling

• Quotable

Step 3: Create a "semantic network" from the content.

• Multiple articles on the same topic

• strong internal association

• Unified cognitive framework

Step 4: Upgrade the official website from a "business card" to a "knowledge hub"

Let the AI ​​know explicitly:

"You're not a product sales page, but an industry information source."

Step 5: Sustained output, rather than a one-time burst of effort.

AI trusts what "long-term existence" means, not what "short-term bursts" mean.

8. What is the essence of what AB customers are solving here?

Many foreign trade companies are not ignorant, but rather stuck on three practical issues:

• I don't know what to write.

• It was written in a disorganized manner.

• I did it but I can't see the results.

What ABke truly solves is not "helping you write articles," but rather:

Transform "AI recommendation logic" into a system that foreign trade enterprises can sustainably implement.

• Use structured website building to make your official website "understandable by AI".

• By systematically delivering content, we can ensure that our expertise is "remembered by AI."

• Using semantics and internal linking logic, websites can form a "trusted network".

What's amplified is your existing professional competence.

9. The last piece of truth for those in foreign trade

In the next few years, a clear watershed will emerge in customer acquisition for foreign trade:

• A type of company that AI repeatedly mentions

• One type of company is gradually disappearing from recommendations.

The difference lies not in the budget, nor in the scale, but in:

Have you enabled AI to understand: who you are, what you are good at, and whether you are worthy of being recommended?

If you start planning now, you'll be one step ahead of most of your peers.