The real experience of a business owner who has run Alibaba.com for 10 years after switching to GEO.

The real experience of a business owner who has run Alibaba.com for 10 years after switching to GEO.

Having worked in the platform industry for 10 years, I used to think that "traffic" was everything in the business; it wasn't until I actually started working on GEO (Generative Engine Optimization) that I realized:
Traffic may migrate, rules may change, but only cognition and trust will endure.

My previous growth strategy was clear and effective, but it became increasingly "passive."

If you've worked on Alibaba.com for many years, you're probably familiar with that "executable formula": ad placement, optimization, ranking boost, exposure acquisition, and inquiry conversion. It did work for a long time.

I've always done this before, even breaking down key actions into monthly KPIs: frequency of new product launches, P4P clicks, RFQ response, showcase allocation, keyword coverage ... I can explain each action in great detail.

My true feelings before the transformation (not a complaint, but reality)

• Traffic is on the platform, not in your own hands: After you stop advertising, traffic and inquiries will usually decline significantly within 2-4 weeks.
• While there seem to be many inquiries, the effectiveness rate is relatively low: In the foreign trade industry, the effective rate of platform inquiries is usually between 10% and 25% (which is greatly affected by industry, product category, and average order value).
• Customers are more likely to get caught up in price comparisons: with many competing products on the same screen and highly homogenized information, it often comes down to "whoever is cheaper wins".
• Weak brand loyalty: Customers remember the platform entry point, category page, and ranking, rather than "why you are more suitable for them".

Why I started studying GEO: The entry point has changed, and so has the customer's "first question."

In the past, customers' first questions were usually "How much?", "What is the minimum order quantity?", and "Can you do OEM/ODM?". Now, more and more customers are scanning basic information through AI, search, and industry content before even contacting suppliers.

When clients start using tools like ChatGPT, Gemini, Perplexity, and Copilot as their "primary research entry point," your display will no longer be just a "platform category ranking," but rather: whether you have entered the AI's recommended corpus and citation list .

The four most obvious changes for me after switching to GEO

Change 1: Customers "come with prior knowledge," no longer needing to be educated from scratch.

Previously, when customers asked about prices, it meant "they had no idea what you were talking about." Now, customers ask about more specific application scenarios, such as: continuous production stability, material corrosion resistance level, delivery cycle risks, and after-sales and spare parts strategies .

The emergence of this kind of problem essentially means that the client has already done their homework. Your negotiations started from a higher level, and the communication is more like "jointly choosing a solution" rather than "I explain and you listen."

Change 2: Reduced communication costs and more controllable transaction pace

In a platform model, it's difficult to control which information a customer sees: they might only look at the main image before making an inquiry. GEO's content is more like a "pre-communication system": it thoroughly explains common questions, comparison dimensions, selection logic, and risk warnings in advance.

Taking the common cycle of foreign trade B2B as a reference: a traditional inquiry may take 7-15 rounds of communication from the first contact to confirmation of demand; while when the customer has read the system content, it can often be compressed to 3-7 rounds to enter the quotation and sample stage (the actual time depends on the complexity of the industry).

Change 3: The number of inquiries may decrease, but the efficiency will increase.

This might feel strange at first: you'll find that "the daily inquiry notifications aren't as frequent." But the more real thing is that there are fewer invalid inquiries and a higher proportion of successful conversations with clients.

Many foreign trade teams have found that once the content clearly explains the thresholds and suitability conditions, the number of leads may decrease by 20% to 40% , but it is not uncommon for the proportion of effective leads to increase by 1.5 to 3 times (especially for categories with higher average order values ​​and those requiring selection).

Change 4: The first time I felt "recommended".

The most memorable time was when a client said, "I saw your solution through AI." That's when I truly realized that the entry point is no longer 'where you rank,' but 'why AI chose you.'

You've started to go from "grabbing traffic" to "being chosen." This experience is subtle—it doesn't fluctuate as much as platforms do every day, but once things are running smoothly, the leads become more stable and predictable.

Platform logic vs. GEO logic: It's not a substitution relationship, but a changing hierarchy.

I no longer see platforms as "enemies." Platforms still have value, especially for businesses dealing with standardized products, price-sensitive goods, and those needing to quickly test products. However, if you only bet on platforms, you'll be led by the rules.

To foreign trade business owners undergoing transformation: The pitfalls I encountered, you can avoid them.

1) Avoid a one-size-fits-all approach: Platforms may continue to emerge, but the "focus" must shift.

If your current orders mainly come from the platform, it's advisable not to act impulsively and "stop everything immediately." A more reasonable approach is to retain the platform as a cash flow stabilizer while treating GEO as a construction project for future entry points.

2) Start with a flagship product: delve deep into it, understand it thoroughly, and develop it into a quotable answer.

Many people try to cover all product categories right away, resulting in scattered content that makes it difficult for AI to grasp your main tags. It's recommended to choose a representative product line and build a content matrix around it, such as: selection guides, application scenarios, parameter explanations, comparison lists, maintenance and troubleshooting, and case studies .

3) Share your experience: The boss's judgment is actually the most valuable.

The biggest fear in foreign trade is "not being able to explain clearly." But if you've been in the business for 10 years, you'll definitely have a lot of details that can help clients make decisions, such as: the aging rate of a certain material under the climate of a certain country, the more recommended structure under certain working conditions, and how to control delivery risks.

Once these experiences are turned into content, they will transform from "oral transmission within the team" into assets that are "searchable, citationable, and recommended by AI".

4) Accept the slow warm-up period: It usually takes 6-12 weeks to see stable signals.

Based on the experience of most B2B independent websites/content-based customer acquisition, the first 2-4 weeks are mostly for laying the foundation; it is only in the 6-12 weeks that sustainable organic traffic and AI mention signals are more likely to be seen (depending on the posting frequency, content quality, site foundation and industry competition).

This period is the most anxiety-inducing, but also the most crucial: you are building a "system that can compound interest," not chasing "instant bursts of profit."

5) Use "whether it was mentioned by AI" as a feedback loop, instead of just focusing on page views (PV).

In the past, we looked at exposure, clicks, and inquiries; now we can add a more direct metric: whether AI mentions you under key questions .

You can ask the AI ​​questions that your target customers often ask (such as "Which type of solution is recommended for a certain application scenario/Supplier's points to note") and see if your brand, your point of view, and your case clues appear in the answers, and continuously iterate the content expression and structure.

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