Out of Ideas? Ask AI First

⬅️ Coming from · Website Basics

Your site is live — for building one today we recommend 👉 AllinCMS (the earlier Bolt / v0 tutorials are now historical reference). But when the editor opens, many people freeze — what do buyers actually want to read? This guide solves two things: what to write, and how to tell whether it worked.

🌟 Goal: use real inquiries and AI to find the questions buyers genuinely ask, and turn your site into something that closes deals, with verifiable content. No hype here — every action below is something you can start alone.

💡 What you will finish here: find 3 candidate buyer questions, draft a first version of your answer page, and learn to judge whether it worked. About 15 minutes to get started.

One: Find Yourself Here

People working on their own site usually get stuck at one of four spots:

1. You don't know what buyers want — who they are, or what words they use to find you;
2. You don't know what to write — hours in front of a blank editor, and it still reads like a product sheet;
3. Nobody reads what you wrote — you published a few posts and three months of silence followed;
4. You can't tell whether it worked — plenty of numbers in the dashboard, but no idea which piece brought inquiries.

The next five sections solve these one by one: Section Two solves ①, Section Three solves ②, Sections Four and Five solve ③, and Section Six solves ④. Start with the deadliest one.

Two: What Do Buyers Want?

Don't ask AI "who is my customer" — look at what you already have. Three sources, ranked by how much to trust them:

Desensitize Before Sending to AI

Customer emails, chat logs, and RFQ quotes often contain names, email addresses, company names, prices, and order numbers. Before sending anything to any AI: remove personally identifiable details; handle prices and non-public specs per company policy; when unsure whether you may share it, ask the person in charge first.

Source 1: Your Company's Memory

New to the job? The company isn't — chat logs from senior salespeople, a few old emails, notes on the back of trade-fair business cards. Buyers' own words are worth the most: "we need it food grade" and your summary "customers care about food safety" are two different things. Get authorization before using these materials, and desensitize them per the box above.

Source 2: RFQ Boards

An RFQ is a request for quotation posted by a buyer. The RFQ boards on Alibaba.com and Made-in-China carry publicly viewable buyer questions. Take only content you are allowed to view and analyze, collect the minimum necessary snippets, gather 20–50, and send them to AI for clustering:

Below are desensitized buyer inquiry quotes I collected from RFQ boards. Please:
1. Cluster them by topic: product selection / certification / price / lead time / customization / other;
2. Find phrases that appear 3+ times and keep the exact English wording;
3. For each cluster, summarize what buyers are really trying to confirm, and which page my website needs in order to answer it.
[Paste 20–50 desensitized RFQ quotes]

Source 3: The AI Explorer

No access to the first two? Then use this one. Keep this in mind first: AI is a low-cost explorer, not a demand validator. Its output echoes content that already exists — in markets with less published buyer content, it helps you draft hypotheses, but scarce material does not mean more accurate answers or stronger demand. Let it draft the questions buyers might ask:

I am a salesperson at a [industry, e.g. stainless-steel tableware] export factory. My main product is [product, e.g. 304 stainless-steel trays], and I export to [market, e.g. Germany].
Act as buyers from this market and list the 20 questions they would most likely ask when looking for a supplier:
1. Group them by stage: selection / vetting the supplier / final checks before ordering;
2. Write each question as a natural English sentence a buyer would actually use;
3. For each question, note what the buyer is really trying to confirm.
No marketing advice — just the question list.

Once you have 20 questions, your part starts: pick the 3 high-intent ones — prefer questions that touch concrete specs, quantities, lead times, compliance, or samples; those directly affect purchasing decisions. Search each in the search engine your target market uses (once in the local language, once in English), and read what the top 10 pages answer — whatever they leave unanswered is only a candidate topic. It still has to pass three checks: can you (or your company) truly answer it? Does it have commercial value for buyers? Do you have a lawful, credible source? Write only after all three pass. If your site has Google Search Console (GSC) with impression data, cross-check with real search terms. Without GSC you can still start, but never treat AI-guessed questions as real demand — before publishing, verify each with target-market search results, customers, or feedback from senior salespeople.

Pain point ① (not knowing what buyers want) ends here.

Three: What to Write

First, break the mental block: you don't need to be a writer; you need to be a good answerer. High-intent buyer questions are all factual, and the answers are mostly in your head — but numbers like lead times, MOQ (minimum order quantity), and test standards usually need sign-off from production, quality, or the boss. Before writing, mark each item on this "decision-value checklist" as confirmed / pending internal confirmation / not applicable; do not publish specific numbers that are unconfirmed.

1. Where the product does not fit ("double-wall tumblers are not for carbonated drinks — the inner seal decides");
2. Lead-time ranges ("7 days for samples, 30 days for bulk, +10 in peak season");
3. MOQ and tiered-pricing logic ("500 pieces minimum; why 500 — the cost of one color change on a single line");
4. Sample process ("sample fee, whether freight is collect, and how many days until shipment");
5. When we say no ("three situations where we would advise against a custom logo");
6. Testing methods ("how a salt-spray test is run" — write only standards from your company's test reports or confirmed by the quality department; never fill in pass values yourself);
7. Parameter explanations ("304 vs 316, and which one food buyers should pick");
8. Inspection and after-sales (inspection flow and response times; compensation and liability follow company-approved contract terms — salespeople must not promise them on their own).

These 8 items share one trait: concrete, verifiable, and hard to copy — the kind of content AI answers tend to consult first. That said, whether you get cited is decided by the platform, the query, and page quality, and is never guaranteed.

Pain point ② (not knowing what to write) ends here.

Four: Don't Get Sidetracked — GEO Has No Magic

Three words, one line each: SEO — getting clicked in search results; GEO — getting cited in AI answers; AI search — entries like ChatGPT, Perplexity, and Google AI Overviews.

Now a fact that can save you tens of thousands: for AI Overviews and AI Mode in Google Search, Google has said officially there is no extra "AI-specific optimization" — no llms.txt needed, no structured data built specially for AI needed (ordinary SEO structured data continues as usual). It is still the most basic SEO: crawlable, indexable, clear content that isn't a duplicate of everyone else's. ChatGPT's and Perplexity's source-selection mechanisms are not guaranteed to match. So the next time someone charges you a fortune promising to "make AI recommend you", feel free to skip it.

Start with three basic pages — the same road as the hands-on SEO guide:

1. A product page that states the product and where it applies;
2. A verifiable spec and delivery page;
3. A trust page with evidence, a contact, and an inquiry entrance.

Once the site stands firm, add FAQ, compliance, logistics, and privacy pages as your product and market require. Be extra careful on certifications: publish only what is real, applicable, and verifiable. FDA registration is not FDA approval (using medical devices as an example; regulatory paths differ by category); ISO writes standards and issues no certificates. For each certificate, state what it is and what it does not mean, along with the certification body, scope, validity, and verifiable number — that is both AI-ready material and your compliance line. New formats like llms.txt are fine to try, just don't treat them as leverage.

Five: Answer One More Question Than Peers

Want to know who AI shows buyers today? Run a light sample: take the 5–8 high-intent questions from Section Two, send each to ChatGPT, Perplexity, and Google, and record which companies get named, which pages get cited, and whether answers stay stable. Repeat on the same day each month.

Two cautions: this only observes "who AI surfaces today" — it is not a ranking and proves no causation; how different AI products pick sources, and who they cite across languages, gets no firm conclusion on this page — sample repeatedly within a target market, a fixed question set, and a fixed time window [needs hands-on testing].

Then "imitate and surpass" — properly defined: add the decision information those pages don't have, not more length. What you genuinely have — fit boundaries, lead times, failure conditions, inspection flows — is the surpass. Never fabricate "exclusive test data": buyers are experts, and invention gets caught on the spot. Borrowing structure is fine; the text, data, and cases must be your own, and every number needs an internal source and an owner.

Finish Sections Four and Five and a new site stops being "written but unread" — because you are answering what buyers were already asking. Pain point ③ ends here.

Six: How to Tell Whether It Worked

House rule first: being cited by AI is a process metric; inquiries are the outcome metric. A screenshot of "AI recommended us" proves nothing.

Tooling today (September 2026): Google Search Console has launched generative AI performance reports, showing impressions, pages, countries, and more from AI features in Google Search and Discover — they do not cover ChatGPT or Perplexity. OpenAI currently states that links from ChatGPT search results carry an automatic utm_source=chatgpt.com tag [needs hands-on testing: shared, copied, or other entrances may not carry it]. Attribution for each AI product needs its own testing.

At low traffic, what should you watch? Prioritize inquiry quality — one real, well-matched inquiry is more persuasive than any beautiful curve. Add a "How did you hear about us?" single-choice field to your inquiry form; it is a useful supplementary signal, but it cannot replace GSC, analytics, and sales records.

Pain point ④ (not knowing whether it worked) ends here.

📋 Common Pitfalls

Pitfall	Consequence	How to avoid
🔴 Treating "cited by AI" as the outcome	Screenshot bragging, zero inquiries	GSC for Google-side AI exposure, utm tags for ChatGPT, separate records for Perplexity and others; inquiries make the final call
🔴 Fabricating "exclusive data" to surpass peers	Exposed by buyers; credibility gone	Write only what is true; without data, write fit boundaries, lead times, failure conditions
🔴 Feeding raw customer quotes to AI	Leaked names and prices; policy violations	Desensitize before uploading; when unsure, ask the person in charge
🟡 Machine-translating the whole site into 5–6 languages	5× the upkeep; machine translation pollutes every market at once	Pick one market with real order potential and build one localized path (product page + specs + inquiry entrance)
🟡 Buying "get cited by AI fast" services	Money spent, site unchanged	Google officially: no AI-specific optimization — start with crawlable, indexable, clear content
🟢 Copying a peer's text, swapping the product name	Spam risk; neither AI nor Google will cite you	Borrow structure, write your own facts; answer one more question than they did

📚 Further Reading

• 📚 B2B SEO without anxiety: the full execution roadmap after topic research
• 👉 AllinCMS: our recommended way to build a site today
• 📚 Laifaxin AI outreach overview: systematic inquiry follow-up and feedback loops (optional tooling)

🚀 Next

For how to actually produce an article, see 📄 the hands-on SEO guide. Once inquiries pile up and you want to manage them systematically (feedback loops, follow-ups, next-round topics), see 📄 the Laifaxin AI outreach overview — optional tooling, not a requirement of this guide's method.