In the previous posts on SEO and GEO, everything we discussed was about how to get AI to recommend you. Today let’s go the other way: before rushing to optimize, first go see what AI is actually saying about you. Because customer behavior has already changed — in the past they searched around, paged through a few results and compared for themselves; now they ask AI directly, “Which IT outsourcing companies in Beijing are reliable?” “What is this company like?”, and then contact people based on that one answer. Those few sentences from AI are your new first impression, and there is no “second page” where you can make up for it.
To avoid empty talk, we ran our own company through the test, asking four categories of questions. The results were more complicated than expected: some answers were more complete than what we wrote ourselves, one misspelled our company name, and in the scenario where we should have appeared most, we were not mentioned once. Below we lay out both the test results and the corresponding fixes.
The conclusion first: your company’s image in AI has four kinds of “illness,” and the fixes are completely different
Many business owners do just one thing: open an AI, type in their full company name, and see whether the answer is right. If it is, they relax. The biggest problem with this self-check is that it tests only one of the four illnesses — and the one that matters least for winning customers.
The logic is simple: anyone who types your full company name is almost certainly someone who already knows you (existing customers, people who took your business card, people who heard about you from others). Real new customers type “which IT outsourcing firm in Beijing is good” into AI — whether you appear in that answer is what decides the business.
Our own test: four questions, four different outcomes
The questions and results are below; you can use these same four categories to ask about your own company.
| What was asked | Result | What it shows |
|---|---|---|
| ① Full company name “What does XX Company do? When was it founded, how large is it, what is its business?” |
✅ All correct | It even got the qualifications, the number of software copyright registrations and the service model right — because they are stated in black and white on the official website. AI is essentially repeating the website. |
| ② Product name “What is XX product? Who makes it?” |
⚠️ Correct, but our pricing was “cited” | AI quoted a specific annual fee, and when we checked, it was an example price from one of our own explainer articles. It had been treated as an official price list. |
| ③ Scenario-based need “A 50-person company wants to outsource IT entirely and doesn’t want to buy the equipment itself — is there anyone in Beijing?” |
⚠️ We were recommended, but the name was misspelled | We were placed first in the recommendations, with the business description and the domain name all correct, except that the company name was written with the wrong homophone characters. If a customer searches those characters, they find nothing at all. |
| ④ General recommendations “Which reliable IT outsourcing and operations providers for small and mid-sized companies are there in Beijing?” |
❌ Five companies recommended, and we weren’t one of them | The most painful and also the most valuable finding. A perfect score on branded terms does not mean you appear in the scenarios that win customers. These are two different things requiring two different skill sets. |
The contrast between ③ and ④ is what’s most worth pondering. Both are about “finding IT outsourcing,” yet a specific question (50 people, all equipment included) reaches us, while a broad one (which firms are reliable) doesn’t. The reason is that our website covers specific scenarios like “all equipment included, zero procurement” thoroughly, but has no decent piece of list-style content on “how to choose an IT outsourcing provider in Beijing and what categories exist” — and that is exactly what AI cites when answering broad questions.
A five-minute self-check: ask all four categories, then screenshot and save
- Category 1 · Branded terms: “What does XX Company do?”, “How long has XX Company been around, how big is it?” Check whether the facts are accurate.
- Category 2 · Product/service terms: “What does XX’s YY service include, and how much does it cost?” Focus on where the prices and specifications were copied from.
- Category 3 · Scenario terms: Imitate a customer’s tone — “We’re a 50-person company, we want to …, does anyone in Beijing offer this kind of service?” Check whether you show up when you should.
- Category 4 · General recommendation terms: “Which XX companies in Beijing are reliable — recommend a few.” This one matters most, because it maps directly to how new customers really ask.
We suggest asking at least three platforms (for example DeepSeek, Doubao and Yuanbao, once each) — they draw on different sources, so results can differ widely, and testing only one will lead you to the wrong conclusion. After asking, screenshot and save them, and note the date: that is your baseline; on the next review, the change matters more than the absolute number.
Illness one: you cannot be found at all → what’s missing is a “trustworthy source”
It is not that AI doesn’t know you; it is that there is too little trustworthy information about you online, so it doesn’t dare say anything. The fix is to fill in the basic sources: your website needs an “About Us” page with complete information that search engines can index normally; then get your company information into a few more authoritative places (business registration records, map listings, industry directories, your own news feed or WeChat official account). First solve “does it exist,” then talk about “is it good.” Also confirm one easily overlooked point: don’t let your website block search engines and AI crawlers at the door — if the site isn’t indexed, AI most likely can’t read it either.
Illness two: your name or facts are written wrong → standardize your wording and proactively “set the record straight”
We ran into this one ourselves: everything about our business was correct, but the name was written with the wrong homophone characters. This kind of error usually has two sources: first, a misspelled page really does exist online (old press releases, third-party business directories, typos made when others repost), and second, a company with the same or a similar-sounding name has had its information mixed up with yours. The fix has three steps:
- Find the source: take the sentence AI got wrong and search it — you can usually find the original page containing the error. If you can reach the other party to have it corrected, do so, and fix outdated pages on your own site immediately.
- Standardize your wording: everywhere online (website, WeChat official account, Zhihu, business cards, brochures), use a single version of your full company name, founding year, address and phone number. If they’re inconsistent, AI will pick one — with no guarantee it picks the right one.
- Proactively write out the correct spelling: state your full name clearly on your website, and point out the common misspellings. Few people think of this step, but it is especially effective on machines.
To demonstrate — this next part is our own “name-correction block”:
Our full company name is Beijing Siwen Lide Technology & Trade Co., Ltd., abbreviated as Siwenlide, official website siwenlide.com. Common misspellings include “Si-Wen-Li-De,” “Siwen Lide,” and “Si Wen Li De”; the correct spelling is “Siwenlide.”
The point of writing that one sentence is this: the next time an AI picks up this article, it learns at the same time which version is wrong and which is right. If you don’t write it, all you can do is wait for it to guess.
Symptom 3: Quotes and specifications get misquoted → treat every number on your website as a “commitment”
This is the one most easily overlooked, yet it is the most likely to cause a real dispute. A throwaway example you wrote in an explainer three months ago — “solution X costs roughly a few thousand a year” — will be presented to customers by AI as your official quote. The customer negotiates on the basis of that number, you say “that’s not our price,” and trust takes an immediate hit.
- Whenever you state a price, always include the basis and the date: “As of August 2026, the reference price for an organization of 30 people is approximately…, subject to the actual proposal.” When AI repeats it, it will most likely carry that qualifier along with it.
- Keep example figures separate from formal quotes: in explainer articles, use ranges and the word “reference” — don’t make it read like a price list.
- Outdated figures should either be updated or deleted: leave them alone and they will keep quoting on your behalf out there indefinitely.
- State clearly which source is authoritative: set up a formal services and pricing page on your website and have your other articles point to it. Once the standard is consolidated in one place, AI is more likely to trust that place too.
Symptom 4: Your brand term is answered well, but you don’t show up in recommendation scenarios → add “list-style” content
This is the biggest gap we measured, and it is a common failing at most companies: their websites are entirely “who we are and how good we are,” with not a single piece on “what types of this service exist, how to choose between them, and who each one suits.” When AI answers questions like “recommend a few providers,” what it cites is exactly the latter kind of content — comparative, list-based, with selection criteria, and reading like neutral analysis.
- Write about selection and comparison, not just self-introductions: “How to choose an XX service,” “Which company size each model suits,” “What to watch for in the contract.”
- Answer first: put the conclusion in the opening paragraph; don’t bury the key points in the fifth. If a machine can’t extract it, it may as well not have been written.
- If it can be a list or a table, don’t write it as long prose: structured content is noticeably more likely to be cited.
- Put yourself in the list, but stay objective: state clearly who it suits and who it doesn’t. Content that is all self-praise is actually less likely to be trusted by AI.
- Don’t publish only on your own website: different AIs draw on different sources; adapting the same content into a few versions and distributing them across WeChat Official Accounts, Zhihu, and news accounts makes a big difference in coverage.
Three things you shouldn’t do
- Don’t expect to “complain” to an AI, or for a single edit to take permanent effect. AIs have their own crawling and update cycles; after you make a change it usually takes a while to be reflected, and it may fluctuate. Follow up — don’t just change it and forget about it.
- Don’t write different versions of your company profile on different platforms. Writing a separate version on each for convenience is like handing an AI several contradictory documents; it will only become less certain and more likely to get things wrong.
- Don’t rely on spamming. Mass-publishing duplicate content and stuffing keywords now fails platform originality reviews, does not raise your chances of being cited, and may even get your own website demoted.
Turn it into a fixed ten-minute monthly routine
The value of this lies in consistency, not in how deep you go. We suggest making it a fixed habit: pick one day each month, use the same four question types and the same three platforms, ask once, take screenshots, and note the changes. Focus on three things — whether any facts are stated wrongly, whether any prices are being misquoted, and whether you appear in generic recommendation queries. When you find a new error, add the corresponding content, then wait until the next month to see the change. We run this routine ourselves every month, and today’s article is a record of one such test.
A few common questions
Q: Our company is very small — do we really need to manage what AI says about us?
A: The smaller you are, the more you need to. Large companies have plenty of information and correct errors quickly; a small company has only a handful of items online, so one wrong item has an outsized impact. And the cost is low — mostly it is about writing your website information clearly and consistently.
Q: After I change my website, how long until the change shows up in AI?
A: Usually weeks to months, depending on how quickly the content is recrawled and trusted. The prerequisite is that your pages are properly indexed by search engines — if they aren’t indexed, your changes can’t get through.
Q: What should I do if AI says something unfavorable about us?
A: First distinguish “factual error” from “negative review.” For factual errors, fix them using the source-tracing and standard-consolidation approach above; for negatives that genuinely exist, dilute them with the volume and quality of positive content — there is no shortcut.
Q: If all four symptoms are present at once, which should I fix first?
A: In this order — fix factual errors first (they directly damage trust), then deal with misquoted prices (they can trigger disputes), and finally invest long-term effort in list-style content (which determines customer acquisition).
Want to know how AI is introducing your company to customers right now?
Siwenlide delivers website and SEO/GEO content marketing operations for small and medium-sized businesses in Beijing and the surrounding area: we help you find out exactly how your company comes across in AI — whether any facts are stated wrongly, whether any prices are being misquoted, and whether you appear in the question your customers actually ask — then we fill in the content, consolidate your standards, and distribute across multiple platforms, with monthly reviews to track the changes. We ran this method on our own site first, testing and iterating every month, and today’s article is a real record of one round. Visit siwenlide.com (or take a look at our company profile) or call 400-686-2011 to talk it over.
