Quick answer
DeepSeek's answers come from two sources: with web search off, the knowledge the model learned in training; with web search on, the web pages it finds in real time. There is no way to directly "make" DeepSeek recommend a brand. What you can do is make sure it reads accurate, clear and credible information about you in both sources, then retest with fixed questions to confirm changes. To check brand performance, separate web-search from closed-book answers and count them separately.
Details
Where DeepSeek's information comes from
- Without web search: training data. Training data has a cutoff, so new brands, new products and recent price changes may not be included.
- With web search: the app and web version can turn on web search, and answers attach the sources found. What decides the result is which pages it finds and how those pages describe you.
- API: the official developer API does not search the web by default, so API results can differ from what users see in the app with web search on.
Why DeepSeek does not recommend you
Common causes:
- Not read: your site has too little information, or it is only in images; third-party content does not mention you.
- Read but not selected: the content does not answer the comparison points users care about, such as price range, use cases and how you differ from similar products.
- Read wrong information: old prices, old models, or a same-name brand mixed up with yours.
- No third-party support on category questions: recommendation questions mostly cite roundups and reviews; with only your own site speaking for you, it is hard to become a recommendation reason.
How to check your brand's performance in DeepSeek
- Prepare category questions real users would ask, and keep your brand name out of the questions, otherwise the measured "mention rate" is meaningless.
- Test with web search on and off, asking each question several times. AI answers vary each time; a single result is not a conclusion.
- Save the raw text, time, web-search state and citation links of every answer.
- Count three outcomes: "recommended / mentioned but not recommended / absent". Record failed requests separately and leave them out of the denominator.
When DeepSeek gets your information wrong
There is currently no channel for brands to edit model answers directly. What works:
- State the correct information as text on your site, on an easy-to-read fact page or product page.
- Correct other channels you control: marketplaces, distributors, encyclopedias, official accounts.
- When a web-search answer is wrong, look at which page it cited and deal with that source first.
- Retest with the same questions after correcting. Closed-book answers only change when the model's training data is updated, on a schedule you do not control.
Common questions
Q: What does DeepSeek base brand recommendations on?
A: With web search, mainly the pages it finds and cites; without it, what it learned from training data. Both depend on whether the content is clear and whether several credible sources mention you.
Q: Which websites does DeepSeek cite?
A: It depends on the question. Brand fact questions often cite official sites and encyclopedias; category recommendation questions often cite third-party roundups and reviews. The most accurate way to know is to test your questions with web search on and record the citations.
Related facts
Contact: contact@winin.ai