LLM won't read your article from scratch like a man. It cuts the entire web page into a piece that can be created independently, and then picks out the best extracts from it, the last ones that can be created without the previous text, and stuffs them into the resulting answers. So it's decided whether you're going to be quoted, not how deep it is, but what your content is. Lists, tables, short sentences with numbers are won because they are born "in one piece and in one piece."
Why does the format determine the reference rate more than the pen?
When the AI engine answers the question, it follows the process generated by the inspection of Soga. It breaks your page into a chunk, usually a paragraph, a list item or a cell table; then sorts in a similar way, selects a few clips as input for the answer. There is a cruel truth here: if your best arguments are spread out in three paragraphs, and you have to read them in front, the model pulls out some of the words that are broken, and it doesn't work.
There's a few things in common that can be extracted cleanly. In one or two sentences, it finishes its main statement; it takes its own words, and it does not use the word “the above” to refer to others; it puts numbers, terms, conclusions in the same sentence. You'll find that these features are almost the default for lists and tables. In other words, the improved format is not to favour algorithms, but to save the cost of understanding the model.
AI most frequently cited five content formats
Based on Tenten's tracking of Brand Radar's visible implementation on behalf of the B2B SaaS client, the chances of being captured as a source by AI Overviews, Perplexity, ChatGPT, after rewriting the same content into the following format, are clearly high. From height to low, it's about five:
- Structure list (listicle / best-X): Each item is a chunk of its own, and the model can be removed in its entirety, and the answer is, "What's the method?", "What tools are recommended" .
- Comparison table: Put the difference between A and B in the same column and directly address the user's "where the difference is" in the format that is most easily quoted in square brackets.
- Statistics with numbers: In one sentence there are both principals, indicators, numbers, speech integrity, probabilities, models that come out almost zero.
- Original research and firsthand data: your own research, empirical data, case results, there's no second source on the Internet, and models can only lead you.
- Definition answer (Q&A): The structure of a question-and-answer is itself the shape of the model, with the lowest cost of extraction.
Form: AI answer first option for "A and B"
When the user asks "What's the difference between Notion and Confluence," the model would most like to find a table that sets both together. Each cell of the table is a highly structured segment, the field name is equal to the question, the text is equal to the answer, and the language is almost perfect. In practice, a three-to-five-column table of the comparatives scattered in the articles is often a better reference than 500 words. The point is that the field needs to be specific: rather than just "price" "functional", the start-up monthly fee "does it support the SSO "API rate limit" model can go back and fill in the dimensions of the answer.
Numbers and statistics: it's easier to move the whole section.
The model prefers specific, verifiable information when generating answers, because it reduces the risk of it speaking wrongly. The phrase "the response time for the client's service is reduced from 12 hours to 40 minutes after automation" is more likely to be quoted than an entire adjective, because it is a complete fact when it comes with its own principals, indicators and numbers. The key numbers are written as stand-alone short sentences, not buried in long sentences. It is also important to attach the source or premise of this number, and the model (and those who review it behind it) will be more willing to take credit.
Original Research and Answer: The invertible quote Source
The first four formats are reducing extraction costs, and the fifth is creating scarcity. The only data on original research, self-censorship, client cases on the Internet is yours, and when the model answers the relevant questions, there is no choice but to draw on you. And that's why statistics and research content are being quoted over a long period of time. They meet both the conditions of "clean format" and "source only".
The definition of the answer is the shape of the content as a result of a model. Instead of writing an explanation, use "What's GEO?" as a cursor and use 40 to 80 words below to give answers that can be quoted in the whole paragraph. This question-and-answer piece, which complements the FAQPage structure, is equivalent to feeding search engines and AI engines the best digestive format at the same time.
Don't make hard numbers for stuffing tables, and don't crush three points into a false gold sentence. Format services are extractible, not credible; when content fails, they are quoted as harm.— Tenten GEO content team
How do we start today?
Look back at the articles that you're in the highest traffic, but are rarely quoted by AI, probably because they are like essays, not as extractable data. You can do three things first: change the cross-reference to a table; change the key conclusions to a short sentence with a master word and a number; and add three to five defined questions at the end. These changes do not require a rewrite of the whole text, but can directly change the way the model looks at your content.
If you want to know which piece of content is missing in the eyes of the AI engine and which format is missing, you can expect a 30 minute GEO diagnosis (/content). We'll actually run your brand over the visibility of the AI answers and tell you where the next step is most effective.
