Your website was written for a crawler. Short paragraphs, a keyword in the heading, a meta description of exactly the right length, a chirpy paragraph about your commitment to quality.
That website is now being read by something else entirely, and it hates almost everything on it.
AI assistants do not rank pages. They extract statements. They pull sentences out, check them against other sources, and reassemble them into an answer with a name attached. If your page contains no extractable statement, you are not competing badly. You are not in the pool.
The research on what gets extracted is unusually consistent, and it comes down to three edits.
Citing sources lifts visibility in AI answers by around 40%. Adding hard statistics lifts it around 41%. Adding real quotations lifts it around 28%.
Almost no business website does any of the three.
Edit one. Put a number in it.
Open your main service page. Count the numbers. Not the phone number and not the year you were founded. Numbers that describe what you do or what happens when you do it.
Most pages have zero. They have adjectives instead. Fast, reliable, affordable, experienced, trusted.
Adjectives are unquotable. A model cannot repeat "we are reliable" as a fact, because it is not one. It can repeat "we respond to commercial callouts within four business hours across the Central Coast" all day long, because that is a claim with an edge on it.
Go through your key pages and convert every adjective into a measurement.
- "Fast turnaround" becomes "most jobs completed within five working days."
- "Affordable" becomes "typical projects run between four and nine thousand dollars."
- "Experienced" becomes "over 600 installations since 2014."
- "Trusted" becomes "142 Google reviews at 4.9 stars."
Every one of those is a sentence an assistant can lift verbatim to justify recommending you. Every adjective you replace is one less reason for the model to reach for a competitor who was more specific.
A model cannot quote a feeling. It can only quote a fact. Every vague sentence on your site is a sentence that will never be read aloud to a buyer.
Edit two. Quote a human, by name.
Quotation marks do something specific to a language model. They mark a passage as attributable, self contained and safe to reproduce. That is why quoted content gets pulled through at a materially higher rate.
You do not need to interview an industry analyst. Three sources are sitting in your business right now.
Yourself. A short, opinionated, named quote in the middle of a page. "We stopped offering the cheap option in 2023 because it was generating 80% of our warranty callbacks, says Kendall King, founder." That is quotable, attributable and human.
Your customers. Real testimonials with a full name and a specific outcome, published as text on the page rather than trapped inside an image or a third party widget the model cannot read.
Your team. The person who actually does the work usually has the most quotable sentence in the building, because they talk about the job rather than the marketing of the job.
Edit three. Cite where things came from.
This is the one businesses resist hardest, because linking out feels like sending people away. That instinct is a decade out of date.
Citation does two things. It signals to a model that the page is assembled from verifiable material rather than invented, and it places your page inside a network of sources the model already trusts.
Practically, it means when you state an industry figure, say where it came from and link it. When you refer to a standard, a regulation or a warranty term, name the document. When you make a claim about typical results, say what it is based on.
A page that reads like a well researched briefing gets treated as a source. A page that reads like a brochure gets treated as marketing, and marketing is exactly what these systems are built to filter out.
The structure that makes extraction easy
Beyond the three edits, formatting decides whether a model can cleanly lift what you wrote.
Lead every page and section with a direct answer in the first two sentences. Not context. Not a warm up. The answer, then the explanation.
Use headings that are literally the questions people ask, then answer them immediately underneath. A model matching a user's question to a heading it recognises is doing pattern matching, and you can just hand it the pattern.
Keep statements self contained. "As mentioned above, this applies here too" is worthless to an extraction system, because the sentence means nothing on its own. Repeat the subject. It reads slightly redundant to a human and perfectly to a machine.
And define your terms plainly, once, near the top. Definitions are among the most frequently extracted passages on the entire internet.
A warning about overcorrecting
One caution, because this advice gets taken too far.
Writing for extraction does not mean writing like a database. Pages stuffed with disconnected facts and no argument read badly to humans, and humans are still the ones who decide to pay you.
The goal is a page that works twice. A person reads a clear, persuasive argument. A machine finds a dozen clean, quotable facts inside it.
The good news is these rarely conflict. Specific writing with real numbers and named sources is simply better writing. The extraction benefit is a side effect of doing the thing you should have been doing anyway.
Do this on five pages, not fifty
You do not need to rewrite the site. Pick the five pages tied to actual revenue.
For each, spend an hour. Replace every adjective with a number. Add one named quote. Cite one external source properly. Rewrite the opening two sentences so they answer the question in the title. Convert the headings into the questions your customers actually ask.
Five hours of work, on the five pages that matter, against a system that is currently deciding what to tell buyers about your industry.
Your competitors are still adding keywords to their meta descriptions. Let them.