Structured Data That AI Search Engines Actually Read

Why Real Questions Beat Generated Ones Questions produced by keyword tools are smoothed. They use category vocabulary, they avoid awkward specifics, and they tend to be the questions everyone has already answered.

The most citable content most businesses could publish already exists, unwritten, in sales calls and support tickets. It is the set of questions people actually ask, with the answers your team gives verbally every week and has never put on a page.

Second, the questions have to keep coming from customers rather than from the content calendar. Within a few months the temptation appears to invent questions to fill a schedule, and invented questions produce exactly the marketing-in-disguise sections that get ignored.

One thing worth deciding before you start is who inside the business will answer factual questions. This work generates a steady trickle of small queries about lead times, price ranges and what you will and will not take on, and an agency that cannot get answers will either stall or guess. Naming one person and giving them twenty minutes a week removes the most common cause of these projects drifting.

Days Thirty to Sixty: Correct the Record Take the ranked list of cited sources from phase one and go through it. On each source, check whether you appear, whether the details are right and whether the platform accepts corrections.

The defensible position is to spend an hour on it if you like, and to spend the rest of the week on the things every system already reads: accessible pages, accurate Organization markup, consistent identity and content a machine can quote.

The complication is that AI systems use several distinct agents for different purposes. One may crawl for training corpora, another may fetch pages live when composing an answer, and llm seo a search provider's traditional crawler may feed both search results and an AI summary.

Keep a small number of deliberately hostile prompts in the set permanently. Questions asking whether you are expensive, slow or suitable only for large clients reveal what the system believes about your reputation, and the belief is often traceable to one specific source. Nobody enjoys reading those answers, and they generate more actionable work than the flattering prompts do.

A quick way to find contradictions is to write out your key facts on one sheet, taken from your structured data, then check that sheet against your about page, your main directory listing and your marketplace account. Doing it manually feels crude and it surfaces the conflicts that validators never flag, because a validator checks syntax rather than whether your founding year matches the one you published elsewhere.

What needs you: factual accuracy. Somebody inside the business has to confirm the numbers, limits and claims before publication, because you carry the consequence of anything untrue being published about your own products.

Accuracy Beats Coverage The most common real defect is not missing markup, it is markup that disagrees with the page or with the rest of the web. A founding year in your schema that differs from your about page. A logo URL that returns a 404. A contact point nobody monitors.

Days One to Fourteen: Find Out Where You Stand Somebody writes fifty questions your buyers would ask, in their words. They run each one three times across the two or three assistants your customers use, from a signed out session, and record the full answers and every source cited.

Where to Put Them Individual pages for questions with real volume and commercial weight, grouped sections for the smaller ones. Both work, and the decision should follow how much there is to say rather than a rule.

Assertions with nothing behind them are weaker than silence, because they introduce a detail that fails verification. The pattern that works is reciprocal: your site names the profile, the profile links to your site, and some independent source associates the two without either of you being involved.

The more useful signal is qualitative and free. Add one question to your enquiry form or your first sales call asking how the person came across you, and read the answers monthly. When people start saying an assistant recommended you, or start repeating a description of your business you did not write, something has changed in a way no dashboard captured.

The output is a spreadsheet and it is the most important document in the project. It tells you whether you are named, whether what is said about you is true, who is named instead, and which pages your category's answers are actually built from.

What Honest Reporting Contains The prompt set, versioned and unchanged since last month. The raw answers, kept in full rather than summarised. Which competitors were named. Which sources were cited. What work was done. What moved, and the specific claim about which work caused it.

A reasonable definition: after two quarters, no increase in mentions on buying intent prompts, no improvement in the accuracy of how you are described, and no new citations from the sources your category's answers are built on. If all three are flat, the work is not landing.