How Perplexity builds an answer
Ask Perplexity a question and it searches, reads a set of pages, and writes an answer with numbered references to those pages. The answer is constrained by what it retrieved: if the pages it read do not mention you, the answer will not either, and if they describe you wrongly, so will the answer. This is different from an engine answering from training data, and it has a useful consequence. On Perplexity you can see exactly which pages produced a given answer, and therefore exactly what to change.
Perplexity documents its crawler and how to allow or block it in robots.txt. A site that blocks it cannot be a source, whatever else it does well.
Checking your visibility
Ask as a buyer, and keep the sources
Use the same question set you would use for any engine: awareness, comparison, commercial, local and one or two with your brand name. Ask logged out, in fresh threads, more than once, with a neutral location line if your market is local. For each answer keep three things: the text, the list of sources, and the date. Mark whether you are named in the text and whether any of your pages appear in the sources.
Read the sources, not just the answer
The sources are the finding. For every answer, list the domains cited. After fifteen questions you will see the same handful of sites recurring: these are what Perplexity treats as authoritative for your category. If you are absent, they are where you need to be present and accurately described. If you are named but not cited, they are where the engine is learning about you, and where errors must be corrected first.
Check what it believes about you
Ask directly: “what does X do”, “where is X”, “how much does X charge”. Compare each claim with the facts. Wrong claims on Perplexity come with their source attached, so the correction is a matter of following the reference and fixing the page it points to, then checking that your own site states the fact plainly.
What makes a page citable
Perplexity cites pages that it could fetch, read and quote in support of the answer. In practice that means:
- Fetchable. Allowed in robots.txt, not blocked by bot protection, returning the content in the HTML rather than after scripts run.
- Specific. A page about one question (“implant costs in Tallinn”) is more quotable than a page about everything you do. The heading should match the question; the first paragraph should answer it.
- Factual. Numbers, names, places and dates stated in text. Marketing adjectives give the engine nothing to quote.
- Current. A visible date, and content that has not obviously gone stale. Retrieval engines prefer pages that look maintained.
- Consistent. The same facts as your other pages and your third-party listings. Contradictions lower the chance that any one page is chosen.
Structured data helps where it describes something real (an organization, a product with a price, an FAQ); there is no published evidence that it changes citation on its own. An llms.txt file is a proposal no major engine has documented using. Both are cheap; neither substitutes for a readable, specific page.
Reading competitor citations
When a competitor is named and you are not, look at the reference next to their name. It is usually one of three kinds. A third-party page (a directory, a register, a review platform, an industry list): get an accurate entry on the same page or its equivalent. A comparison or “best of” article: find out who publishes it and whether inclusion is editorial. Or the competitor’s own page: open it with JavaScript off and read how it is structured, because that structure is what got it cited.
Why this matters beyond Perplexity
ChatGPT with search and Claude with web search also retrieve pages at answer time, but show less about what they read. Perplexity’s visible sources are the closest you can get to seeing what retrieval finds about your company. A page that is cited on Perplexity is a page that can be retrieved and quoted, which is the same property the other engines need. Fix it once, measure it everywhere.
Our free check puts three buyer questions to ChatGPT and Perplexity and emails you the answers with the sources and your brand marked. The full audit adds Google AI Overviews and Claude, repeat runs, the crawl and citability checks, accuracy flags against your facts, and a fix list. The methodology explains how each engine is queried.