How does Perplexity work differently from ChatGPT?

Perplexity is a search-first AI: every answer it generates is built from live web content it retrieves in real time, rather than from patterns memorised during training. When a user asks “best hotel for families in Dubrovnik”, Perplexity fetches current web pages (travel articles, TripAdvisor listings, hotel websites, review aggregations) and synthesises an answer from them, with numbered citations.

The practical consequence: Perplexity reads your hotel website when it searches your category and city. If your website has good structure, an llms.txt file, clear property descriptions and FAQ content, Perplexity can read and cite it directly. If your website is a Flash-based image gallery from 2014, Perplexity cannot read it and won’t cite it.

What sources does Perplexity read when it searches for hotels?

Perplexity’s hotel results typically draw from five kinds of sources: review aggregators, travel editorial sites, individual hotel websites, Booking.com listing pages and local tourism board sites.

  • TripAdvisor and similar review aggregators (very commonly cited)
  • Travel editorial sites (Condé Nast Traveller, Lonely Planet, local guides)
  • Individual hotel websites (if well-structured and text-rich)
  • Booking.com listing pages
  • Local tourism board websites

The weighting varies by query. Broad category queries (“luxury hotels in Tokyo”) tend to surface editorial sources. Specific attribute queries (“hotel in Tokyo with indoor onsen, not a chain”) are more likely to surface individual hotel websites and specific review content.

Why do Perplexity’s citations matter for a hotel?

Because Perplexity shows numbered citations for every claim in its answer, a cited hotel gets a direct referral path: the user clicks straight through to wherever Perplexity read the information, whether that is your own website, TripAdvisor, or an editorial article, rather than landing on a booking platform first.

For direct booking strategy, Perplexity visibility is particularly valuable for exactly that reason.

How can a hotel improve its Perplexity visibility specifically?

The highest-leverage actions for Perplexity visibility are a readable hotel website, an llms.txt file, an active TripAdvisor presence, and coverage on editorial travel sites.

A readable hotel website. Text-rich, well-structured, with a clear property description, room descriptions, location page and FAQ. Avoid JavaScript-heavy pages that render slowly or block crawlers.

An llms.txt file. Perplexity’s crawler respects llms.txt. This file gives the crawler a clean, authoritative summary of your property to use when generating answers. What is llms.txt for hotels explains how to create one.

TripAdvisor presence. Perplexity cites TripAdvisor frequently. A complete, active TripAdvisor listing with a high review volume helps ensure your property surfaces in Perplexity searches.

Presence on editorial sites. A mention in a notable travel publication significantly improves Perplexity visibility for relevant queries, because Perplexity weights editorial sources highly.

See also: Does ChatGPT recommend hotels | What is llms.txt for hotels | Does Gemini recommend hotels | Get found: the technical playbook