<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Review Platforms on palmtree.ai Blog - AI Visibility for Travel Businesses</title><link>https://blog.palmtree.ai/tags/review-platforms/</link><description>Recent content in Review Platforms on palmtree.ai Blog - AI Visibility for Travel Businesses</description><generator>Hugo -- 0.157.0</generator><language>en</language><lastBuildDate>Fri, 02 Oct 2026 14:52:00 +0200</lastBuildDate><atom:link href="https://blog.palmtree.ai/tags/review-platforms/index.xml" rel="self" type="application/rss+xml"/><item><title>Citation Geography: Who AI Travel Planners Actually Read Before They Recommend Your Hotel</title><link>https://blog.palmtree.ai/posts/ai-travel-citation-geography-hotels/</link><pubDate>Fri, 02 Oct 2026 14:52:00 +0200</pubDate><guid>https://blog.palmtree.ai/posts/ai-travel-citation-geography-hotels/</guid><description>Every AI hotel recommendation is assembled from a retrieval pass over a source map that differs by engine — and mostly is not your website. Perplexity&amp;#39;s citations are led by Reddit overall but pivot to TripAdvisor and Yelp on commercial intent; Google AI Overviews leans on YouTube; Wikipedia holds 8.9% of citation slots in a 51,723-citation cross-engine study; and prompt intent swaps the source mix entirely — review sites lead solo-travel prompts while safety blogs dominate women&amp;#39;s solo travel queries (Meltwater GenAI Lens, June 2026). Here is the engine-by-engine citation map, the 30-day freshness rule, the model-variance trap, and a five-step citation-coverage playbook for hotels, tour operators and DMCs.</description></item></channel></rss>