What to do this week

Check your review recency. Look at your Google, TripAdvisor, and top OTA profiles. If your most recent reviews are more than 30 days old, you have a velocity problem that directly affects AI visibility.

Start responding to reviews consistently. Prioritize Google and TripAdvisor. Reference specific details the guest mentioned. These responses become part of the content AI reads.

Ask for detail, not just stars. When requesting reviews, prompt guests to mention what they enjoyed most. Specific language about amenities, location, and experiences creates the signals AI uses to recommend you.

Boost Background

A client in the Southwest had a 4.6-star average on Google and solid occupancy. When we asked ChatGPT and Gemini to recommend hotels in their market, the property didn't appear once. A competitor with a lower rating but three times the review volume and recent TripAdvisor activity showed up in nearly every answer. The higher-rated hotel had 180 reviews, mostly from 2023. The competitor had 900, with dozens from the past 60 days.

That's the pattern we see repeatedly. AI doesn't just look at your rating. It looks at volume, recency, platform breadth, and the language guests use to describe their stay. Reviews have become the single most actionable lever hotels have for improving AI visibility.

Why reviews are now a visibility signal

Every hotel recommended consistently across ChatGPT, Perplexity, and Gemini in the Cloudbeds study of 145 properties maintained strong guest ratings with high review volume across multiple platforms. The average sentiment score among top-ranked properties was 75 out of 100. This wasn't a secondary factor. It was table stakes for appearing in the answer at all.

The reason is mechanical. AI models don't visit your property. They read what others have written about it. Reviews are the richest, most frequently updated source of structured opinion about your hotel on the open web. When a traveler asks "best family-friendly hotel in Scottsdale with a pool," AI pulls from TripAdvisor reviews mentioning families and pools, Google reviews describing the experience, Reddit threads where travelers compared options, and OTA review sections with specific amenity callouts.

Google has been explicit that reviews factor into local search rankings, with review signals comprising over 15% of local ranking factors according to industry research. But the impact on AI visibility goes further. Google's AI Overviews now synthesize review themes directly into search results. If guests consistently mention your breakfast, your spa, or your proximity to a particular attraction, that language shapes how AI describes and recommends your property. Your marketing team doesn't control the narrative. Your guests do.

What AI reads in your reviews

The specific language in reviews matters more than the star rating. AI models parse sentiment at the attribute level, not just the overall score. They identify what guests praise and complain about: room cleanliness, staff responsiveness, noise levels, food quality, location convenience.

This creates both risk and opportunity. If your reviews consistently mention slow check-in or outdated rooms, AI will reflect that in how it positions you. But if guests describe specific experiences, naming the rooftop bar, the concierge who arranged a private tour, the view from room 401, that specificity gives AI concrete details to include in recommendations. Generic five-star reviews that say "great stay" provide almost no signal. Detailed reviews that describe what made the stay exceptional are what AI surfaces.

This is also where management responses matter. Hotels that respond to 40 to 45% of reviews earn double the booking revenue of those that respond less, according to WiserReview's analysis. AI systems recognize active engagement as a positive signal. A thoughtful response that addresses a complaint or adds context increases the content depth of your listing and gives AI more text to work with.

Where your reviews need to live

Platform breadth is as important as volume on any single site. Cloudbeds found that 98% of AI-recommended hotels appeared on YouTube, 97% in travel blogs, and 95% on Reddit.

For reviews specifically, the key platforms are Google Business Profile (the source of 81% of all online reviews according to Birdeye's 2025 data), TripAdvisor (the most cited source in ChatGPT's hotel recommendations), and OTA review sections on Booking.com and Expedia.

A strong profile on one platform isn't enough. AI cross-references across sources. If your Google reviews say one thing and your TripAdvisor profile tells a different story, that inconsistency weakens your signal.