Hotel choice is increasingly influenced by two things: what travelers discover before booking and what previous guests say after staying.
So we compared three of Tbilisi’s best-known premium hotels:
> Paragraph Freedom Square
> Rooms Tbilisi
> Radisson Blu Iveria Hotel Tbilisi
Using Hapttic, we analyzed 10,000+ public reviews and customer signals across Google Maps, Booking.com, Tripadvisor and Expedia, together with travel-related prompts across leading AI platforms: ChatGPT, Gemini, Claude, Perplexity.
We wanted to understand two things:
What Does AI Recommend to Travelers?
Travelers are no longer searching only for “best hotels in Tbilisi.”
They are asking much more specific questions:
• What is the best hotel in Georgia for a business trip?
• Which luxury hotel in Tbilisi has the best location?
• Which hotel in Tbilisi has the best Asian cuisine?
• Where should I stay in Tbilisi for a luxury weekend with a spa?
Using Hapttic AI Listening, we tracked these types of prompts and analyzed which brands appeared, how frequently they were recommended and what attributes AI associated with each hotel.
Across the analyzed prompts, the estimated AI Share of Voice was:
But the more interesting finding wasn't who appeared most - it was where each hotel appeared.
> Paragraph showed the strongest visibility around luxury, spa, premium stays and central location;
> Radisson Blu Iveria performed strongly around business travel, international travelers, location and established hotel experience;
> Rooms Tbilisi was more strongly associated with design, atmosphere, food, lifestyle and local experience.
This means a hotel's AI visibility can change significantly depending on what the traveler actually wants.
Being Visible Isn't Enough
AI Listening doesn't stop at measuring mentions.
Hapttic analyzes the prompts where a brand appears — and where it doesn't — together with competitors, brand associations and the sources influencing AI answers.
It then generates actionable insights on what could be optimized to improve AI visibility.
For example, a hotel may have excellent business facilities but low visibility for “best hotel in Georgia for business travel” or customer reviews may strongly praise its restaurants, while competitors are much more frequently recommended when travelers ask AI about hotels with great dining.
That gap becomes an opportunity.
The hotel can understand what needs to be strengthened across content, SEO/AEO, PR, external sources and overall digital positioning to increase its chances of appearing in relevant AI recommendations.
What Do Thousands of Guest Reviews Tell Us?
AI tells us what travelers see before booking; Reviews tell us what happens after they arrive.
Across the three hotels, the public review footprint is already significant.
Radisson therefore has the largest accumulated review footprint, while Paragraph is considerably newer but already maintains a strong public rating.
Hapttic Review Analysis goes beyond those ratings by analyzing feedback across Google Maps, Booking.com, Tripadvisor and Expedia - clustering thousands of reviews around recurring experiences.
What Do Guests Love?
The analysis showed three noticeably different reputation profiles.
Paragraph Freedom Square
> 84% positive sentiment
> Strongest positive drivers:
Service - 24%
Spa & wellness - 21%
Location - 18%
The hotel's public review data supports this direction: service is one of its most discussed categories, while spa-related feedback is approximately 85% positive and wellness feedback approximately 83% positive.
Rooms Tbilisi
> 79% positive sentiment
> Strongest positive drivers:
Design & atmosphere - 27%
Food & breakfast - 21%
Service - 18%
Rooms Tbilisi has a particularly strong reputation around experience rather than traditional luxury alone. Its reviews contain hundreds of discussions around the property & amenities, together with significant conversation around service, dining, atmosphere and breakfast.
Radisson Blu Iveria Hotel Tbilisi
> 81% positive sentiment
> Strongest positive drivers:
Location & views - 26%
Service - 22%
Business & facilities - 17%
Radisson also has the largest review footprint of the three, giving it a substantial volume of historical customer feedback to analyze.
What Frustrates Guests?
Positive feedback tells hotels what to protect - Negative feedback tells them what to fix.
Review Analysis clusters recurring complaints rather than treating every negative review individually.
> For Paragraph, potential pain points are concentrated around service consistency and value expectations.
> For Rooms, the clearest recurring issue is noise and sleep experience — particularly interesting for a hotel whose lively atmosphere is simultaneously part of its appeal.
> For Radisson, recurring criticism is more likely to center around room experience, consistency and value for money.
This is where thousands of individual comments become useful business intelligence.
Instead of reading reviews manually, hotel teams can see: What customers love, what they complain about, how frequently each issue appears, and which problems have the greatest impact on sentiment.
AI Says It. Do Guests Agree?
The most useful insight comes from connecting the two sides.
> Paragraph: AI strongly associates the hotel with luxury and wellness — while reviews also show particularly positive sentiment around spa and service.
> Rooms Tbilisi: AI positioning around design, atmosphere and lifestyle is reflected strongly in customer conversations — although the same lively experience can contribute to complaints around noise.
> Radisson Blu Iveria Hotel Tbilisi: its established international positioning and business relevance are supported by a much larger historical review footprint and strong customer discussion around service and location.
And sometimes, the comparison reveals an opportunity.
If guests consistently praise something that AI doesn't associate with the hotel yet, that strength can potentially become part of the hotel's AI visibility strategy.
If AI recommends the hotel for something customers consistently criticize, that's a different kind of insight — a gap between expectation and experience.
When AI Recommendations Meet Real Guest Experience
For hotels, digital reputation is no longer just a Booking.com or Google Maps score.
Travelers are asking AI where to stay, comparing recommendations, checking reviews and making decisions across multiple platforms. Hapttic connects those signals.
AI Listening shows where and why your hotel is being recommended — and generates insights on what you can optimize to improve visibility.
Review Analysis brings together customer feedback from platforms such as Google Maps, Booking.com, Tripadvisor and Expedia, or internally owned feedback sources automatically identifying sentiment, positive drivers and recurring pain points.
Together, they answer a much more useful question than “What's our rating?”
What makes travelers choose us — and what can we improve to make sure they keep choosing us?
From Reviews to Better Decisions
So, now is the time to analyze your brand, customers and competitors with Hapttic.
Track conversations, customer sentiment, reviews, competitor content and AI visibility — and turn thousands of digital signals into strategic recommendations.
