Why Does ChatGPT Recommend One Hotel Over Another? What Hoteliers Need to Know Before Blaming the Algorithm

There are still hoteliers convinced that ChatGPT works like a new search engine, displaying hotels based on who pays the most for advertising or who has the strongest SEO ranking. Nothing could be further from the truth. This simplistic view leads many properties to invest resources in the wrong direction while overlooking what is truly building their digital reputation.

Over recent months, I have carried out dozens of tests using ChatGPT as though I were a real guest. I have asked very different questions: "Which romantic hotel would you recommend on the Mediterranean coast?", "Which one has the best breakfast?", "Which hotel would you choose for remote working?", "Where would you celebrate an anniversary?", "Which boutique hotel offers the best value for money?". The answers constantly change depending on the context of the question, but there is a very clear pattern behind all of them.

What is truly interesting is that ChatGPT does not think like a metasearch engine. Nor does it think like Booking, Google Hotels or TripAdvisor. Its purpose is not to display every available hotel, but to answer which one it considers most suitable for a specific need. That nuance completely changes the rules of the game.

As hoteliers, we have spent years obsessing over appearing first on Google, securing more reviews or improving our OTA scores. All of that remains important, but the arrival of artificial intelligence adds a new dimension: the ability to interpret a hotel's overall reputation and turn it into a reasoned recommendation.

And here we encounter a reality that many have yet to accept: AI does not recommend the hotel that shouts the loudest, but the one that inspires the most trust.

The real criteria ChatGPT uses to recommend a hotel

The first thing to understand is that ChatGPT does not have a secret ranking listing every hotel from best to worst. Nor is there a single formula or an official score.

When a user asks about a hotel, the model tries to identify which property best meets that specific need by using multiple quality and reputation signals, many of them similar to those a very well-informed person would use.

The most important include:

• Overall online reputation. Having a 9.2 on Booking or a 4.6 on Google is not enough. ChatGPT interprets the full range of reviews available online, looking for consistent patterns. If hundreds of guests repeatedly highlight the breakfast, cleanliness or human touch, that information carries considerable weight.
• Consistency across all sources. A hotel receiving excellent reviews on Google, Booking, specialist media, blogs and social media conveys far greater credibility than one whose messages are contradictory.
• The property's digital authority. It is not simply about the volume of content, but its quality. A complete, up-to-date and information-rich website makes it far easier for AI to understand a hotel's positioning.
• Specialisation. ChatGPT tries to recommend specialists rather than generalists. If someone asks about a hotel for cyclists, wellness travellers, golfers, gastronomic getaways or business trips, it will look for properties clearly associated with that concept.
• Brand consistency. When all communication conveys the same personality, it becomes much easier for AI to understand what that hotel represents.

All of this fits perfectly with an idea I have been advocating for some time: artificial intelligence needs to clearly understand who you are before it can recommend you.

Reviews carry significant weight... but not as much as some believe

One of the most common mistakes is to think that simply accumulating thousands of positive reviews is enough.

The reality is considerably more sophisticated.

Artificial intelligence pays attention to aspects such as:

• The quality of the language used by guests.
• The repetition of positive attributes.
• The absence of major contradictions.
• The evolution of reviews over time.
• The credibility of the overall picture.

A hotel with 500 highly detailed reviews can be far more convincing than another with 5,000 superficial comments.

Moreover, ChatGPT interprets the semantic content of reviews, not just the score.

It is not the same to read:

"Everything was perfect."

as it is to find one hundred comments saying:

"The staff remembered our names from the very first day."

The second statement helps build a very specific identity.

AI looks for stories, not just data

This is probably the most important change.

For years, we have optimised our websites with Google in mind.

Now we must also start thinking about how artificial intelligence interprets information.

When ChatGPT analyses a hotel, it tries to answer questions such as:

• What makes this property different?
• Which type of guest leaves most satisfied?
• What experience does it promise?
• What personality does it convey?
• Why should someone choose it?

The easier those questions are to answer, the greater the likelihood that a hotel will appear as a recommendation.

Specialisation is gaining ground over the "hotel for everyone"

One particularly curious observation that repeatedly emerges from my tests is that AI avoids recommending overly generic hotels.

When a property tries to be all of the following at once:

• A family hotel.
• A romantic hotel.
• A business hotel.
• A wellness hotel.
• A gastronomic hotel.
• A sports hotel.

It ultimately becomes difficult to classify.

However, when a hotel communicates clearly:

"We are the ideal hotel for couples seeking tranquillity by the sea."

AI immediately understands its value proposition.

In hospitality, we have been talking about segmentation for years.

Artificial intelligence turns that segmentation into an even more decisive factor.

Owned content matters more than we imagine

Many hotels still publish offers only.

However, ChatGPT understands those properties far better when they create quality content about:

• Guest experience.
• Gastronomy.
• The destination.
• Local events.
• Sustainability.
• Design.
• The building's history.
• The team.

All of that content helps build a much richer identity.

Experience still comes before technology

There is a certain obsession with the idea that AI will favour only the most technologically advanced hotels.

I do not believe that.

In fact, many of the tests show exactly the opposite.

Artificial intelligence tends to highlight deeply human aspects:

• Personalised service.
• Hospitality.
• The ability to resolve problems.
• Authenticity.
• The team's empathy.

Technology helps.

But recommendations stem from the experience guests perceive.

There is something paradoxical about artificial intelligence ultimately recommending precisely those hotels where people do their jobs best.

Trust will be the new SEO

If I had to summarise in a single sentence how I believe hotel visibility will evolve in the years ahead, it would be this:

Structured reputation will progressively replace traditional ranking.

SEO will not disappear.

Neither will Google or OTAs.

But a new layer will emerge, where the decision will no longer depend solely on who occupies the first position, but on who inspires the greatest trust when artificial intelligence analyses all available information.

This will force many hotels to rethink their digital strategy.

Having a good website will no longer be enough.

They will need to ensure that the whole internet tells the same story.

And that story will need to be true.

Because artificial intelligence may occasionally make mistakes, but it has an enormous ability to detect inconsistencies.

Perhaps that is precisely the best news for our sector. For years, we have repeated that reputation is built one stay at a time. Today, we are beginning to see that it is also built one response at a time. And when a guest asks ChatGPT where to stay, AI does not invent a reputation: it summarises it.

At its core, artificial intelligence is restoring prominence to the most classic principles of hospitality. Operational excellence, brand consistency, specialisation and genuine guest satisfaction carry more weight than any marketing artifice.

The best strategy for appearing in ChatGPT recommendations is not to optimise for artificial intelligence, but to manage the hotel in such a way that every guest, journalist, supplier or employee describes the same experience in similar words. When that happens, AI simply does what it does best: identify patterns and recommend what inspires the greatest trust.