How reviews shape what AI tells travellers about your destination

Destinations have fought to appear on top of search results—through SEO, ad budgets, content marketing—since the widespread use of the internet.  

So now that AI is doing the heavy lifting on travel planning—with over 90% of global travellers relying on it to shape their trips—what changes for destinations?  

Recently, they’ve been racing to figure out how to show up in AI results—and how to show up well. In fact, according to Sojern’s State of Destination Marketing 2026 report, adapting to AI-driven discovery and visibility has emerged as one of the key challenges facing destination marketers today 

Although this may seem complicated at first, destinations have significant opportunities to influence how they are represented in AI-generated travel recommendations, especially given AI’s heavy reliance on user-generated content such as reviews, blogs, and social media posts.  

Mexico provides a clear example of this trend. Research found that while AI models frequently recommend Mexico as a travel destination, only a small proportion (9%) of the information used to generate those recommendations comes from official tourism sources. Instead, AI systems are far more likely to draw on content created by bloggers, influencers, and real travellers.  

This means the challenge destinations worldwide need to solve isn’t new. It’s one they’ve lived with for years: traveller sentiment and  online reputation.  

In this blog learn:   

• How AI decides what to show users
• Why reviews matter specifically to AI
• What destinations can do about it
• How to know if it’s working.

How AI decides what to recommend 

Traditional searches on the internet worked like a popularity contest. The higher up the podium you stood, the more likely you were to be found. 

AI doesn’t work that way. Models like ChatGPT, Gemini, or Perplexity analyse content from multiple sources, weigh what appears to be more relevant or reliable and then present a synthesized answer in natural language, saving users from having to read and compare numerous websites themselves.  

Evidence for how it chooses those sources comes from researchers at Princeton, Georgia Tech, the Allen Institute for AI, and IIT Delhi, who ran the first large-scale study of exactly this question in 2024. Their research introduced a new framework called Generative Engine Optimization (GEO) and examined how different versions of the same web content performed in AI-generated response 

The researchers tested nine different content modifications and measured how each affected visibility within generative engine answers. Traditional SEO-style tactics such as keyword stuffing offered little benefit. By contrast, adding statistics, citations, quotations, and other signals of credibility consistently improved a page’s prominence in AI-generated responses. 

Depending on the technique and domain, these changes increased visibility by as much as 40%. The findings suggest that, in an AI-driven environment, content supported by evidence and verifiable sources is more likely to be incorporated into generated answers than content optimised primarily around keywords. 

One of the study’s most interesting findings was that the benefits were often greatest for lower-ranked websites. In some cases, pages that would typically receive less visibility in traditional search results gained substantially more prominence once they included stronger evidence signals such as citations and supporting data.  

This suggests a possible democratisation of destination promotion, where visibility depends increasingly on credibility and demonstrated value rather than solely on marketing budgets or brand scale. 

For destinations, this shifts the focus from simply optimising websites to building a strong digital reputation, as AI draws on a wide range of sources including reviews, media coverage, and third-party content. 

It’s worth noting that the landscape is already evolving as generative AI platforms introduce paid visibility. OpenAI recently reported that ChatGPT Ads reached $1 billion in annualised revenue in under 200 days. While advertising remains separate from generated answers, AI discovery may gradually develop some of the commercial dynamics of traditional search. 

Why travellers’ real stories matter more than ever in AI search 

Reviews have long been one of the most trusted sources of travel information. Expedia Group’s 2025 Traveler Value Index found that three-quarters of travellers are willing to pay more for accommodation with better reviews, highlighting the significant role peer feedback plays in travel decisions. 

AI is amplifying that dynamic. 

Think about how people naturally seek travel advice. If you were asking a friend who had already visited a destination, or speaking with a travel agent, you probably wouldn’t ask, “what’s the highest-rated restaurant?” 

Instead, you’d ask: 

• Does it have gluten-free options? 
• Is it family-friendly? 
• Is the beach within walking distance? 
• Does it have sea views? 
• Is it quiet at night? 

These are exactly the kinds of questions travellers are increasingly asking AI. 

The problem is that the answers rarely live in official destination websites or marketing material. They live in reviews. Reviews contain the details, context, and first-hand experiences that help AI answer increasingly specific questions. 

This changes what a “good” review profile means. For years, the focus was on achieving the highest possible rating. Ratings still matter, but AI can look beyond a simple score. 

A high volume of detailed, traveller comments  can be more valuable than a near-perfect rating alone. In many cases, a mix of positive and critical feedback, paired with thoughtful responses, creates a more credible and trustworthy picture than a flawless stream of praise. 

Review freshness matters too. A steady stream of new reviews helps AI recognise that a business remains active, relevant, and consistently delivering experiences today, rather than relying on a reputation built in the past. Thoughtful and timely responses add another layer of credibility, demonstrating that the business is engaged with its customers and attentive to feedback. 

In other words, the question is no longer “How many stars do we have?” It’s “Have enough real people described their experience in enough detail for AI to understand who we are and who we’re right for?” 

How destinations can strengthen their AI presence 

A destination cannot control every review, reply to every comment, or manage the online reputation of every tourism business.  

The signals that shape online perception are spread across hundreds, sometimes thousands, of independent operators.  

That means the goal is not to create reviews. It is to understand, strengthen, and amplify the signals that already exist. 

1. Use travellers’ real feedback as destination intelligence

Reviews are often treated as a customer service issue.  

In reality, they are one of the largest sources of visitor insight available. Hotels can see hotel reviews. Restaurants can see restaurant reviews. Only a destination organisation can step back and see the full picture.  

• What are visitors consistently praising?  
• What surprises them?  
• What complaints appear repeatedly?  

The answers can reveal how travellers actually experience a place and interacts with the destination’s tourism offering and any of its Points of Interest, not how marketers assume they experience it.  

This is where dedicated travel intelligence platforms for destinations come in. Data Appeal Mabrian aggregates and analyses review and traveller sentiment data across accommodation, restaurants, attractions, and transport at a destination-wide scale—something no single business can do on its own.

2. Turn recurring themes into destination strategy

If thousands of reviews mention walkability, local food, authenticity, friendliness, sustainability, or cultural experiences, those themes should influence destination marketing and product development and will be taken as an asset for AI engines. 

Likewise, if visitors repeatedly complain about transport, overcrowding, accessibility, or wayfinding, that feedback should not stay buried inside review platforms. Reviews provide a continuous stream of real-world visitor feedback. Smart destinations use it to identify opportunities and challenges, and guide decisions.

3. Help local businesses improve review quality, not just quantity

Most destinations already offer training on digital marketing, Google Business Profiles, social media, and online visibility. The next step is helping businesses understand what makes reviews useful in an AI-driven environment. Encourage operators to: 

• Ask guests specific questions rather than simply requesting a review 
• Encourage detailed descriptions of experiences 
• Respond to both positive and negative feedback 
• Maintain a steady flow of recent reviews 
• Build a presence across the platforms their customers actually use 

4. Publish evidence-based destination content

Individual businesses can only tell part of the story.  

A destination organisation can analyse feedback across accommodation providers, restaurants, attractions, events, transport services and any type of point of interest, to identify broader patterns and trends.  

That information can then be turned into reports, articles, dashboards, and destination insights supported by data.  

This is particularly valuable in the context of AI search, where, as we’ve seen previously, content backed by statistics, citations, and evidence is more likely to be surfaced in AI-generated responses. 

5. Keep official information accurate and current

AI systems still rely heavily on the information available online.  

If event calendars are outdated, attraction details are inaccurate, or practical visitor information is incomplete, those issues can find their way into the answers travellers receive.  

Maintaining accurate destination data may not be glamorous, but it remains one of the most important things a destination can do.

6. Measure reputation, not just reach

For years, destination marketing focused on impressions, clicks, rankings, and website traffic.  

Those metrics still matter.  

But AI introduces a new question: What story is the internet telling about your destination?  

The answer increasingly depends on reviews, visitor experiences, online conversations, and third-party content.  

Data Appeal Mabrian tracks sentiment and destination image over time by continuously analysing review data at scale, giving tourism boards an ongoing, evidence-based answer rather than a one-off snapshot. 

How to know if it’s working  

Everything so far is a mechanism, not a guarantee.  

A destination can do all of it—better reviews, better training, better published content—and still have no real sense of whether any of it is changing what AI actually says.  

That’s the gap most destinations sit in right now: GEO tracking is nowhere near as precise or comprehensive as SEO tooling. 

A rough baseline is easy enough to build—pick a handful of realistic traveller questions, run them across ChatGPT, Gemini, and Perplexity each month, and note what comes back. But that only tells you whether something changed, not why. 

Where it gets harder is turning that baseline into strategy—connecting what AI is saying back to the sentiment sitting underneath it, across thousands of reviews, in multiple languages, updated in real time. That’s a different scale of problem than a monthly spreadsheet can handle. 

It’s also the gap Data Appeal Mabrian can close. The platform analyses traveller reviews in real time to surface what’s actually driving a destination’s reputation—strengths and weaknesses across hospitality, food and drink, attractions, and transport—and turns that into concrete, destination-specific recommendations rather than a raw pile of data. Additionally, the platform’s Smart Insights AI assistant feature further enhances this capability by providing summaries, recommendations, and key review themes. 

For a destination trying to work out whether its AI visibility efforts are landing, that’s the missing half: not just checking whether AI mentions you, but understanding why it’s saying what it’s saying, grounded in the same review evidence this whole piece has been about. 

The two questions destinations need answered are simple to ask and hard to answer alone: what is AI already saying about us, and what’s actually driving that? The first can start with a diagnosis. The second is where dedicated destination intelligence earns its place. 

How Data Appeal Mabrian can help  

Want to understand what’s actually driving your destination’s reputation?  

Data Appeal Mabrian provides destinations with real-time review and traveller sentiment intelligence across hospitality, food and drink, attractions, and transport, alongside market demand, air connectivity, competitiveness, spending impact, events and sustainability data, all turned into destination-specific recommendations you can act on. 

You’ll find more examples of how our data is helping destination support their local businesses and operators to improve their online presence on our blog. Helsinki especially, uses visitor feedback and reputation insights to work directly with local tourism operators, helping them improve their online presence and respond to the factors shaping visitor perceptions. The result is a more coordinated approach to enhancing the visitor experience and strengthening destination reputation and AI positioning.