We’ve just rolled out a major update to D / AI Destinations – our destinations’ marketing and management platform, making it easier than ever to understand what visitors love (or don’t) about your destination.
With enhanced AI-driven topic detection, the platform now analyses traveller feedback more deeply, automatically categorising insights by theme and providing clear, actionable recommendations in a simple “do this, do that” format.
You’ll also spot trends faster to boost, or improve your reputation according to what you’d like to be reputable for, and make overall smarter decisions.
Managing a destination is complex, but with this update, you’ll have the insights you need to focus on what truly matters.
In this blog we’ll look at:
- What you need to know about the new Semantic Analysis update
- What it means for you as someone working in destination management
- Practical use cases
- Real-world examples
What you need to know about the new Semantic Analysis update
The latest update to D / AI Destinations introduces an advanced Semantic Analysis feature based on LLMs, designed to significantly enhance how you interpret and act on visitor feedback—resulting in a more refined, AI-driven approach to understanding your destination’s reviews.
This makes it easier to identify key themes, assess sentiment, and track trends.
It analyses reviews using AI-powered topic detection and sentiment analysis, automatically sorting them into two key categories: topics that are frequently discussed positively (“What people love”) and those that are frequently mentioned but with less positive sentiment (“What needs to be improved”).
This allows you to see exactly what aspects of your destination are resonating with visitors and which areas require attention.
As usual, you can now track historical sentiment and geographic trends, helping you see how feedback changes over time and across regions.
The result is a comprehensive, data-driven view of your destination’s performance, empowering you to make informed decisions and improve strategies more efficiently.
Topic analysis: What are the new features?
Overview: Get tips on what people love, or what you need to improve—at a glance
The Topics Analysis feature uses LLM to dive into a destination’s reviews, uncovering and categorising the main themes that visitors frequently mention.
These topics are split into two categories:
- Those praised by visitors (“What people love”)
- Those discussed with less favourable sentiment (“What needs to be improved”).
This analysis provides immediate, actionable insights, pinpointing a destination’s strengths and areas for improvement.
Additionally, it offers customisation by allowing the addition of custom topics, enabling a more tailored approach to management strategies.
With the ability to monitor sentiment trends over time and across different locations, it empowers decision-makers to make data-driven choices that reflect both current visitor feedback and broader geographical patterns.
Most relevant topics: What are people talking about, and what are they saying?
This feature allows you to analyse all topics and pinpoint the most relevant ones, categorising them based on factors like rating, performance trends, digital trace volume, and sentiment.
It presents a comprehensive list of topics (e.g., Rooms, Parking, Services), making it easy to track public perception and spot changes over time. The tool helps identify trends and priorities by highlighting areas that are performing well and those that need attention, such as a decline in sentiment for Parking.
With detailed insights on ratings and sentiment, it supports data-driven decisions, guiding where to make targeted investments, such as improving Cleanliness or Costs.
Additionally, it enables continuous reputation monitoring by tracking each topic’s performance and interaction over time, giving you greater control over how your destination is perceived.
Wordcloud: A quick overview of the most-discussed topics
The Word Cloud offers a visual representation of the most discussed topics related to a destination, highlighting each one based on its relevance and sentiment.
It provides an immediate overview of what matters most to visitors, giving you a quick snapshot of priorities. This tool helps identify both critical areas with negative sentiment (e.g., Cleanliness, Parking) and successful areas with positive sentiment (e.g., Location, Services).
It’s also an effective communication tool, offering a clear, concise way to present insights in reports and presentations for both internal and external stakeholders.
Add your custom topics
A new feature that allows the analysis of a destination’s reviews based on customised topics (“custom topics”), reprocessing them with the Topic Detection algorithm to identify, categorise, and determine the sentiment of text segments related to the newly defined topics:
- Precise analysis: Focus on targeted topics (e.g., specific events, local issues, marketing initiatives) to gain detailed insights.
- Timely monitoring: Ability to add or remove topics at any time, allowing for quick reactions to emerging trends.
- Strategy optimisation: Improved understanding of what works or needs improvement through direct feedback from visitors.
- Decision support: Tailored reports on sentiment related to specific topics, aiding in investments and concrete actions.
Smart Insights: Turning reviews into actionable tips
The new semantic analysis based on LLMs is not the only new feature we are introducing: we have also implemented a new functionality that will radically change your destination management!
Smart Insights is a powerful feature designed to extract meaningful, actionable knowledge from unstructured review data. Leveraging the capabilities of LLMs, it analyzes thousands of textual reviews to provide Destination Managers with clear, data-driven guidance—all without the need to manually sift through feedback.
What it does
Smart Insights transforms complex review content into four key components:
- Summaries: Quickly grasp what visitors are saying. This feature distills extensive review content into concise overviews, spotlighting recurring sentiments, praise, and concerns—so decision-makers can focus on what matters most.
- Recommendations: Go from insight to action. Based on sentiment analysis and review patterns, the system offers tailored suggestions to help improve visitor satisfaction and operational efficiency.
- Most-discussed topics: Know what everyone’s talking about. The feature highlights the themes and topics that appear most frequently in reviews—whether positive or negative—helping teams to identify both strengths and problem areas at a glance.
- Open questions: Ask and receive intelligent answers. Destination Managers can pose specific questions (e.g., “What do visitors think about cleanliness?”) and receive instant, LLM-generated responses based entirely on the content of the reviews.
Key advantages
- Decisions rooted in authentic visitor feedback: Smart Insights ensures that decisions are grounded in what real visitors are actually saying. By surfacing trends directly from user reviews, Destination Managers can easily identify what guests value most—and what’s falling short. Whether it’s cleanliness, customer service, accessibility, or pricing, the insights reflect unfiltered visitor sentiment.
- Save time without compromising depth: Analysing thousands of textual reviews manually is time-consuming and inconsistent. Smart Insights automates this process, delivering a comprehensive yet precise view of visitor sentiment in a fraction of the time. This enables teams to focus on strategic decisions, armed with clear evidence and accurate summaries.
- Tailored operational strategies: The insights go beyond surface-level observations. With access to contextualised summaries, specific recommendations, and the ability to ask open-ended questions, destination teams can adapt their strategies to meet actual needs. Whether refining services, adjusting marketing messaging, or improving infrastructure, actions can be directly aligned with qualitative visitor feedback.
12 ideas to boost your strategy using Semantic Analysis and Smart Insights
1. Improving underperforming areas based on visitor sentiment
Example: A city notices consistently negative sentiment around “public transport cleanliness” in reviews. With this insight, local authorities invest in regular deep cleaning and launch a campaign to promote the improvements.
2. Prioritising investment based on most-loved aspects
Example: Reviews show high praise for “green spaces” in a city center. The destination chooses to invest further in urban parks and promote this feature in marketing materials.
3. Monitoring the impact of a new event or campaign
Example: A coastal town launches a summer music festival. By adding it as a custom topic, managers track visitor sentiment and feedback, learning that attendees love the atmosphere but complain about parking access.
4. Tailoring strategies by sector (hospitality, retail, etc.)
Example: A tourism board uses industry-specific categorisation to learn that hotels are praised for “staff friendliness,” while shops receive lower scores for “customer service.” Each sector receives targeted support and training initiatives.
5. Spotting local success stories through shifting sentiment over time
Example: A once-overlooked neighborhood sees a sharp rise in positive sentiment around food and atmosphere after a street market is introduced. Planners use this momentum to replicate the model in other underperforming districts.
6. Supporting crisis or issue response
Example: A natural site experiences an overcrowding issue. Visitors express frustration about queues and access. With near real-time feedback, managers introduce a timed entry system and see sentiment improve within weeks.
7. Enhancing digital communication and storytelling
Example: A destination uses Smart Insights to extract key themes from positive reviews and turns them into website testimonials and social media content (e.g., “Visitors love our walkability and hidden food spots”).
8. Helping local stakeholders understand their performance
Example: A regional tourism board shares tailored reports with hotel owners, showing that “room cleanliness” is a consistently praised feature, but “check-in process” often frustrates guests. This allows each business to focus on specific improvements.
9. Justifying policy or funding decisions with data
Example: A local council applies for EU funding to improve accessibility. They use sentiment data showing consistent feedback about lack of ramps or signage for people with disabilities.
10. Benchmarking perception against competitors
Example: A city compares sentiment trends with nearby destinations and sees it’s falling behind in “nightlife” topics. The insights prompt collaboration with local venues to enhance and promote after-dark experiences.
11. Prioritizing investment based on standout visitor experiences
Example: Sentiment analysis reveals unusually high praise for a city’s free walking tours, which weren’t a focus of prior marketing. The tourism office allocates budget to train more guides, expand tour routes, and promote it as a signature experience.
12. Tracking trends across geography and time
Example: Sentiment about a historic district steadily improves over six months following restoration works. Authorities use this trend to justify future investment in similar areas.
Get your free D / AI Destinations demo
The new Semantic Analysis based on LLMs and Smart Insights are now part of our comprehensive destination marketing and management platform, D / AI Destinations—a single platform that helps you make sense of visitor feedback, spot emerging trends, and make informed decisions to boost your destination’s reputation.
Want to give it a try?
Start your 7-day free trial today and see how D / AI Destinations can enhance your destination management.
