ML and AI in Hospitality & Travel: Top Benefits & Use Cases

https://acropolium.com/img/articles/ai-and-ml-in-travel/img01.jpg

Key takeaways

• AI in hospitality industry means implementing Natural Language Processing (NLP), robotic process automation (RPA), computer vision, voice recognition, predictive analytics, or other related technologies.
• The main benefits of artificial intelligence in hospitality include enhanced guest experiences, streamlined operations, and improved decision-making.
• Use artificial intelligence in hotels for recommendation engines, revenue management systems, chatbots and assistants, robot services, or sentiment analysis.

The hospitality industry is undergoing a transformative shift with the adoption of AI. The key driver is the demand to streamline operations and deliver exceptional customer experiences expected from other sectors.

Developing a hotel management system that uses artificial intelligence for hospitality can help you predict, market, and provide services to the right customer at the right time, boosting your revenue in the process.

In this article, we’ll look at:

• The in-depth benefits of AI and ML in hospitality
• How artificial intelligence in hotel industry helps you generate more value and meet customer demands
• The main obstacles to implementing these technologies

What is ML & AI in Hospitality and Travel

Artificial Intelligence (AI) encompasses the simulation of human intelligence processes. At the same time, Machine Learning (ML) involves the development of algorithms and models that can learn and improve from data without explicit programming.

AI technology in hospitality industry works in the following ways:

• Natural Language Processing (NLP) technology understands and generates human language for chatbots, virtual assistants, and sentiment analysis of customer reviews.
• Recommendation systems utilize collaborative or content-based filtering to suggest personalized services, accommodations, and travel itineraries.
• Voice recognition allows the implementation of voice-activated assistants and voice-controlled devices to facilitate hands-free interactions.
• Computer vision enables facial recognition for check-ins, monitoring guest flows, and enhancing security measures.
• Predictive analytics forecasts demand, pricing trends, and customer behavior using ML models.
• Implementing robotic process automation (RPA) for tasks like housekeeping, food delivery, and luggage handling improves operational efficiency.

The global AI in tourism and hospitality market is expected to grow 11,87% annually during 2023-2031. These technologies aim to enrich the guest experience, optimize work, increase efficiency, and adapt services to individual preferences.

The survey, including both consumer and management, showcases a positively correlated side of ML in hospitality industry. For example, guest satisfaction increases from 2.5 points for pre-adoption to 8.7 points for post-adoption. Also, the revenue rises from 1.8 to 7, and the overall efficiency boosts from 1.1 to 6 points.

The Benefits of AI and Machine Learning in the Travel and Hospitality Sector

According to the 2023 Deloitte Hospitality Industry Outlook, 83% of companies reported rising costs and labor shortages as key risks to growth. At the same time, the next industry priority after managing inflationary pressure (86%) is streamlining operations (69%).

Artificial intelligence in travel industry can help your hotel data management system overcome these and other challenges.

Automate Processes and Services

For 64% of customers, speed is as important as the price. Artificial intelligence in tourism can cut an average response time to just minutes with AI-based assistants (chatbots).

65% of service dedicated teams in travel and hospitality use process/workflow automation, and 30% employ artificial intelligence. They report high use of AI and automation for phone communication (85%), email (84%), in-person interactions (80%), social media (75%), and online chat/live support (71%).

AI in the hospitality industry can also help companies plan resources and automate revenue accounting. Talking about examples of AI in tourism, a platform can learn from typical baggage mishandling situations to trace it more effectively. RPA can automate invoice categorization, which would otherwise be performed by trained accountants.

Personalize Customer Experience

Implementing artificial intelligence in hospitality industry can give you customer behavior insights to tailor deals to a customer’s family status, the purpose of visit, favorite cities, and preferred hotel locations.

At the same time, people love expressing their views online. With the right software, you can identify the emotional background of posts, which allows you to see both the positive and negative sides of your business and thus improve your service.

Make Your Staff More Efficient

Artificial intelligence in travel and hospitality industry can bring a personal touch to your whole organization by analyzing guest preferences from their tracking patterns and making real-time recommendations to staff. This, in turn, increases customer satisfaction and builds loyalty.

You can also use NLP-powered speech analytics hotel applications to extract meaningful data from voice interactions between support staff and customers, and use automation tools to free your employees’ time from routine processes.

Detect Fraudulent Activities

Are you afraid for your and customers’ data? It’s not surprising. According to the 2023 Data Breach Investigation Report, external (93%) malicious actors are hunting on payment (41%), credentials (38%), personal (34%), and other (26%) data. And guess what… 100% of cyber incidents in the accommodation and food services sector are financially motivated.

Artificial intelligence in the hospitality industry can evaluate transactions to detect illegal activity.

Optimize Expenses

Natural disasters and technical malfunctions cause thousands of delays every day. Thankfully, advanced algorithms make it possible to predict travel disruptions based on data about weather and flight delays. Many companies also use AI and ML in conjunction with trackers to plan regular services.

Also, you can use AI in hotel industry for predictive maintenance to schedule vehicle repairs, buy replacement parts in advance, and forecast fuel consumption rates for trips.

Create More Value

AI can anticipate guest needs by recognizing patterns like early requests for room cleaning or increased demand for water in rooms that face the road. These are just two AI in hospitality industry examples that can create dynamic clusters of guest types. Increase the likelihood of higher sales and customer satisfaction by analyzing travel goals, price preferences, length of stay, and buying history.

Enhance Decision Making

Predictive AI for hospitality industry forecasts demand patterns based on historical data, seasonality, and external factors like weather and events. Hoteliers optimize pricing strategies, room allocations, and staffing levels with such information.

Additionally, machine learning in tourism facilitates competitive analysis by observing market technology trends, competitor strategies, and customer feedback. Use this data to identify opportunities for differentiation, adjust pricing and marketing strategies, and maintain a competitive edge.

ML and AI Use Cases in the Hospitality and Travel Industry

Let’s turn to some implementation examples of artificial intelligence in hospitality industry.

Recommendation Engines

Implementing micro-segmentation throughout the customer journey can potentially double revenue. For example, a $50 million business experiencing a 3% conversion rate may see its revenue soar to $113 million. However, only 35% of traditional travel companies digitalize more than half of the shopper journey.

Companies use artificial intelligence in hospitality to address customer needs and customize their offerings. Advanced algorithms can learn from a user’s browsing activities and purchase history to provide data-powered recommendations. For instance, they can offer the best hotels, the cheapest flights, alternative dates, and additional services like car rentals.

Example

• Booking.com. The leading hotel booking provider uses ML to suggest the best destinations and hotels based on previous user purchases, as well as the best next actions (taxi, car rental, and other services).

Revenue Management Systems

One of the most popular AI use cases in hospitality is to predict who will pay more for service under certain circumstances. AI-powered revenue management applications can process thousands of factors to sell a product to those who need it at the right time and through the best channel.

Machine learning in hospitality can also predict fluctuations in hotel pricing and property availability using seasonal trends, demand, weather forecasts, special offers from airlines, and hundreds of other factors. This allows companies to adjust the prices to get more revenue automatically.

Example

• Marriott International uses revenue management systems to optimize pricing strategies, inventory management, and demand forecasting across its portfolio of hotels.

AI-Based Chatbots

Companies have long been integrating AI-powered chatbots into messaging apps such as Slack, Telegram, and Facebook Messenger.

A digital assistant use input data, customer-specific info, and other external factors to recommend the best flights. AI in travel and tourism lets people check room availability, get travel ideas, and resolve their issues 24/7, allowing businesses to build better customer relationships.

Example

• Expedia unveiled an innovative travel planning feature in its app, powered by ChatGPT. Users can now receive destinations, accommodations, transportation, and activity recommendations. Additionally, the feature saves discussed hotels to a trip itinerary, simplifying the organization and booking processes for flights, cars, and activities.

Automated Disruption Assistance

Data science can help resolve pressing problems travelers and carriers might face during trips. Artificial intelligence in tourism industry can predict disruptions from weather forecasts and info from carriers. This information is then sent to users and companies so they can plan alternative routes or check for available hotels to spend the night.

Example

• Amadeus. The world-renowned global distribution system uses a data science-powered engine that identifies disruptions and helps address them promptly.

UX Personalization

Adaptive interfaces, homepages, and feeds are extremely popular among streaming platforms like Spotify and Netflix. Not many hotel and travel services are using the full potential of UX personalization yet, so you can get a competitive advantage by implementing it in your platform.

Machine learning in hospitality industry works by processing large volumes of data to create user segment types based on their role (vendor, carrier, buyer, or another partner), location, behavioral patterns, and other factors. A portal can then use this information to adjust the on-screen layouts, interface, and other website elements for different user groups.

Example

• United Airlines. This major US airline has a platform that uses over 150 variables and historical data to adapt the user interface for multiple customer types.

Hotel Robot-Services

Robots in hotels? Why not? Research shows that the most open to this technology are representatives 36-45 years old, traveling as tourists, primarily men, with a master’s degree and an income of 50 to 100 thousand dollars per year. The best adoption of robots is seen in operations like room service, housekeeping, and food and beverage.

What’s more, voice-activated AI in tourism can help guests customize the surroundings and make themselves more comfortable, allowing staff to focus on other curated services.

Example

• At a Hilton in Virginia, a robot named Connie serves as a standout concierge, assisting guests with directions and information about the hotel and local area. It establishes personal connections, listening attentively to client requests and expressing a range of emotions.

Sentiment Analysis

Managing online reputation is crucial in the hospitality industry. Sentiment analysis investigates guest reviews, feedback, and social media posts to gauge customer opinions. Understand whether guests express positive, negative, or neutral views about their experiences.

The symbios of AI and hospitality allow you to identify your strengths and weaknesses relative to competitors, highlighting opportunities for differentiation. Understanding guest preferences and pain points allows you to tailor your offerings to better meet customer needs and preferences.

Example

• Sentiment analysis helps Airbnb hosts understand their business better. They identify areas where their services may not meet expectations and address these issues before they become bigger problems.

The Challenges of Implementing ML & AI in the Hospitality and Travel Industry

AI in travel and hospitality industry can improve user experience in many ways, but you need to know about potential challenges. Despite initial development costs, be ready for:

• Data dependency. AI needs a large amount of data to generate actionable insight, which means it may not be the best option for smaller businesses. Small hotels would need months to collect sufficient info about guests, which is way too ineffective. A system also needs to be able to collect data from disparate sources, including social networks and review platforms.
• Personalization problems. Segmentation technology can divide a user base into relatively large groups of users, but systems need to consider more factors to create a truly personalized experience. You need to use content-based (previous user behavior) and collaborative (preference of similar users) filtering approaches to refine segmentation results with personalized offers.
• Third-party app restrictions. Some data aggregation APIs (like TripAdvisor’s) prohibit you from analyzing data. You should always read the legal terms and conditions before integrating new systems. The most scalable and efficient solution is to create a custom data processing platform, and this requires specific skills and expertise that many developers lack.
• Data security. Travel and hospitality businesses collect a huge amount of personally identifiable information about customers, visitors, and employees, making them a prime target for hackers. Even large channel management platforms and hotel chains have suffered data leaks of millions of files about their customers through vulnerabilities in their systems. It’s imperative to make cybersecurity a part of your platform if you value your reputation and financial well-being.

Acropolium’s Solutions for the Hospitality Industry

Data science and AI in the travel industry can help companies deliver tailored services, automate recurring tasks, lower risks, and consequently boost revenue. However, to take advantage of this technology, you need a reliable and secure platform capable of gathering and analyzing large volumes of data.

Acropolium has close to twenty years of experience working on multipurpose enterprise projects (edtech, healthcare, fintech) of varying complexity, including custom artificial intelligence and tourism systems. Our experience delivering software solutions to HoReCa companies and knowledge of industry-specific challenges means we can easily evaluate your business and digitalize your company.

• For example, we created a cloud-based Big Data processing app for one of our clients. We were initially tasked with creating a graphical interface for the back end, but our R&D department found a way to further automate processes. The result? We managed to improve analysis accuracy and processing time by about 40 percent.
• For a hotel management solution provider, we overcame integration issues, developed a cloud-based property management system (PMS), and made the client’s e-commerce platform. As a result, the number of integrations with booking platforms rose by 82%, the customer base increased by 9.7%, and annual recurring revenue boosted by 14.5%.
• We created a property management system (PMS) software for a rental business to simplify booking and streamline tasks. It improved operational efficiency by 37%, cutting administrative costs by 40%. Features like the built-in booking engine raised booking rates by 30%.

Our IT outsourcing experts can advise you on the advantages of AI for hospitality (middleware, chatbots, speech recognition tools, automatization, or contactless solutions) before getting to work on the solution that’s right for you.

Whether you need legacy system modernization with a relevant tech stack and experienced project managers or build AI in the hotel industry from start to finish. Just contact us to know more about project timelines and budget.

Sources of Information

• Global AI in Hospitality Market
• 2023 Deloitte Hospitality Industry Outlook
• The State of Personalization Maturity in Travel and Dining