Algorithms will help restructure the tourism industry

Cyprus International University (CIU) School of Tourism and Hotel Management Director Prof. Dr. Orhan Uludağ stated that algorithms will change the way the tourism and accommodation industry operates, and noted that they predict that especially tourism business operations and customer experiences will be restructured due to these algorithms.

Uludağ pointed out that recommendation algorithms use machine learning to examine a large number of customer preferences, behaviors and interactions, and added that in this way, businesses can increase consumer satisfaction and loyalty by offering special travel suggestions, accommodation and routes according to individual tastes and interests.

Uludağ drew attention in particular to the following five algorithms: "Predictive analytical algorithms", "Natural language processing (NLP) algorithms", "Dynamic pricing algorithms", "Geo-spatial algorithms" and "Sentiment analysis algorithms".

Noting that predictive analytical algorithms are used to predict historical and real-time data, tourism demand trends, Uludağ said that businesses can thus optimize pricing, resource management and capacity planning by predicting peak seasons, popular destinations and customer preferences.

NLP algorithms allow chatbots and virtual assistants to talk like humans. “During the journey experience, these AI-supported agents can provide quick help, answer questions and offer personalized recommendations,” said Uludağ.

Mentioning that Dynamic pricing algorithms can change prices in real time according to demand, customer behavior and market conditions, Uludağ shared the information, “Dynamic pricing solutions allow companies to maximize revenue, offer promotions during off-peak times and avoid overbooking”.

Uludağ said that geospatial algorithms provide real-time navigation, location-based advertising and augmented reality travel experience by using location data, and that businesses can improve the experiences of travelers with these algorithms.

To conclude, Uludağ stated that analyzing customer evaluations and feedback will help sentiment analysis algorithms to contribute to the areas of satisfaction and improvement, and said, "This information will help companies improve their services and protect their reputation."

Emphasizing that algorithms can also improve personalization, operations and customer satisfaction in the tourism and hotel industry, Uludağ pointed out that the way businesses can stay competitive and satisfy today's tourists can be achieved by following these technologies.