Artificial intelligence (AI) is changing everything we do, including enabling the hotel industry to advance in ways that were never conceivable before. Before AI, online travel agencies (OTAs) defined and monetized every way in which a hotel was marketed online. Each post and listing was monetized to the point where the default position was to work with as many OTAs possible, in a bid to secure the traffic and bookings needed to keep the hotel alive. With the power of OTAs over the revenue management department of hotels in clear evidence, there was growing recognition that this gap needed to be bridged.
Win-wins for customers and hotels
AI-based digital marketing and price optimization strategies have revolutionized the travel industry through dynamic pricing strategies. By leveraging cutting-edge AI technology and data analytics, customers are being offered the best possible prices for their bookings on OTAs. Hotels, meanwhile, are benefiting from improved search rankings and visibility on all OTAs by at least 25 percent through intelligent copy optimization of their listings and the dynamic pricing strategies driven by AI.
Dynamic pricing is a sophisticated pricing strategy that is constantly evolving, based on market demand and competition. By analyzing historical data and real-time trends, which are publicly available data, AI algorithms can predict the optimal pricing for hotel rooms, flights and other travel products. This allows operators to dynamically adjust the prices of clients’ rooms and airline flight tickets on all OTAs to meet the demands of customers in real time and remain competitive in a constantly changing marketplace.
Picking up the preferences
One way to optimize dynamic pricing for customers is through machine-learning algorithms, which analyze vast amounts of data to predict consumer behavior and preferences. By predicting what a customer is willing to pay for a hotel room, the right price can be offered at the right time, resulting in increased conversions and revenue for both hotels and their chosen OTA platform.
Another key component of the pricing strategy is understanding the competitive landscape. By tracking competitors’ prices and making the necessary adjustments, it’s easier to remain competitive and offer customers the best possible prices.
A recent case study that highlights the success of a dynamic pricing strategy is our partnership with the H Hotel Dubai. Through our collaboration, we were able to analyze data on past bookings, cancellations and competitor pricing to develop a dynamic pricing strategy that improved occupancy and increased revenue for the hotel chain. Using AI algorithms to predict demand and adjust pricing accordingly, we were able to increase room occupancy by 9.1 percent and revenue by 13.7 percent year-on-year.
Enhancing the service and outcomes
There is growing evidence that AI-based dynamic pricing is a key component in the travel industry of the future. By using cutting-edge AI algorithms and real-time regional data analysis, the hotel listing can be optimized on all OTAs, leading to a gain of at least 25 percent in search rankings for all search terms and optimized pricing for both OTAs and hotel partners. The ultimate goal should be to offer customers the best possible prices while also ensuring that hotel partners achieve their revenue goals and maintain an advantage over competitors.
Leveraging data analytics and machine learning algorithms, operators are able to predict demand and adjust pricing in real-time, resulting in increased conversions and revenue for both customers and hotel partners. This innovative approach to pricing is transforming the travel industry and providing customers with a much improved travel booking experience.