Every Data Set Counts – Using Google Trends to Update Digital Content in Hospitality
Until recently revenue managers had to collect, review and analyze numerous data sets each time a room rate needed to be updated and then calculate the ideal rate based on those variables. This presented a time consuming task that meant that rates could not be updated as often as they should. Meanwhile, the creation of Online Travel Agencies otherwise known as OTAs meant that large quantities of data became available and the task of manually executing pricing decisions became impossible.
Few industries are as customer centric as the hospitality industry; hotels, resorts and airlines aim to create a valuable customer journey from start to finish. In fact it is an industry where consumers start their customer experience well before rooms are booked by shopping around different channels, seeking rates availability and room types, and even booking the exact room for their stay. Increasingly guests seek a rich, personalized experience by use of familiar and increasingly sophisticated technology.
Digital transformation and the development of Artificial Intelligence and Machine Learning are revolutionizing the way hotels are managed and ultimately the entire customer experience. Through the Cloud, Cluster Computing and scale-out methodology hotels have now access to Revenue Management Systems (RMS) that leverage Machine Learning and AI technology. RMS automatically collect and compute large amounts of complex and disparate data convert it into more manageable sizes and into easily understandable data; the system effectively sifts through the signals detected from market variables, discovers patterns and anomalies, makes predictions for guest arrivals and calculates optimum prices as the market changes, rendering the manual implementation of revenue management tasks no longer necessary.
At the same time, with machine learning RMS accurate pricing suggestions are made; the implementation of dynamic rates based on specific variables chosen by the revenue manager is possible; algorithms can be designed to analyze sentiments and suggest operational improvements that can be made to enhance guest experience; K-Nearest Neighbors’ algorithms are used in order to dynamically identify similar properties within the hotel’s competitive set; sentiment analysis is used to increase or decrease room rates based on whether or not guests are happy; and, the creation of fluid segmentation in real time ensures the hotel continues to reach the right guests, at the right time and price, through the right channels.
Google trends and other similar tools are used to discover what the current trend is and include it in the customer experience. For instance presently pink flamingos are the trend and every self-respecting summer destination will be including inflatable flamingos and other products such as pizza slices in their pools.
Similarly AI supports the ability to access, codify and appropriately present more data about the guest at every point of his stay cycle; and, supports the human or machine process by presenting more relevant information at the right moment.
As Carson Booth C-Suite Technology Strategist points out “No industry is better positioned to leverage AI’s ability to sift through vast amounts of data and help create a unique guest experience”.
More and more the hospitality industry uses AI to go beyond just the customer experience level and indeed those doing so have seen amazing results. According to a recent research 79% have seen an increase in customer engagement by targeting the right audiences thanks to information gathered by AI; 89% of companies using AI retain their customers as opposed to 33% in those that don’t use AI.
For instance, The Hyatt Regency Riverfront in Jacksonville, Florida uses an AI system to better generate staffing schedules and forecast food and beverage needs. Similarly, the Pan Pacific in San Francisco was able to achieve highly accurate restaurant room service and banquet forecasting as well as maintain appropriate staffing levels. Meanwhile, the Luxury Hotel Portfolio Dorchester Collection is using the AI Metis platform to enhance its customer experience that allows it to tap directly into digital customer feedback. As its director for global guest experience and innovation, Anna Brant points out, “Metis reads thousands of customer reviews and tells us what really matters to our customers”.
In a nutshell, AI revolutionizes how businesses can achieve better customer experience and by use of powerful data analytics tools companies are able to track near real time changes in customer sentiment and make data driven decisions that protect the bottom line. We have reached a point in the history of mankind where more information is available than ever before and where the customer is more demanding and selective than ever again and if the hospitality industry wants to remain competitive it needs to exploit and use to its advantage the gifts provided by technological innovation.
Few industries are as customer centric as the hospitality industry; hotels, resorts and airlines aim to create a valuable customer journey from start to finish. In fact it is an industry where consumers start their customer experience well before rooms are booked by shopping around different channels, seeking rates availability and room types, and even booking the exact room for their stay. Increasingly guests seek a rich, personalized experience by use of familiar and increasingly sophisticated technology.
Digital transformation and the development of Artificial Intelligence and Machine Learning are revolutionizing the way hotels are managed and ultimately the entire customer experience. Through the Cloud, Cluster Computing and scale-out methodology hotels have now access to Revenue Management Systems (RMS) that leverage Machine Learning and AI technology. RMS automatically collect and compute large amounts of complex and disparate data convert it into more manageable sizes and into easily understandable data; the system effectively sifts through the signals detected from market variables, discovers patterns and anomalies, makes predictions for guest arrivals and calculates optimum prices as the market changes, rendering the manual implementation of revenue management tasks no longer necessary.
At the same time, with machine learning RMS accurate pricing suggestions are made; the implementation of dynamic rates based on specific variables chosen by the revenue manager is possible; algorithms can be designed to analyze sentiments and suggest operational improvements that can be made to enhance guest experience; K-Nearest Neighbors’ algorithms are used in order to dynamically identify similar properties within the hotel’s competitive set; sentiment analysis is used to increase or decrease room rates based on whether or not guests are happy; and, the creation of fluid segmentation in real time ensures the hotel continues to reach the right guests, at the right time and price, through the right channels.
Google trends and other similar tools are used to discover what the current trend is and include it in the customer experience. For instance presently pink flamingos are the trend and every self-respecting summer destination will be including inflatable flamingos and other products such as pizza slices in their pools.
Similarly AI supports the ability to access, codify and appropriately present more data about the guest at every point of his stay cycle; and, supports the human or machine process by presenting more relevant information at the right moment.
As Carson Booth C-Suite Technology Strategist points out “No industry is better positioned to leverage AI’s ability to sift through vast amounts of data and help create a unique guest experience”.
More and more the hospitality industry uses AI to go beyond just the customer experience level and indeed those doing so have seen amazing results. According to a recent research 79% have seen an increase in customer engagement by targeting the right audiences thanks to information gathered by AI; 89% of companies using AI retain their customers as opposed to 33% in those that don’t use AI.
For instance, The Hyatt Regency Riverfront in Jacksonville, Florida uses an AI system to better generate staffing schedules and forecast food and beverage needs. Similarly, the Pan Pacific in San Francisco was able to achieve highly accurate restaurant room service and banquet forecasting as well as maintain appropriate staffing levels. Meanwhile, the Luxury Hotel Portfolio Dorchester Collection is using the AI Metis platform to enhance its customer experience that allows it to tap directly into digital customer feedback. As its director for global guest experience and innovation, Anna Brant points out, “Metis reads thousands of customer reviews and tells us what really matters to our customers”.
In a nutshell, AI revolutionizes how businesses can achieve better customer experience and by use of powerful data analytics tools companies are able to track near real time changes in customer sentiment and make data driven decisions that protect the bottom line. We have reached a point in the history of mankind where more information is available than ever before and where the customer is more demanding and selective than ever again and if the hospitality industry wants to remain competitive it needs to exploit and use to its advantage the gifts provided by technological innovation.