Big Data Analytics in Hotel Industry
The Hotel industry is another data rich industry that captures huge volumes of data of different types. Find out, how Customer Segmentation, Energy Consumption, Investment Management, and Resource Allocation for it can be revolutionized using big data analytics.
Energy Consumption
In the hotel industry world, analytics can also be used for internal operations. Energy consumption accounts for 60 to 70% of the utility costs of a typical hotel. However, costs can be controllable, without sacrificing guest comfort, by using energy more efficiently. At present times, smart data can help managers to build energy profiles for their hotels. There are modern software solutions that gather data from multiple sources, including weather data, electricity rates and a building’s energy consumption to build a comprehensive ‘building energy profile’. Through a cloud-based, predictive analytics algorithm, the software can fine-tune whether power comes from the grid or an onsite battery module.
Investment Management
Another way to use analytics for the hotel industry is for financial performance and investment. When managers want to proceed to make capital investments, like refurbish the lobby or the rooms or renovate their restaurant, they can consider implementing a “Randomized Testing” strategy. How does this work? Basically the hotel chain would refurbish the lobby and rooms in only two or three “test” hotels. Then, they would monitor if there has been a difference in bookings and customer satisfaction. The data obtained from the test hotels can then be compared to the data of the other hotels that were not refurbished.
Thus, managers can take a data driven decision and clearly see if it’s profitable to make the investment throughout the whole chain. In conclusion, data analytics can be a powerful force in transforming the hotel industry. From taking evidence based actions to developing customer centered marketing and pricing strategies, increasing the ROI of capital investments and generally empowering hoteliers to make bigger and better decisions. There are however also some great examples of hotel chains moving in the right direction in respect to use of analytics. This can result in improved customer satisfaction, personalized marketing campaigns and offers so that the right guests book the right room at the right moment and at the right rate. In addition, it can boost in employee productivity and more efficient operations.
The advantages of using analytics and data mining the hotel industry are enormous. Deep customer insights can lead to improved guest satisfaction and an unforgettable experience. Making these insights available to all levels and departments within the hotel is crucial. It allows the concierge to know which local tours to recommend that fit your preferences. It allows the restaurant departments to predict which menu items are likely to be ordered, based for example on the local weather. It allows the reservations department to predict the optimal rate for a room and sales and marketing to create tailored messages across different (social) networks and send truly personalized email campaigns. Let’s dive a bit deeper in some possibilities:
The right room at the right rate
Yield management is nothing new in the hotel industry. Providing different rates to different customers has been done for ages and with success. Big Data offers hotels the possibility to take revenue management a giant leap forward and start offering truly personalized prices and rooms to guests. The massive growth in booking websites, hotel review websites such as TripAdvisor and Yelp and the ever growing list of social media networks offer a lot of potential.
Combined with hotels’ own CRM systems and/or loyalty programs there is a lot of data that can be used to optimize revenue management. According to some industry studies, the hotel chain Marriot has been using Big Data Analytics to start predicting the optimal price of its rooms to fill its hotels. They do this by using improved revenue management algorithms that can deal with data a lot faster, by combining different data sets and making these insights available to all levels to improve decision-making. The American hotel chain Denihangoes even a step further. They used Analytics software to maximize profit and revenue across thousands of their rooms by combing their own data sets and data from for example review sites, blogs and/or social network website. They understand the likes and dislikes of their guests, optimize their offering and adjust the room rates accordingly.
Mobile Big Data throughout the Hotel
More and more hotels have developed mobile Apps that guests can use to book a hotel room. These apps however offer vast more possibilities for guests if developed correctly. It could serve the key to your hotel room; it can be used to make reservations in restaurants and spa’s and for example to order room service. If hotels start using the vast possibilities of mobile application they can generate massive amounts of data that can be analyzed. So, from a guest perspective, mobile offers a lot of convenience.
From an employee perspective, it can make life a lot easier for the staff while at the same time increase customer satisfaction. Providing the housekeeping department with smart devices for example will allow them to know in real time, that you prefer an extra pillow or an extra light. Kempinski and Hyatt in Dubai already use such applications for their hotels. Most of the staff within hotels do not have an office or a computer so providing them with real-time guest information should be done on-the-go. Although this requires a different approach and a different way of presenting the insights, placing user-friendly analytics in the hands of guest facing employees will definitely improve customer satisfaction.
More efficient hotel operations
From a hotel operations point of view, big data offers also many different solutions. Big Data can be used to reduce your energy bill for example. By combining data from 50 different sources, including electricity rates, weather data and a building’s energy consumption, two InterContinental hotels in San Francisco managed to reduce their energy costs by 10-15%. They created detailed energy profiles for their buildings and using a predictive algorithm they decided whether to use an onsite battery module or receive power from the grid. Hotels should also use analytics more to help more efficiently running their IT operations, which is especially relevant for chains that operate their own booking engine. A server that breaks down or a booking engine that is inaccessible could result in lost bookings and therefore lost revenue. IT operations analytics monitors a hotel’s complete IT environment, including the different relations between applications and hardware and can predict when things are about to go wrong. Advanced IT operations analytics can even solve problems automatically before they occur. This could save a lot of money because IT that’s not working will results in a bad customer experience. Of course the examples given here are just a few of the massive possibilities that analytics has to offer for the hotel industry.
Data mining technology can be a useful tool for hotel corporations that want to understand and predict guest behavior. Based on information derived from data mining, hotels can make well-informed marketing decisions, including who should be contacted, to whom to offer incentives (or not), and what type of relationship to establish. Data mining is currently used by a number of industries, including hotels, restaurants, auto manufacturers, movie-rental chains, and coffee purveyors.
Firms adopt data mining to understand the data captured by scanner terminals, customer-survey responses, reservation records, and property-management transactions. This information can be melded into a single data set that is mined for nuggets of information by data mining experts who are familiar with the hotel industry. However, data mining is no guarantee of marketing success. Hotels must first ensure that existing data are managed—and that requires investments in hardware and software systems, data mining programs, communications equipment, and skilled personnel. Affiliated properties must also understand that data mining can increase business and profits for the entire company and should not be viewed as a threat to one location.
Since data mining is in its initial stages in the hotel industry, early adopters may be able to secure a faster return on investment than will property managers who lag in their decisions. Hotel corporations must also share data among properties and divisions to gain a richer and broader knowledge of the current customer base. Management must ensure that hotel employees use the data-management system to interact with customers even though it is more time consuming than a transactional approach.
Bio: Goran Dragosavac, @goran_drago, is a data mining practitioner and blogger.
Original .
Related:
