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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.



By Goran Dragosavac (SAS), @goran_drago.

Hotel industry is another industry where effective use of analytics can change dramatically how business is run. It is another data rich industry that captures huge volumes of data of different types, including video, audio, and Web data. However, for most hoteliers data remains an underused and under-appreciated asset. Hoteliers capture loyalty information, for example, but few go beyond loyalty tier in how they consistently view and take action with their guests. With analytical exploitation of their data, hoteliers can go beyond their traditional loyalty programs and deepen their knowledge of guests in order to develop a more granular understanding of segment behavior, needs, and expectations; identify profitable customer segments and their buying preferences; and identify opportunities to attract new guests. But all that starts with having clear customer-driven vision, before embarking on Integrating and standardizing guest data from multiple channels, systems and properties into a unified, accurate view of all interac­tions.

Diamond

Next phase is using analytics to segment guests according to booking trends, behavior and other factors in order to reveal their likelihood to respond to promotions and emerging travel trends. It is vitally important for hoteliers to be able to understand guest preferences (locations, activities, and room types), purchase behavior (frequency, length of stay, time of year) and profit potential in order to increase the brand loyalty and wallet share of their most valuable guests. Focusing on the wrong guests reduces profitability across the enterprise. For example, if a hotel targeted guests who would likely take advantage of spa services, golf and restaurants, rather than guests who only generate room nights, they could significantly increase revenues and profitability.

To maximize profits, hotels need to increase the loyalty and wallet share of their most valuable guests by marketing to their preferences and encouraging repeat visits. Focusing on the wrong guests reduces profitability across the enterprise. For example, if a hotel targeted guests who would likely take advantage of spa services, golf and restaurants, rather than guests who only generate room nights, they could significantly increase revenues and profitability. Unfortunately, money often gets spent on blanket campaigns that don’t target individual guests or segments with offers they’re most likely to respond to. As a result, guests may feel that the hotel doesn’t care about them, or simply doesn’t offer services designed to meet their needs. It becomes easy for those guests to switch to a competing hotel.

Unfortunately, money often gets spent on blanket campaigns that don’t target individual guests or segments with offers they’re most likely to respond to. As a result, guests may feel that the hotel doesn’t care about them, or simply doesn’t offer services designed to meet their needs. It becomes easy for those guests to switch to a competing hotel. For analytics to truly be a game changer, hospitality organizations need to recognize the difference between reactive and proactive decision making. Using your data to create reports, drill-downs or alerts helps you to keep a finger on the pulse of your business. But these things only show you what happened. They will not tell you why the problem is happening or what effect it will have in the future.

Predictive analytics, like forecasting and optimization, can help you figure out why things are happening, show you what will happen next, or even lead you to the best alternative action considering all of your operating constraints. Hoteliers are starting to use more and more predictive analytics to move from reactive to proactive decision making, which would enable them to stay one step ahead of trends, set strategy and achieve goals. They gain advantage over the competition, increase value to shareholders, and continue to surprise and delight their guests. Following are areas where analytics can play essential role:

Customer Segmentation

For the hotel industry, a more useful approach might be to identify the unique cluster groups and to then conduct a separate value segmentation exercise for each cluster. For example, for a given hotel we identify 4 basic clusters or distinct customer groups such as tennis groups, ski group, pampered group (e.g. use spa and valet type services) and the nighthawk group ( fine dining and theatre goers). The segmentation approach might look as follows: initial learning from this type of segmentation could be used in developing a marketing strategy that is data-driven.

The hotel could examine its current business customer base and once again establish unique groups of business customers. For example, we know that there are groups of business customers that simply use the hotel for overnight stays, while others are there for longer term events held at the hotel. It may be possible to further segment these groups based on industry sector. We would certainly expect that local events held by the oil and gas industry might be more appropriate in one city, while financial services type events may be more prevalent somewhere else.

Of course, all this supposition on what might define unique business segments would need to be determined quantitatively through clustering routines. By using the data and mathematics rather than intuitive judgment to define key customer segments, we can develop unique programs that are appropriately geared to different groups of unique business travelers.

Customer experience has always been the overriding customer philosophy within the travel industry, long before the advent of data analytics. Yet, with data analytics, the travel industry can now use information to make better decisions regarding its customers. This enhanced decision-making capability enables hotels to be more proactive with its customers. Traditionally, success in the hotel industry has always been determined by superior customer service actions that address the immediate requested needs of the customer. The competitive advantage in today’s hotel industry is driven more by the ability to anticipate and proactively meet the needs of customers; an ability that can only be exercised through data analytics.


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