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RJ Friedlander, CEO, Review Pro
Over the past several years, there has been extensive coverage of Big Data and the promise of how such analytics will eventually help businesses offer more targeted marketing and better tailored experiences to customers.
For the hotel industry in particular, Big Data offers the promise of significant opportunities for improving services and revenue; however, most hoteliers do not value the potential impact of Big Data or know how to implement such analytics within their property or brand. One very clear application of Big Data analytics for hoteliers is the mining of guest feedback data, both from the social web and from direct survey responses. Savvy hoteliers are accessing meaningful insight into traveler behavior and likes/dislikes to make decisions that improve operational and service excellence and to create personalized experiences for guests. When properly managed, hotel brands both small and large, are significantly increasing guest satisfaction and revenue. Instead of making decisions based simply on experience, one person or an internal teams’ opinion(s), more and more hoteliers are leveraging detailed Guest Intelligence information to take action that will benefit future guests and the property/brand.
We live in a world where user-generated content–and as a result, a property’s online reputation– have an enormous influence on both consumer and business travelers when booking a hotel room. As such, a comprehensive Big Data strategy is a vital consideration for hotels worldwide in 2015 and beyond.
So what are the key components of Big Data for the hotel industry?
Ultimately, Big Data analytics in the hotel industry will include data sets from many areas of the enterprise (PMS, CRM, Channel Manager, Booking Engine, Financial, etc.) Today, however, the “low-hanging fruit” is related to combining online review, guest satisfaction survey and historical pricing data.
Online Review Data
The first component is the aggregation and analysis of online reviews, from more than 140 online review sites and online travel agencies (OTAs, such as Expedia, Booking.com and Hotels.com) in all languages worldwide.
Online review analytics can identify detailed areas for improvement, as well as strengths and weaknesses in a hotel’s operations. Using semantic analysis (which analyzes the language used by guests to find specific keywords); hoteliers can identify, almost on an atomic level, how guests feel about their stay at the hotel. This insight can be used as the basis for changes in sales messaging, operational processes and even distribution strategy. Even within the individual departments, it is possible to determine what types of changes will best address guests’ concerns and preferences.
Like a real-time focus group, online review analytics can help hoteliers to make wise investment decisions related to capital expenditures, internal training and process improvements to ensure the highest ROI on such actions. When the right guest analytics are combined with successful execution, hoteliers exceed guests’ expectations, which will yield higher ratings on online review sites and increased revenue.
In order to effectively aggregate and analyze review data, hotels should use an online reputation management solution that analyzes reviews from all sources, that is easy-to-use (to ensure that staff follows through on using the tool) and that offers an open platform (API access that can connect to a property’s current internal technological systems) to ensure that all data is available via one integrated platform.
Guest Satisfaction Survey Data
Guest surveys are another valuable input source for Big Data analytics for hoteliers. When properly designed, during-stay and post-stay surveys provide guests with an opportunity to provide very detailed feedback related to their concerns (in a non-public venue). Also, these surveys provide management with an opportunity to respond directly to the guest to address concerns before they are posted on review sites, such as TripAdvisor or OTAs, such as Booking.com.
Profit from Guest Intelligence
Not only can the use of Big Data analytics yield a significant improvement in guest satisfaction, it can also increase a property’s revenue drastically: according to a landmark Cornell University study (using ReviewPro’s data), a one-point increase in a property’s online reputation can lead to a possible 0.89 percent increase in price (Average Daily Rate– ADR), 0.54 percent increase in occupancy and a 1.42 percent increase in RevPAR (revenue per available room).
Big Data also enables hoteliers to optimize their internal revenue strategy, by providing the information necessary to identify specific, actionable insights and to turn them into opportunities to improve a property’s financial performance. By combining guest feedback and historical pricing data (STR or equivalent), hoteliers can measure the extent to which ADR and RevPAR have been optimized, both by looking at the hotel’s reputation/revenue performance individually and comparing it to that of its competitors.
One very clear application of Big Data analytics for hoteliers is the mining of guest feedback data, both from the social web and from direct survey responses
Over the coming years, it will be commonplace for hoteliers to leverage business intelligence tools to manage massive data sets from a wide variety of inputs, including ORM and GSS. In the meantime, forward-thinking hoteliers will see that it is relatively simple to generate a significant improvement on guest experience and revenue using a combination of online review, guest satisfaction survey and historical pricing data.