Data leadership: making sense of big data in hospitality sector
Era of crucial data transformation
In the recent years, hotel industry has been collecting tones of information to better reach and serve the guests. Customer data within loyalty programs, price comparisons, location data and booking data… All this information was meant to understand a customer better and to improve the rendered services in future. Within this environment, it’s pertinent to remember that, while big data definitely provides valuable insights, the collection of customer data goes hand-in-hand with a responsibility to safeguard personal information.
In the recent years, sophisticated technologies used in the field of big data analytics penetrate almost every field – hotel and hospitality industry is not an exception. Innovations are frequently linked to the rising importance of mobile consumption. Thus, the majority of hospitality companies are developing new ways to engage with customers on smartphones and tablets in order to enjoy higher levels of customer engagement.
To illustrate, some mobile apps that are installed on a secured Android device in hotel rooms act as truly “universal” remote controls for the guest experience, allowing guests to order room service, text hotel employees, control the in-room lighting and TV. Cloud-based services are another major driver of the hospitality sector. Modern IT leaders constantly develop curated technology portfolios for hospitality specific goals. For instance, one of these services allows guests to view different rooms available and choose the one they want to stay in.
Nowadays, hospitality sector collects huge amounts of data about their customers. Effective leveraging of that data and deep technical expertise are among the main ingredients of success. Data leadership is rapidly acquiring its shape. Since there’s too much data out there to process completely, they need to implement a system for filtering and organizing that data. Such a system enables the specialists to predict guest behaviour by analyzing previous interactions across a number of digital devices, such as smartphones, TVs and laptops.
How hospitality sector has been transformed by data leveraging?
Customer categorization. Categorization and identification of incoming customers is one of the main ways to maximize revenues.
Personalized service. More hotels are offering customized services to cater to their most valuable customers – either in groups or as individuals. In this way, hotels can’t always rely on internal data to predict a customer’s return. Hence, data analysts have to collect data from surrounding, external sources to help identify travel patterns, habits and common timeframes.
Social media. Since many customers refer to social media for questions and concerns, the platforms provides a great opportunity to connect with consumers in brand-new ways. Many hotel networks compile vast datasets containing online search histories, completed bookings on every one of their customers. The data helps the sales managers create personalized travel experiences for their frequent guests.
Yield management. Big data analytics also affects yield management. By calculating the optimum value of each room and factoring in metrics like seasonal demands, regular guests and similar trends, hotels can ensure maximum profits.
Descriptive, predictive, and prescriptive analytics as tools to forecast future events
Descriptive, predictive, and prescriptive analytics are the methods that are commonly used for applying big data in the hotel and hospitality industry. Their impact is immense and can be traced throughout the entire business organization.
Descriptive analytics is used to extract data from past occurrences and activities. Being one of the most straightforward and efficient ways of generating actionable data, this method allows to conduct a deep analysis of various sales or capital-related metrics.
Predictive analytics uses big data to try and forecast future outcomes or events. For instance, the process of preparing a hotel for a seasonal changes - reduction of the hours of staff members to accommodate the fewer number of reservations in the offseason.
As for prescriptive analytics, it takes advantage of highly advanced algorithms to process big data and provide actionable advice. Hence, certain systems provide recommendations to improve service and increase profits. Online reservation systems that track a guest’s past stays automatically generates discount codes for future reservations, assemble personalized services for each guest and even deliver their favourite drinks or food.
By and large, big data analytics has all the chances to entirely transform the customer experience within the hotel and hospitality industry. It’s not a quick process, but the industry is already making huge steps toward a full adoption of big data and all the benefits it has to offer.
Data leadership transforms the hospitality sector driven by innovations and data analytics. It changes not only the way people travel, but also the manner hospitality businesses operate heralding the era of absolute digitalization.
Some of the most data-driven hotel chains are already adopting long-term strategies and policies for big data management. Those who are unwilling to embrace the changes might find it hard to compete in the years to come.
Regardless of whether hotels are trying to better their offers, provide personalized services, engage their social media audience or stretch the value of their properties, they must use and apply all this data before it has an impact. The information on its own is dormant until activated through the disciplines of big data processing and analysis.
Big data can help hotel owners and other business leaders identify important patterns and trends. As a result, it can help improve revenue management, optimise marketing efforts, and enhance the customer experience that is being delivered.