The Application of Data Analytics Is Revolutionizing the Hotel Business

The ability to wander is built into the human brain. People now have a greater yearning than ever before to interact with one another, discover new places, and travel. Unfortunately, the COVID-19 pandemic arrived in the country as an unwelcome visitor, and as a result, the hotel hospitality business, which is a substantial contributor to the expansion of the economy, was seriously impacted. In order to increase their number of guests, hotel owners need to become more creative and tech-savvy. In order to maintain a competitive advantage over their rivals, they need to make use of developing technology and data analytics to improve and leverage business operations, develop original marketing tactics, and comprehend occupancy rates. The hotel hospitality business can benefit from data analytics by gaining a better understanding of demand, client behavior patterns, and how to efficiently manage their customer base.

The Application of Data Analytics Is Revolutionizing the Hotel Business

India was struck by the COVID-19 epidemic in 2020, which led to the imposition of statewide lockdowns and travel restrictions in March 2020. As a direct consequence of these measures, India’s Revenue per Available Room (RevPAR) dropped to 1,675 INR per day in 2020. When compared to the year 2019, there was a decrease that was approximately sixty percent.

Following the initial pandemic wave, the hospitality industry in India saw a recovery of 4,000 rupees per day in terms of revenue per available room (RevPAR). On the other hand, RevPAR dropped by 53.9 percent as a result of the restrictions that were implemented because of the second wave of the pandemic. Therefore, 2019-2021 are going to go down in history as the worst years for the tourism industry. Because of a new variety known as Omicron, it is anticipated that this will continue for the next two quarters. Despite this, hoteliers have expressed optimism about their industry’s ability to recover and have estimated that it will return to its pre-pandemic level by the years 2022 or 2023. (Source). “We strongly believe that the use of data science, big data, and artificial intelligence will be crucial to the travel, tourism, and hospitality sector,” said Ritesh Agarwal, founder and CEO of OYO Hotels and Homes. “We strongly believe that the use of data science, big data, and artificial intelligence will be crucial.”

Although it may not appear to be particularly simple at first glance, making use of a data integration approach of sufficient caliber will make the procedure much simpler.

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What are the Advantages of Using Data Analytics in the Hospitality Industry?

Let’s go through some of the following strategies that come highly recommended:

The term “revenue management” (RM) refers to the process of employing analytics and performance data of customers to assist individuals working in the hotel business in predicting the behavior of their clients. Methods of machine learning are included in analytics. Some examples of these methods are demand forecasting, consumer segmentation through the use of clustering algorithms, and other classifier models. Utilizing this data helps optimize product pricing tactics as well as distribution methods.

The hotel businesses utilize a tool called Revenue Optimising System (ROS), which forecasts demand and suggests appropriate prices by integrating real-time data such as historical and current reservations, cancellation and occupancy, reservation behavior, room type, and daily rates. In addition to this, it forecasts data regarding climate and weather, booking habits on other sources, pricing offered by competitors, and the existence of sporting or musical events occurring in property areas.

Analytics Predictive: The extensive data repository and predictive modeling offered by hotels offer solutions in the areas of consumer intelligence and data science that assist organizations in acquiring, comprehending, and keeping their most important clients. The term “predictive analysis” refers to the application of a variety of methods, such as data mining, predictive modeling, and machine learning, to forecast future demand patterns and tendencies by analyzing either the most recent data or data from the past.

In the hospitality business, the kinds of parameters that can be improved with predictive data analytics

  • Recommendation Systems for the Purposes of Upselling and Cross-Selling Products and Services
  • Strategies based on Dynamic Pricing
  • Reflections on the Emotional Content of Social Media Posts
  • Creating a Unique Experience for Each Traveler
  • Seasonally specific adaptations of packaging
  • Reduce the rate of customer churn.

Example: Numerous places have recently shown a rekindled interest in drawing in visitors who travel by automobile. Analysts predicted that the vehicle travel market would be fully mature by May 2021; nonetheless, 68 percent of travelers do not want to fly within the country. Visitors were successfully categorized as either vehicle travelers, residents, or flight passengers based on the device location data that was given into a predictive algorithm. This made it possible for analysts to conduct in-depth research into the demographics of vehicle travelers and construct target audience segments based on these characteristics. Source

Tools for business intelligence (BI) analysis and data visualization: It is essential to have a solid understanding of the products and services that your rivals offer their clientele. Business intelligence is a useful instrument for compiling all the tidbits of information that are available. It provides hotel owners with an all-encompassing perspective of many things, including an overview of their annual yields as well as their expenses for supplies and electricity.

BI and visualization tool features and capabilities

  • Reports and projections regarding customer bookings as well as stays
  • The ability to see both revenue and margins
  • Multi-property management
  • Integration of data and storage of it
  • Harmonization of data sources located in separate silos

InterContinental Hotel Group conducts customer satisfaction surveys during their guests’ stays, and then combines the resulting insights with data regarding economic and industry performance in order to have a clearer view of how their business operations are performing. By taking this method, InterContinental is able to have a better understanding of the internal and external elements that influence the quality of their service.

The Texas Hotel group makes use of iDashboard in order to achieve organizational transparency, particularly with regard to the company representative shares.

The data science and new technology implementation at hotels results in a 135 percent rise in the hotel’s online revenue. (PwC, 2019). For instance, the Best Western Hotel has reaped significant benefits, such as a fall of 71 percent in guest complaints, an increase of 19 percent in customer service ratings, and a reduction in the amount of time needed for onboarding new employees. (PwC, 2019).

Conclusion

Recently, hoteliers have come to the realization that data analytics is altering the landscape of the hotel hospitality business and enables them to make decisions that are founded on data and supported by evidence. On the other hand, the use cases that were covered in this essay are merely the tip of the iceberg. Businesses in the travel industry may better understand the requirements and preferences of their customers by utilizing the vast array of solutions made available by data science. This allows these companies to give their customers with the most beneficial services and deals.

Companies pursue digital transformation by merging digital and conventional data to obtain a competitive edge. We provide a comprehensive perspective of the digital consumer, which enables businesses to discover new avenues of revenue, forecast hospitality trends and popularity, increase client retention rates, and maximize the efficiency of their property expenses. “We have helped our clients capitalize on the pent-up demand by identifying their loyal customers who are searching for bleisure, domestic, and green travel”.

Big Data in the Hospitality Industry

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