In the hotel sector or the hospitality industry in general, the consumer is very crucial. The entire point of the business is to keep customers pleased. However, the margins are gradually shrinking; it is no longer enough to keep customers satisfied. As a hotel manager, one must create new ways to entertain guests and maintain their market share. Hoteliers would have to figure out how to close the gap between perceived and actual delight. In view of new technological breakthroughs and changing customer behavior, hospitality managers face radically different difficulties now than they did in the past. With the introduction of applications, customers have come to anticipate a certain level of ease and efficiency, which must be met. Essentially, changing consumer needs have limited quality services in the hospitality sector and can be addressed through the use of big data and advanced analytics.
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Proposition: Smart Technology Solves the Challenges Posed by Changing Consumer Needs
Dynamism in the hospitality industry has introduced a major challenge: adapting the structure and operations to meet new needs and preferences. According to Neuhofer (2016), the decline in customer delight is significant since only 16% of customer service results in complete customer satisfaction. The chasm between reality and perception must be bridged to maintain the core values expected of the hospitality sector. Today, the excellent service provided yesterday would not be sufficient to meet clients’ needs. As a result, with changing customer expectations, pleasing customers in the hospitality industry is becoming more difficult. As competition increases, hoteliers and key players in the hospitality industry have to develop technologically innovative programs.
From the comfort of people’s homes to the way cities are run, smart technology is transforming everything. It is not different in the hospitality sector; the hospitality industry is at the forefront of smart business technology adoption. Smart hotel technology features a multitude of cost savings and income opportunities across operations, customer satisfaction, and marketing, allowing hotel owners to achieve new levels of profitability. With the changing consumer behavior, hotels and key players in the hospitality industry have to innovate and find new ways to meet customer demand (Celtek, 2020). Smart technological solutions, which entail big data, have been applied to handle dynamic guest behavior.
The Impact of Big Data on Smart Guest Experiences
From the fact that no hotel can function without guests, hoteliers can anticipate seeing smart technology continue to alter guest attitudes. Visitor data may be used not only to better satisfy guests’ demands and also be with remote monitoring sensors to automate guest exchanges throughout their stay, lowering both friction points and personnel expenses (Wu & Cheng, 2018). As a result of intelligent technology, hotels will be able to predict and customize a variety of visitor services based on previous visits and aggregated guest data.
Smart technology’s ability to gather data and make it useable is one of its primary advantages. However, with huge data comes a lot of responsibility, whether taking on a new market sector or altering the rate plans to compete against competitors (Leung, 2019). The safety of large data and the requisite data storage is, however, the most pressing worry. According to Aithal (2019), the purpose of every data harborer is to protect their clients’ data.
However, data loss and inefficient database security systems have made it difficult to achieve complete data safety and analytics. Massive data breaches, such as those at Equifax and Target, have put hundreds of millions of users in danger in recent years. It is expected that more hotel owners embrace and invest in big-data technologies as the price point renders them more affordable to medium-sized portions of the hotel business. More importantly, solution providers who can ensure data security will probably dominate their market segments.
Advantages of Big Data
Big data is an important subject to understanding in the hospitality sector since it may assist hotel owners and other industry leaders in identifying vital patterns and trends. As a result, it assists in improving revenue management, optimizing marketing activities, and improving the customer experience (Neuhofer et al., 2016). In terms of hotel revenue management, big data can help hotels with revenue management methods by allowing them to more correctly predict levels of demand for rooms. Past occupancy rates and present bookings are examples of key performance measures (Aithal, 2019). Big data may also be utilized to forecast demand and future trends, which is crucial for successfully implementing revenue management plans. Weather, school holidays, and other factors will help hoteliers predict the next “big rush,” allowing them to staff appropriately, provide an amazing guest experience, and operate at peak efficiency.
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Big data can assist hoteliers in determining the appropriate marketing spend across numerous channels to reach diverse categories. It may help hotel facilities and their goods gain a deeper understanding of different categories and their guests, resulting in enhanced engagement and visibility (Leung, 2019).
If a hotel establishes that a specific target demographic makes bookings through social media channels, for example, marketing efforts might be directed toward those platforms. Hotel data is a valuable tool in identifying marketing blunders. When potential visitors depart a booking website, for example, big data can assist in identifying and correcting the problem. According to Leung (2019), big data can also be used to detect traits that define hotel customers, ranging from commuters to families on yearly vacations, as well as their content preferences. Marketing content should be modified to facilitate more engagement and improved conversion rates for incentives through consumer behaviors and trends.
Opposition to the Use of Big Data in Hospitality
Despite the breakthroughs associated with big data in the hospitality sector, there are some critics who believe that its use limits customer experience and creates a disconnection between customers and service providers. Data security, cultural changes, and privacy concerns are some of the drawbacks linked to big data and its use in the hospitality industry. Wu and Cheng (2018) argue that big data and its associated analytics can be used to manipulate customers’ records. It is also argued that big data introduces a cultural change in an industry and may suffer from inadequate skilled personnel. Data mismanagement may lead to privacy and security concerns, which have significant cost implications for customers and hotel managers (Wu & Cheng, 2018). Essentially, while hoteliers may be targeting new customer experiences and enhancing their competitiveness, there are considerable costs implications. If the drawbacks are not effectively managed, big data may lose its relevance.
Value Preservation in Hospitality
One of the core values of the hospitality sector is creative problem-solving. Dynamic customer needs have remained a significant problem limiting the role of hoteliers in solving emerging issues in the industry. Using big data to facilitate predictive analysis and smart customer experiences is set to preserve hospitality’s problem-solving abilities (Neuhofer et al., 2016). Finding ways to ensure customer data is secured will also limit the drawbacks associated with big data and give customers a great experience.
While many hoteliers may be focused on revenue and competition, it is crucial to understand that values pertinent to the hospitality sector should be preserved as they guarantee continuity and support within the industry. Big data also holds the values of care, trust, and focus, which are vital in the hospitality industry. This follows from the use of big data to ensure customer needs are met in the most convenient way possible. Lastly, the quality of services and facilities will be ensured.
In conclusion, the hospitality industry has been significantly impacted by changing technologies and customer trends. Customer preferences and experiences are dynamic, necessitating the development of innovative solutions to ensure that their needs are met while preserving the hospitality industry’s core values. Big data is a potential solution to the customer dynamics challenge. It will allow hoteliers and business managers to collect valuable information for predictive analysis and develop new techniques, services, data management methods. Despite the potential benefits associated with big data, critics argue that it presents considerable challenges in regard to privacy, hospitality culture, and data security. However, data security can be managed and customers assured of their privacy and quality services.
In conclusion, the changes witnessed in the hospitality sector will continue since consumers often change their perspectives and attitudes. For this reason, hoteliers and managers need to venture into big data applications to develop viable solutions that will guarantee revenue growth, customer retention, and value preservation within the industry.
Aithal, P. S. (2019). Information communication & computation technology (ICCT) as a strategic tool for industry sectors. International Journal of Applied Engineering and Management Letters (IJAEML), 3(2), 65-80. Web.
Çeltek, E. (2020). Big data, artificial intelligence, and their implications in the tourism industry. In Handbook of Research on Smart Technology Applications in the Tourism Industry (pp. 115-130). IGI Global.
Leung, R. (2019). Smart hospitality: Taiwan hotel stakeholder perspectives. Tourism Review, 74(1), 50-62. Web.
Neuhofer, B., Buhalis, D., & Ladkin, A. (2016). Smart technologies for personalized experiences: A case study in the hospitality domain. Electronic Markets, 25(3), 243-254. Web.
Wu, H., & Cheng, C. (2018). Relationships between technology attachment, experiential relationship quality, experiential risk, and experiential sharing intentions in a smart hotel. Journal of Hospitality and Tourism Management, 37, 42-58. Web.