Analysis of Contemporary trends in data science for hospitality industry

Introduction:

The tremendous growth of Technology, especially social media, impacted the way the hospitality industry interacted with their customers, which enhanced the development of data analytics to support management on decision making processes and solve real-life problems. This essay will discuss the challenge for management to evaluate customer satisfaction and dissatisfaction, opportunities to use text analytics to extract keywords to get an insight view of customer review and issues in the data transformation process. In addition, this essay will also indicate the challenge for lacking remote data accessibility to the Opera (Property Management System),opportunities for cloud service to maintain data integrity and data normalisation and will bring cost efficiency and data accessibility to our hotel business.

Challenge 1 on evaluate customer behaviour

“When you walk into the hotel, you can see verdant green jungles and beautiful ocean and sky (sight). A dedicated ‘Five Senses Concierge’ will greet you on arrival, offering a choice of the finest quality towels (touch) and diffusers and bath salts infused with the warming scent of tart cranberries and spiced apples (scent) with a glass of champagne (taste). The uplifting British jazz is played through the vintage record player (sound). You smile MORE, feel EVEN HAPPIER, and are very SATISFIED (Lee, M., Lee, S. and Koh, Y. 2019).”

Currently I’m working at a new established 5-star hotel. The room and hotel facility are well furnished with a 5-star standard. However, instead of focusing on customer experience of multi sensory (taste, smell, touch, sight and sound), our hotel focuses more on physical and functional aspects of the property such as quantity, quality, price and availability. Even though we do encourage guests to put reviews in social media and also go through them on a timely basis, there is limited understanding/research on predicting customers’ future behaviour. Specifically, there are two main areas that are lacking focus. Firstly, customers have different expectations for economic/budget hotel and luxury hotel, which leads to different behaviour. For example, customers of Luxury hotels are willing to spend more for service quality and location, while budgeted travellers tend to care more about the monetary value of meeting their basic living quarters (Zhang et al., 2011). Secondly, there is not enough understanding for management on how to evaluate customer satisfaction and dissatisfaction in order to improve service quality. However, research finds that multi sensory experiences play a vital role to provide better insight of hotel customer service (Lee, M., Lee, S. and Koh, Y. 2019). One of the best ways to understand guest preference is through their feedback (Padma, P., Ahn, J 2020). According to Al-alak (2014), there are significant differences between luxury hotel guests’ expectation and their actual experience, and it is essential to improve the courtesy aspect of service.

Opportunity 1 for Text Analytics

In the hospitality industry, booking.com, Trip Advisor, yelp.com etc. allows customers to write reviews and comments for their experience in the hotels. Customer reviews are unstructured data so we need to use text-mining software to extract meaningful information (Xiang et al., 2015), by using text-mining with the word frequency analysis, we can find useful model, patterns or trends to help hotel manager to understand the insight of customer behavior and improve guest experience (He, 2013). According to Xiang et al (2015), they used text analytics to classify guest experience. It also analyzed the relationship between service quality with good reviews (rating 4–5) and complaints (rating 1–2). Xiang et al (2015) used critical incident techniques to gain insight of the words by using online reviews. The procedure used for data analysis is explained as below figure 2. For example (As per Figure 3), “husband” represents an expensive hotel, which shows that people who booked with their husband tend to find expensive hotels to stay. In contrast (as per Figure 4), “airport” represents Low Quality Hotels, which shows that people who book near to the airport tend to book with less expensive hotels. This technique provides opportunities for luxury hotel managers to run a hotel that meets customer expectations.

Figure 2 Research progress.

Figure 3 Words Represent High Quality Hotels

Figure 4 Words Represent Low Quality Hotels

Issue 1: volume of data, data cleaning, data integration

Although text analytics methods provide useful information in the hotel industry, it has a number of issues. We are now facing three typical issues in the data transformation process. First and foremost, the volume of data for our hotel is not sufficient. We do not have as many as data to use compared with other luxury hotels as a start-up company. As per below screenshot of our hotel in trip advisor website page, there are only 279 reviews within 3 years.

Secondly, the raw data from travel agent websites is not user friendly. The expectation for domestic and international guests may differ so we may need to put them into two different examines groups to analyze. In order to obtain useful insights, we need to clean and validate data.

Last but not least, the data lacks integration. As the data from the website only represents part of our guest, we may need to combine the feedback from the front office daily log to conduct meaningful data analytics.

Figure 1. Screenshot of Trip Advisor website page.

Impact 1 on using keywords extracted from customer feedback:

By using text analytics to classify customer review will help a new 5-star luxury hotel like us, to understand more about customer needs. Compared with traditional ways of survey studies, data analytics provide a better insight to optimize marketing strategy. Keywords extracted from customer feedback can be used as a guidance for management if they want to buy Google ads words (PJL,T 2017).

In recent times, most hotels are utilizing online reviews in social media, such as Facebook, Instagram, Booking.com, Airbnb, TripAdvisor etc, to understand guests’ behavior. Therefore, our hotel should encourage guests to leave their feedback in social media to help gather the database. Management teams can use data generated from those platforms to investigate customer satisfaction levels.

Challenge 2 on lack remote data accessibility

There is not only a lack of evaluation of customer satisfaction and dissatisfaction, but from an employee perspective, we also lack remote data accessibility to the Opera (Property Management System), so that we cannot work remotely for any urgent circumstances. In result, we sometimes failed to meet deadlines and management expectations. In addition, in certain circumstances, when the server is down, we lose track of data input such as customer check-in/ check-out data.

Opportunities 2 for cloud services implementation

Due to large-scale volumes of data, the needs to be stored in the system, improvement in cloud service, which is typically more cost effective and improves the data accessibility. For example, Oracle introduced new software called “Opera Cloud Services” which is a web-based platform that allows the reception to use and serve the guest anywhere in the property (Hospitality for Hotels — OPERA Cloud Services 2019). Cloud service helps businesses to maintain data integrity and data normalisation. In addition, it also assists managers gain insights from data captured across functional areas, including hotel operations, revenue management, sales, marketing, and catering. In addition, it provides reports for different departments: for example: Front Office (Arrival, departure reports) finance (accounts receivable reports), Reservation (history and forecast) etc., Data analytics also could help improve revenue management by using combined data such as room occupancy with recent events and public holidays to forecast the future demand etc. (Anca, Y 2020)

Issue 2 on data security and privacy

Data security is one of the main concerns faced by organizations in the data transformation process. In 2020, Marriott International declares that approximately 5.2 million guests profile may’ve been exposed in a data breach, which is the second major security incident within 2 years (Carrie, M., 2020), Data and information includes: guest name, date of birth, passport number, their preference, home address and credit card details are being stolen (Armerding, 2018). In fact, according to Micro Strategy (2018), 49% of companies indicate that data privacy becomes the most common concerns and the most influential impacts on e-commerce.

Impact 2 on using cloud service:

By using cloud service to store data, we will have standard reports to analyze on a timely basis and in different sectors which helps management to understand the business in different ways. In addition, Compared with a hotel using a self-designed system, it requires less storage and simplifies the IT infrastructure which saves cost for the hotel, allowing hotel management and staff to focus on delivering exceptional guest experience.

Conclusion:

In conclusion, although there are still limitations for data analytics, we still find it useful for improve customer service quality etc. From a management perspective, they should use customer online reviews to avoid any service failure and improve service quality. Firstly, Text analytics of guest reviews will show patterns of their experience in hotels, which will be useful for hotels to gain insight of customer behavior in order to meet customer potential demands in the future. Based on table 3 (Words Represent High Quality Hotels), the luxury hotel guests seem to have more expectations on amenities, hotel locations and service quality. Secondly, Cloud analytics allows for the simultaneous recording and processing of data regardless if it is near a local server. The data stored improved efficiency as we do not need to wait for the report to be extracted from the local property and by tracking customers’ preference on a cloud basis, which provides better understanding of customer behavior (Data Analytics in Cloud Computing 2013). At last, cloud services can help businesses maintain data integrity and data normalization.

Reference:

1. Armerding, T. (2018), “The 18 biggest data breaches of the 21st century”, available at: viewed 26th Apr 20 www.csoonline.com/article/2130877/the-biggest-data-breaches-of-the-21st-century.html

2. Lee, M., Lee, S. and Koh, Y. (2019), “Multisensory experience for enhancing hotel guest experience: Empirical evidence from big data analytics”, International Journal of Contemporary Hospitality Management, Vol. 31 №11, pp. 4313–4337. viewed 26th Apr 20 https://doi.org/10.1108/IJCHM-03-2018-0263

3. Panchapakesan P, Jiseon,A, “Guest satisfaction & dissatisfaction in luxury hotels: An application of big data, International Journal of Hospitality Management”, Volume 84,2020, viewed 26th Apr 20https://www.sciencedirect.com/science/article/pii/S0278431919301549#bbb 0035

4. Carrie, M (2020), “Marriott discloses new data breach impacting 5.2 million guests”

https://www.cnet.com/news/marriott-discloses-new-data-breach-impacting-5-point-2-million-guests/

5. Data Analytics in Cloud Computing (2013), viewed 26th Apr 20 https://technologyadvice.com/wp-content/uploads/2013/05/Data-Analytics-in-Cloud-Computing_TechnologyAdvice.pdf

6. Fan, W., Wallace, L., Rich, S., & Zhang, Z. (2006). Tapping the power of text mining. Communications of the ACM, 49(9), 76–82. viewed 26th Apr 20 http://doi.org/10.1145/1151030.1151032

7. He, W. (2013). Improving user experience with case-based reasoning systems using text mining and Web 2.0. Expert Systems with Applications, 40(2), 500–507. Contemporary Management Research pp 107–130, Vol. 13, №2, June 2017 viewed 26th Apr 20 https://www.sciencedirect.com/science/article/abs/pii/S0278431914001698

8. “Hospitality for Hotels — OPERA Cloud Services” (2019), viewed 26th Apr 20 https://www.oracle.com/au/industries/hospitality/products/opera-cloud-services.html

9. Pei-J, T. Szu-L,C., Hsiang, C., Wen C,F (2017), “Using Big Data and Text Analytics to Understand How Customer Experiences Posted on Yelp.com Impact the Hospitality Industry”, https://doi.org/10.1016/j.eswa.2012.07.070

10. Xiang, Z. Schwartz,Z, Uysal, M Int. J. Hosp. Manage., 44 (2015), pp. 120–130,” What can big data and text analytics tell us about hotel guest experience and satisfaction?”, viewed 26th Apr 20 https://www.researchgate.net/publication/267750506_What_can_big_data_and_text_analytics_tell_us_about_hotel_guest_experience_and_satisfaction

11. Yallop, Anca & Seraphin, Hugues. (2020). Big data and analytics in tourism and hospitality: opportunities and risks. Journal of Tourism Futures. viewed 26th Apr 20 https://www.researchgate.net/publication/340226370_Big_data_and_analytics_in_tourism_and_hospitality_opportunities_and_risks

12. Zhang et al., (2011) “Guest satisfaction & dissatisfaction in luxury hotels: An application of big data”, viewed 26th Apr 20 https://www.researchgate.net/publication/235297831_Determinants_of_hotel_room_price_An_exploration_of_travelers'_hierarchy_of_accommodation_needs