A Hospitable Algorithm, Satisfied Customers
By Şeymanur AYDIN
As we mentioned in our previous travel articles, tourism plays an important role in the economies of a country. It would be wrong to think that only one word represents tourism. One of the arteries of tourism, which has a multi-channel structure, is accommodation services.
The rate of preference for accommodation services in long destinations and business trips is high. While choosing a suitable place for accommodation, people make a choice according to their economic and socioeconomic conditions and prioritize features such as cleaning, service, and security. In a study involving participants who prefer a hotel, according to the results, accommodation choice is made based on the recommendation of friends and relatives as the highest rate. While online research follows this rate, the choice of travel agency and accommodation place is in the third place. The result is that people tend to minimize the risk by choosing places that have been tried before and are satisfied.
“What should you do to ensure that customers who come to your business come back and to be preferred by customers who will come for the first time?” the question comes to the fore at this point. As a matter of fact, you can start by establishing a business culture with a low rate of complaints and a high satisfaction rate so that the customers who have previously stayed will choose you again and positively affect the customers who will stay for the first time. In a study conducted with 260 participants, when the reactions and attitudes of the participants to the complaints were examined; 28.5% stated that they could change the business, 22.3% would warn people close to them such as friends and family, 19.6% would not stay in the same business again. The reasons for the complaints were stated in order of proportion: insufficient number of employees, communication problems of employees, insufficient cleaning and hygiene, insufficient security.
Artificial intelligence algorithms facilitate our work in many areas, as well as providing an efficient solution in this field for corporate culture and quality, satisfaction for the organization, customer continuity, and circulation.
Considering the reasons for the complaints, the first place is the insufficient number of employees. The main problem is not the inadequate number of employees, but rather the inability to coordinate the employees correctly according to the density. For example, the staff of the bar, which opens at 23:00, can be assigned to the restaurant at busy hours for dinner (such as 20:00). This will minimize customer grievances and increase satisfaction.
The times and regions where the density increases can be detected by computer vision algorithms. Employees can be guided more easily with features such as “crowd detection”, “human route detection” and “density statistical data generation”, as in the algorithms developed by Xena Vision, and with warnings and notifications sent when detected
The other two reasons for complaints were given as communication problems of the employees, inadequacy of cleanliness and hygiene. There may be problems such as delay in service times, one personnel not following the work of other personnel. At this point, the algorithm developed by Xena Vision can facilitate the follow-up of the process with features such as “person route detection”, “person activity detection”, “routine arrival and departure statistics” “intervention detection” “personnel recognition from clothing” in accordance with the field of study.
Another reason for the complaint was security. Especially in luxury and high-end hotels, incidents such as entering customers’ rooms other than themselves, stealing material items such as jewelry and money, or obtaining project files prepared for an important job are common. The problem can be eliminated with a Xena Vision algorithm that detects entry and exit of room and inform customer.
In 2015, an attack was carried out at the Radisson Blu hotel in Bamako, the capital of Mali. In this attack, 170 people were taken hostage, and 12 people were identified as dead after the incident. More recently, terrorist attacks targeting hotels were also carried out in Sri Lanka. Many people lost their lives and dozens were injured in these attacks. It is possible to prevent the danger and increase the security rate with computer vision algorithms, with algorithms such as “Emergency detection”, “Detection of the suspicious walk patterns” developed by Xena Vision, it is possible to integrate this into the system.
References
https://www.aa.com.tr/tr/dunya/sri-lankada-teror-saldirisi/1458604
https://tr.wikipedia.org/wiki/2015_Bamako_otel_sald%C4%B1r%C4%B1s%C4%B1
https://smallbusiness.chron.com/hotel-theft-prevented-56242.html
