Use of Facial Recognition for Data Personalization in Customer Relationship Management (CRM): Case of Great Zimbabwe Hotel
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International Journal of Engineering Trends and Technology (IJETT) |  |
| © 2014 by IJETT Journal | ||
| Volume-14 Number-1 |
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| Year of Publication : 2014 | ||
| Authors : Magomelo Munyaradzi , Mavhemwa Prudence , Mukabeta Tarirayi |
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 10.14445/22315381/IJETT-V14P209 |
Citation
Magomelo Munyaradzi , Mavhemwa Prudence , Mukabeta Tarirayi. "Use of Facial Recognition for Data Personalization in Customer Relationship Management (CRM): Case of Great Zimbabwe Hotel", International Journal of Engineering Trends and Technology (IJETT), V14(1),40-47 Aug 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
This study was aimed at development of an intelligent facial recognition system for data personalisation in customer relationship management and determine the extend at which the system would enhance customer relationship management at the institution. The research was conducted at Great Zimbabwe Hotel. The increased competition in the hospitality industry now calls for organisations to restructure their operations so as to retain customers. Many organisations are now taking on board the ICTs in order to enhance customer services. This has driven this study to be conducted using a facial recognition in order to increase customer relationship management. The system was developed and implemented at Great Zimbabwe Hotel. A total of 40 questionnaires were distributed and 33 were returned giving a response rate of 82.5%. From both questionnaire and report review conducted, the result show that the customers liked the system. Also on performance measurement, the system proved to be very effective as it managed to match 28 out of the 30 participants. Thus from these results it can be concluded that the system presents opportunity to engage more guests to book for a stay at the hotel.
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Keywords
Customer Loyalty, Customer Relationship Management, Facial Recognition, Personalisation