CHALUPA, Štěpán and Martin PETŘÍČEK. Using Customer Characteristics to Manage Marketing and Revenue Management Activities. TEM Journal. Serbia: UIKTEN, 2020, vol. 9, No 3, p. 1088-1093. ISSN 2217-8309. Available from: https://dx.doi.org/10.18421/TEM93-33.
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Basic information
Original name Using Customer Characteristics to Manage Marketing and Revenue Management Activities
Name (in English) Using Customer Characteristics to Manage Marketing and Revenue Management Activities
Authors CHALUPA, Štěpán and Martin PETŘÍČEK.
Edition TEM Journal, Serbia, UIKTEN, 2020, 2217-8309.
Other information
Type of outcome Article in a journal
Confidentiality degree is not subject to a state or trade secret
Organization unit University College Prague – University of International Relations and Institute of Hospitality Management and Economics, Ltd.
Doi http://dx.doi.org/10.18421/TEM93-33
UT WoS 000565865300033
Keywords (in Czech) Market segmentation; cluster analysis; Two-Step Cluster; Hospitality marketing; Revenue Management
Keywords in English Market segmentation; cluster analysis; Two-Step Cluster; Hospitality marketing; Revenue Management
Tags International impact, Reviewed
Changed by Changed by: Ing. Štěpán Chalupa, Ph.D., učo 10522. Changed: 15/12/2020 07:59.
Abstract
Understanding customer behaviour is an essential activity for hotel marketers and revenue managers. This article presents the statistical approach based on the data mining techniques focused on the extraction of valuable insight from big data. Using Two-Step Clustering, four major customers segments were identified, including their characteristics. Their description based on the booked room type, rate plan, booking window, net average room rate and length of stay can help the manager to plan better their activities.
Abstract (in English)
Understanding customer behaviour is an essential activity for hotel marketers and revenue managers. This article presents the statistical approach based on the data mining techniques focused on the extraction of valuable insight from big data. Using Two-Step Clustering, four major customers segments were identified, including their characteristics. Their description based on the booked room type, rate plan, booking window, net average room rate and length of stay can help the manager to plan better their activities.
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