Antonio Nuno, de Almeida Ana, Nunes Luís
Nova IMS, Universidade Nova de Lisboa, Lisbon, Portugal.
CITUR, Faro, Portugal.
Data Brief. 2020 Nov 24;33:106583. doi: 10.1016/j.dib.2020.106583. eCollection 2020 Dec.
This data article describes a hotel customer dataset with 31 variables describing a total of 83,590 instances (customers). It comprehends three full years of customer behavioral data. In addition to personal and behavioral information, the dataset also contains demographic and geographical information. This dataset contributes to reducing the lack of real-world business data that can be used for educational and research purposes. The dataset can be used in data mining, machine learning, and other analytical field problems in the scope of data science. Due to its unit of analysis, it is a dataset especially suitable for building customer segmentation models, including clustering and RFM (Recency, Frequency, and Monetary value) models, but also be used in classification and regression problems.
本数据文章描述了一个酒店客户数据集，其中有31个变量，共描述了83590个实例（客户）。它包含了整整三年的客户行为数据。除了个人和行为信息外，该数据集还包含人口统计和地理信息。这个数据集有助于减少可用于教育和研究目的的现实世界商业数据的匮乏。该数据集可用于数据科学领域的数据挖掘、机器学习及其他分析领域的问题。由于其分析单位，它是一个特别适合构建客户细分模型的数据集，包括聚类和RFM（最近一次消费、消费频率和消费金额）模型，也可用于分类和回归问题。
