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Camacho, P., Almeida, A. de. & António, N. (2020). Using customer segmentation to build a hybrid recommendation model. In Carvalho, J. V. de., Rocha, Á., Liberato, P., and Peña, A. (Ed.), Advances in Tourism, Technology and Systems. Smart Innovation, Systems and Technologies. (pp. 299-308). Cartagena: Springer Singapore.

P. Camacho et al.,  "Using customer segmentation to build a hybrid recommendation model", in Advances in Tourism, Technology and Systems. Smart Innovation, Systems and Technologies, Carvalho, J. V. de., Rocha, Á., Liberato, P., and Peña, A., Ed., Cartagena, Springer Singapore, 2020, vol. 208, pp. 299-308

@inproceedings{camacho2020_1714737796342,
	author = "Camacho, P. and Almeida, A. de. and António, N.",
	title = "Using customer segmentation to build a hybrid recommendation model",
	booktitle = "Advances in Tourism, Technology and Systems. Smart Innovation, Systems and Technologies",
	year = "2020",
	editor = "Carvalho, J. V. de., Rocha, Á., Liberato, P., and Peña, A.",
	volume = "208",
	number = "",
	series = "",
	doi = "10.1007/978-981-33-4256-9_27",
	pages = "299-308",
	publisher = "Springer Singapore",
	address = "Cartagena",
	organization = "",
	url = "https://link.springer.com/book/10.1007/978-981-33-4256-9"
}

TY  - CPAPER
TI  - Using customer segmentation to build a hybrid recommendation model
T2  - Advances in Tourism, Technology and Systems. Smart Innovation, Systems and Technologies
VL  - 208
AU  - Camacho, P.
AU  - Almeida, A. de.
AU  - António, N.
PY  - 2020
SP  - 299-308
SN  - 2190-3018
DO  - 10.1007/978-981-33-4256-9_27
CY  - Cartagena
UR  - https://link.springer.com/book/10.1007/978-981-33-4256-9
AB  - The growing trend in leisure tourism has been closely followed by the number of hospitality services. Nowadays, customers are more sophisticated and demand a personalized and simplified experience, which is commonly achieved through the use of technological means for anticipating customer behavior. Thus, the ability to predict a customer’s willingness to buy is also a growing trend in hospitality businesses to reach more customers and consolidate existing ones. The acquisition of a transfer service through website reservation generates data that can be used to perform customer segmentation and enable recommendations for other products or services to a customer, like recreation experiences. This work uses data from a Portuguese private transfer company to understand how its private transfer business customers can be segmented and how to predict their behavior to enhance services cross-selling. Information extracted from the data acquired with the private transfer reservations is used to train a model to predict customer willingness to buy, and based on it, offer leisure services to customers. For that, a hybrid classifier was trained to offer recommendations to a customer when he/she is booking a transfer. The model employs a two-phase process: first, a binary classifier asserts if the customer who’s buying the transfer would eventually buy a service experience. In that case, a multi-class model decides what should be the most likely experience to be recommended.
ER  -