Using Customer Segmentation to Build a Hybrid Recommendation Model

Pedro Camacho, Ana de Almeida, Nuno António

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationAdvances in Tourism, Technology and Systems - Selected Papers from ICOTTS20
EditorsJoão Vidal de Carvalho, Pedro Liberato, Álvaro Rocha, Alejandro Peña
PublisherSpringer Science and Business Media Deutschland GmbH
Pages299-308
Number of pages10
ISBN (Print)9789813342552
DOIs
Publication statusPublished - 2021
EventInternational Conference on Tourism, Technology and Systems, ICOTTS 2020 - Cartagena, Colombia
Duration: 29 Oct 202031 Oct 2020

Publication series

NameSmart Innovation, Systems and Technologies
Volume208
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Conference

ConferenceInternational Conference on Tourism, Technology and Systems, ICOTTS 2020
CountryColombia
CityCartagena
Period29/10/2031/10/20

Keywords

  • Customer segmentation
  • Hospitality
  • Recommendation system
  • Transfers

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