Contextual and Behavioral Customer Journey Discovery Using a Genetic Approach

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ID Serval
serval:BIB_1AF7E5774867
Type
Partie de livre
Sous-type
Chapitre: chapitre ou section
Collection
Publications
Institution
Titre
Contextual and Behavioral Customer Journey Discovery Using a Genetic Approach
Titre du livre
Advances in Databases and Information Systems
Auteur⸱e⸱s
Bernard Gaël, Andritsos Periklis
Editeur
Springer International Publishing
ISBN
9783030287290
9783030287306
ISSN
0302-9743
1611-3349
Statut éditorial
Publié
Date de publication
2019
Pages
251-266
Langue
anglais
Résumé
With the advent of new technologies and the increase in customers’ expectations, services are becoming more complex. This complexity calls for new methods to understand, analyze, and improve service delivery. Summarizing customers’ experience using representative journeys that are displayed on a Customer Journey Map (CJM) is one of these techniques. We propose a genetic algorithm that automatically builds a CJM from raw customer experience recorded in a database. Mining representative journeys can be seen a clustering task where both the sequence of activities and some contextual data (e.g., demographics) are considered when measuring the similarity between journeys. We show that our genetic approach outperforms traditional ways of handling this clustering task. Moreover, we apply our algorithm on a real dataset to highlight the benefit of using a genetic approach.
Création de la notice
01/10/2019 12:21
Dernière modification de la notice
02/10/2019 6:08
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