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Springer Theses

Temporal Modelling of Customer Behaviour

Authors: Luo, Ling

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  • Nominated as an outstanding Ph.D. thesis by the University of Sydney, Australia
  • Presents innovative machine learning techniques for modelling dynamic customer purchasing behaviour
  • Reviews cutting-edge clustering techniques for temporal behavioural data
  • Highlights applications in the assessment of web-based health programs and supermarket promotions
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eBook $129.00
price for USA in USD
  • ISBN 978-3-030-18289-2
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $169.99
price for USA in USD
About this book

This book describes advanced machine learning models – such as temporal collaborative filtering, stochastic models and Bayesian nonparametrics – for analysing customer behaviour. It shows how they are used to track changes in customer behaviour, monitor the evolution of customer groups, and detect various factors, such as seasonal effects and preference drifts, that may influence customers’ purchasing behaviour. In addition, the book presents four case studies conducted with data from a supermarket health program in which the customers were segmented and the impact of promotional activities on different segments was evaluated. The outcomes confirm that the models developed here can be used to effectively analyse dynamic behaviour and increase customer engagement. Importantly, the methods introduced here can also be used to analyse other types of behavioural data such as activities on social networks, and educational systems.


Table of contents (8 chapters)

Table of contents (8 chapters)

Buy this book

eBook $129.00
price for USA in USD
  • ISBN 978-3-030-18289-2
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $169.99
price for USA in USD
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Bibliographic Information

Bibliographic Information
Book Title
Temporal Modelling of Customer Behaviour
Authors
Series Title
Springer Theses
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-18289-2
DOI
10.1007/978-3-030-18289-2
Hardcover ISBN
978-3-030-18288-5
Series ISSN
2190-5053
Edition Number
1
Number of Pages
XV, 123
Number of Illustrations
4 b/w illustrations, 35 illustrations in colour
Topics