- 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
Buy this book
- 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)
-
-
Introduction
Pages 1-6
-
Datasets
Pages 7-14
-
Literature Review
Pages 15-27
-
Tracking Purchase Behaviour Changes
Pages 29-47
-
Discovering Purchase Behaviour Patterns
Pages 49-73
-
Table of contents (8 chapters)
Recommended for you
Bibliographic Information
- Bibliographic Information
-
- Book Title
- Temporal Modelling of Customer Behaviour
- Authors
-
- Ling Luo
- 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
