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- Title
A Machine Learning Based Method for Customer Behavior Prediction.
- Authors
Jing LI; Shuxiao PAN; Lei HUANG; Xin ZHU
- Abstract
Under the data-driven environment, market competition is increasingly fierce. Enterprises begin to pay attention to precise marketing to make costs down, improve marketing efficiency and competitiveness. E-mail marketing is widely used in enterprises due to its advantages of low cost and wide audience. This paper uses machinelearning techniques such as decision tree, cluster analysis and Naive Bayes algorithm to analyze customer characteristics and attributes with historical purchase records, and further analyzes the key factors that affect potential customers' purchase behavior by selecting models with high promotion degree through promotion graph, to realize accurate marketing. The results show that the prediction effect of decision tree is better than clustering analysis and Naive Bayesian algorithm, and has a higher promotion degree. The customers who are 45-55 years old and commute 1-2 kilometers away are more likely to make purchases if they do not have a car or have a car at home.
- Subjects
CONSUMER behavior; MACHINE learning; MARKETING costs; DECISION trees; BAYESIAN analysis; EMAIL
- Publication
Technical Gazette / Tehnički Vjesnik, 2019, Vol 26, Issue 6, p1670
- ISSN
1330-3651
- Publication type
Article
- DOI
10.17559/TV-20190603165825