Deep Learning Based Prediction Model for the Next Purchase

• Published in: Advances in Electrical and Computer Engineering Vol. 20; no. 2; pp. 35 - 44
• Main Authors: UTKU, A., AKCAYOL, M. A.
• Format: Journal Article
• Language: English
• Published: Suceava Stefan cel Mare University of Suceava 01.05.2020
• Subjects: Accuracy; Business; Cable television broadcasting industry; Consumer behavior; Datasets; Deep learning; Digital currencies; e-commerce; Electricity; Electronic commerce; Hepatitis; Machine learning; Marketing; Methods; Neural networks; prediction; Prediction models; Probability distribution; Stock exchanges; Studies; Time series; time series analysis; Traffic flow; United States; Trinidad and Tobago; California
• ISSN: 1582-7445; 1844-7600
• DOI: 10.4316/AECE.2020.02005

Time series represent the consecutive measurements taken at equally spaced time intervals. Time series prediction uses the information in a time series to predict future values. The future value prediction is important for many business and administrative decision makers especially in e-commerce. To promote business, sales prediction and sensing of future consumer behavior can help business decision makers in marketing campaigns, budget and resource planning. In this study, deep learning based a new prediction model has been developed for the time of next purchase in e-commerce. The proposed model has been extensively tested and compared with RF, ARIMA, CNN and MLP using a retail market dataset. The experimental results show that the developed model has been more successful than RF, ARIMA, CNN and MLP to predict the time of the next purchase. Index Terms--time series analysis, deep learning, prediction, e-commerce.