A0355
Title: Applying machine learning approach to marketing uncovering consumer insights through big data
Authors: Atsuho Nakayama - Tokyo Metropolitan University (Japan) [presenting]
Abstract: Vast amounts of marketing data are now available online. Automated collection of online clickstreams, messaging, word-of-mouth, transactional, location, and other data has significantly reduced the cost of data collection. The amount of data available today is increasing, and consumer behavior can be understood in great detail. In practice, the use of machine learning methods (including deep learning and cognitive systems) is encouraged. In recent years, convolutional neural networks (CNNs) have become the dominant algorithm for many computer vision tasks (acquisition, processing, and analysis of digital images), and many studies and applications using deep learning and AI have been conducted. The impact of them on marketing operations is expected to increase in the future. The question is how deep learning approaches should be used in marketing. Therefore, examples of applying machine learning and deep learning approaches are presented to the vast amount of consumer behavior data currently available, with the goal of supporting marketing decisions. The aim is to contribute to marketing research by deriving useful knowledge for market segmentation and positioning strategy formulation.
