Year: 2019
Type: dissertation
Abstract: In the last few years machine learning, a subset of artificial intelligence (AI), has become widely available and relatively effective at solving many business problems. This thesis reviews top marketing journal papers over the period 2012–2019 on the use of machine learning, offers a state-of-the-art overview on what is currently known about this quickly evolving field, and identifies avenues for further research. The review has three major findings: 1) Machine learning techniques show a significant improvement over traditional methods in most cases. 2) Machine learning has become a mainstream tool for researchers and practitioners in structuring very large amounts of user-generated content for marketing insights. 3) Despite the promising results, most uses of the technology have been researched relatively little in marketing literature. There exist several major research gaps, especially in prediction, personalization, segmentation and customer experience. Directions for further research indicate a pressing need for more research in this important area. Theoretical and managerial implications are provided.
Source: Aaltodoc (Aalto University)
Author: Jyri Heimo
Language: English
Subfield: Marketing
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2966428083