Bibliometric Review of Applications of Deep Learning in Marketing: Advances in Resources and Top Trend Analysis

Abstract

Marketers are compelled to come up with innovative ways to meet customer expectations while maximizing their available resources. In order to do this, marketers are using artificial intelligence and machine learning and especially deep learning. This research conducts an analysis by using bibliometric methods, at deep learning literatures in marketing. Using a bibliometric approach, 235 articles published in 2017–2022 were collected from journals indexed in the Scopus database. Multiple software (R studio, Excel, and Biblioshiny) were employed to analyse the data. The occurrence of publications were determined by year, publication source information and authors, journals, countries, institutions, thematic maps, and current trends of topics, clear, and reliable as a result of this technique. At the end of the report, the findings and a strategy for future study are summarised and discussed. In marketing research, there is a growing interest in deep learning. This article is both instructive and supplementary, since it covers the majority of marketing's fundamentals.