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Publicação
Prescriptive Modelling in Marketing: A Bibliometric Review
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Resumo(s)
In the rapidly growing field of marketing, prescriptive modeling has emerged as a pivotal tool, harnessing the power of data analytics and machine learning to inform strategic decision-making. The main objective of this thesis is to furnish a comprehensive bibliometric analysis of prescriptive modeling in marketing, with a concentration on identifying prevailing trends, circumstances, and specialized areas within this dynamic domain. By employing Bibliometrix, a cutting-edge tool for bibliometric analysis, the investigation methodically scrutinized a substantial corpus of literature, enabling a detailed and quantitative evaluation of influential works in this realm, supplemented by qualitative content analysis. The analysis exposed pivotal themes and trends, particularly the burgeoning focus on data-driven methodologies and the assimilation of prescriptive analytics in marketing practices. Noteworthy areas of focus include prognostication of consumer behavior, optimization of campaigns, and segmentation of markets, with emerging trends in digital marketing and analytics of social media. This research contributes to the academic conversation by presenting a structured overview of the progression and current state of prescriptive modeling in marketing. It acts as a valuable resource for scholars and practitioners, offering insights into the development of marketing strategies and highlighting the growing significance of data analytics in shaping marketing decisions.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Data Science for Marketing
Palavras-chave
Bibliometrics Prescriptive Modeling Prescriptive Analysis Marketing