Publicação
Data-driven decision-making in marketing: a systematic literature review of emerging themes and research gaps
| Resumo: | This study assesses how Data-Driven Decision-Making (DDDM) impacts marketing practices and research. Using the PRISMA 2020 protocol, this research conducted systematic reviews of 94 peer-reviewed articles and utilized bibliometric and thematic analyses. From this, four major themes emerged: improvement in the customer experience via the personalization of marketing; marketing driven by innovation through data resource versatility, Machine Learning, analytics, and Artificial Intelligence; performance enhancement through the optimal allocation of resources; and the data governance and ethical use of such resources, and the use of such data resources. This study illustrates how the combination of multi-level theory and methodical stricture accounts for the systemic influence of DDDM in marketing. This study adds to these theories by proposing a cohesive and synthesized understanding of the interplay of the technological, organizational, and governance elements in data-driven marketing. This research provides organizations with actionable guidance aimed at increasing effective analytics-driven decision-making, while also ensuring the responsible use of data. |
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| Autores principais: | Cruz, Rui Nunes |
| Outros Autores: | Rosário, Albérico Travassos |
| Assunto: | Data-driven decision-making Marketing Systematic literature review Bibliometric analysis PRISMA Systemic framework |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | contribuição para revista |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Setúbal |
| Idioma: | inglês |
| Origem: | Instituto Politécnico de Setúbal |
| Resumo: | This study assesses how Data-Driven Decision-Making (DDDM) impacts marketing practices and research. Using the PRISMA 2020 protocol, this research conducted systematic reviews of 94 peer-reviewed articles and utilized bibliometric and thematic analyses. From this, four major themes emerged: improvement in the customer experience via the personalization of marketing; marketing driven by innovation through data resource versatility, Machine Learning, analytics, and Artificial Intelligence; performance enhancement through the optimal allocation of resources; and the data governance and ethical use of such resources, and the use of such data resources. This study illustrates how the combination of multi-level theory and methodical stricture accounts for the systemic influence of DDDM in marketing. This study adds to these theories by proposing a cohesive and synthesized understanding of the interplay of the technological, organizational, and governance elements in data-driven marketing. This research provides organizations with actionable guidance aimed at increasing effective analytics-driven decision-making, while also ensuring the responsible use of data. |
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