Performance analysis of social media platforms: evidence of digital marketing
Previous studies in the literature have shown that Digital Marketing (DM) can be a factor influencing competitiveness and the performance of marketing actions so that a company can correctly reach the target audience. From this literary assumption, it is imperative to evaluate tools that can help ma...
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Veröffentlicht in: | Journal of marketing analytics 2024-09, Vol.12 (3), p.599-610 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Previous studies in the literature have shown that Digital Marketing (DM) can be a factor influencing competitiveness and the performance of marketing actions so that a company can correctly reach the target audience. From this literary assumption, it is imperative to evaluate tools that can help marketing managers in decision-making to select the most social media platform to use the DM. In this context, this article aims to analyze the performance of social media platforms for using the strategies DM in organizations. from the point of view of experts from different organizations that use DM for marketing actions. To provide empirical evidence, the selection of criteria was based on the eight dimensions of the DM mix to the lens of multi-criteria decision-making based on the inter-criteria correlation method (CRITIC). This method adhered to the order of preference by similarity technique to find an ideal solution with the help of the Fuzzy TOPSIS environment. The results discovered corroborate the previous literature and stand out, mainly by showing that the main criterion with greater weight among the eight analyzed dimensions was promotion (Cr5). Based on this finding, these results indicate that the best performing alternative for DM actions for the specific case was the A1-Facebook platform. This article brings reflections, and presents a robust tool of quantitative analysis in addition to bringing theoretical and managerial contributions that can direct DM strategies in the consumer's journey through social media platforms. |
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ISSN: | 2050-3318 2050-3326 |
DOI: | 10.1057/s41270-023-00211-z |