Data-Driven Decisions: Leveraging Analytics for Strategic Marketing Management

This study investigates the impact of data-driven decision-making, customer data utilization, and predictive analytics on the marketing performance of small and medium enterprises (SMEs) in Medan. Utilizing a quantitative research design, data was collected through structured questionnaires from a sample of 83 SMEs that possess a Business Identification Number (NIB). The analysis involved statistical techniques, including t-tests, F-tests, and regression analysis, using the Statistical Package for the Social Sciences (SPSS). The results reveal a significant positive relationship between the independent variables and marketing performance, with the regression model explaining approximately 58.3% of the variance in marketing outcomes. Findings indicate that prioritizing data-driven strategies can lead to enhanced decision-making and improved business performance for SMEs. This research contributes valuable insights for practitioners and scholars by highlighting the critical role of analytics in developing effective marketing strategies and fostering sustainable growth in a competitive landscape.

Authors

Publication Details

Journal
Equator Journal of Management and Entrepreneurship (EJME)
Published
2024-10-25
DOI
https://doi.org/10.26418/ejme.v12i4.81935
Citations
2
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
1.06
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article

Data-Driven Decisions: Leveraging Analytics for Strategic Marketing Management

Febrina Soraya Tanjung
2 citations
Equator Journal of Management and Entrepreneurship (EJME)
Big Data and Business Intelligence
1.06
article

Data-Driven Decisions: Leveraging Analytics for Strategic Marketing Management

Febrina Soraya Tanjung
article en
2 citations

Abstract

This study investigates the impact of data-driven decision-making, customer data utilization, and predictive analytics on the marketing performance of small and medium enterprises (SMEs) in Medan. Utilizing a quantitative research design, data was collected through structured questionnaires from a sample of 83 SMEs that possess a Business Identification Number (NIB). The analysis involved statistical techniques, including t-tests, F-tests, and regression analysis, using the Statistical Package for the Social Sciences (SPSS). The results reveal a significant positive relationship between the independent variables and marketing performance, with the regression model explaining approximately 58.3% of the variance in marketing outcomes. Findings indicate that prioritizing data-driven strategies can lead to enhanced decision-making and improved business performance for SMEs. This research contributes valuable insights for practitioners and scholars by highlighting the critical role of analytics in developing effective marketing strategies and fostering sustainable growth in a competitive landscape.

Equator Journal of Management and Entrepreneurship (EJME)Vol. 12(4)
Openalex Percentile: Top 16%
Big Data and Business Intelligence
1.06
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