MARKETING ANALYTICS EDUCATION AND DATA-DRIVEN DECISION-MAKING COMPETENCE AMONG UNIVERSITY STUDENTS IN NIGERIA

Abstract

This study examined whether marketing analytics education is related to data-driven decision-making competence among Nigerian university students, and whether that competence differs by year of study, programme type, and institution type. A cross-sectional survey was administered in six universities (three public and three private), and 412 usable questionnaires were analysed. Marketing analytics education was measured through curriculum content, tool-based practice and applied learning, and decision-making competence through data literacy, analytical reasoning, interpretation and decision application. Students reported moderate levels of both marketing analytics education (M = 3.17, SD = 0.53) and decision-making competence (M = 3.42, SD = 0.60). Overall marketing analytics education positively predicted competence (β = .61, p < .001, R² = .37). When the three dimensions were entered together, tool-based practice (β = .39) and applied learning (β = .37) were statistically significant predictors, whereas curriculum content was not (β = .08, p = .056); the model explained 40% of the variance. Competence differed by year of study (η² = .07) and by programme type (η² = .05) but not between public and private universities (p = .135). The findings suggest that analytics teaching built around software practice and applied projects is more closely tied to students’ competence than content coverage alone. The paper recommends adding tool-based practice and applied projects to analytics courses, extending introductory analytics to other programmes, resourcing practice-based teaching, and building industry partnerships, although the cross-sectional design and self-reported measures limit causal claims.