Quality versus Quantity in Digital Marketing: Evidence from Italian Companies

The diffusion of digital technologies has reshaped marketing activities, fostering data-driven digital marketing strategies. However, empirical research often relies on descriptive indicators that fail to capture the latent and multidimensional nature of digital marketing adoption. This study addresses this limitation by proposing an integrated statistical framework for the analysis of digital marketing practices. The framework combines principal component analysis, cluster analysis and non-parametric combination (NPC) ranking to examine adoption patterns across firms and sectors over two time periods. The empirical results reveal persistent heterogeneity in digital marketing strategies and a gradual shift from tool-oriented adoption toward analytics-intensive and capability-based approaches. Although overall adoption increases over time, firms and sectors follow differentiated trajectories rather than converging toward a single model. Methodologically, the study highlights the benefits of integrating complementary multivariate techniques to enhance interpretability and robustness. From an applied perspective, the findings show how quantitative evidence can support strategic decision-making in digital marketing, bridging quality and quantity dimensions.