Modeling the Relationship Between Product Innovation, Digital Marketing, and SME Revenue Growth Using Synthetic Data

Abstract

Small and medium-sized enterprises (SMEs) are widely regarded as engines of employment and value creation in emerging economies, yet the mechanisms linking their innovation behaviour and marketing capabilities to financial performance remain incompletely modelled. This study develops and tests a structural model in which product innovation and digital marketing jointly shape SME revenue growth, including the moderating role of digital marketing on the innovation–growth path. Because access to verified firm-level financial micro-data is constrained by confidentiality and reporting gaps, the analysis is conducted on a synthetic dataset of 250 simulated SMEs generated from a transparent data-generating process with known ground-truth parameters. The synthetic design allows the estimation procedure to be validated against the parameters used to create the data, an evaluation that is impossible with conventional observational samples. Hierarchical ordinary least squares regression shows that product innovation (β = 0.33, p < 0.001) and digital marketing (β = 0.55, p < 0.001) are both positively associated with revenue growth, together explaining 56.8% of its variance. A significant positive interaction (b = 1.89, p = 0.001; ΔR² = 0.018) indicates that the returns to product innovation are amplified when firms invest more heavily in digital marketing. Recovered coefficients closely track the parameters embedded in the data-generating process, confirming that the modelling pipeline is well specified. The paper positions synthetic data as a methodological complement—not a substitute—for empirical SME research, useful for pipeline validation, teaching, and pre-registration of analysis plans. All data are simulated and contain no real firms or individuals.