Decision-making in real-world scenarios faces uncertainty. Fuzzy theory has been a means to represent such uncertainty. In this study, we propose an approach that incorporates bipolarity into multi-criteria decision-making processes applied to digital marketing. The proposal considers both the positive and negative dimensions of data, leading to better-informed decisions. Our contribution integrates bipolarity into Pythagorean fuzzy matrices, a framework that broadens the utility of bipolar fuzzy theory. Through computational experimentation, we identify the most effective strategy for digital marketing platforms. When compared to existing techniques, our approach shows advantages, underlining its potential to improve decision-making in uncertain scenarios and offering insights for businesses that refine their digital marketing strategies.