Marketing Mix Modeling

Marketing mix modeling (MMM) aims to quantify the impact of various marketing channels on sales or other key performance indicators, enabling data-driven budget allocation. Current research emphasizes improving model accuracy and interpretability, focusing on causal inference techniques to disentangle complex channel interactions and incorporating advanced algorithms like Bayesian methods and Shapley value regression to handle heterogeneous effects and partner contributions. These advancements enhance the precision of marketing attribution and optimization, offering significant value to businesses by improving return on investment and informing strategic marketing decisions.