1. Research papers and whitepapers
Challenges And Opportunities In Media Mix Modeling (2017, Google - Chan et al.)
Bayesian Methods for Media Mix Modeling with Carryover and Shape Effects (2017, Google - Jin et al.)
Geo-level Bayesian Hierarchical Media Mix Modeling (2017, Google - Sun et al.)
Hierarchical Bayesian Approach to Improve Media Mix Models Using Category Data (2017, Google, Wang et. al)
Bayesian Time Varying Coefficient Model with Applications to Marketing Mix Modeling (2021, Uber - Ng et al.)
Hierarchical Marketing Mix Models with Sign Constraints (2020, Cheng et al.)
Bayesian Hierarchical Media Mix Model Incorporating Reach and Frequency Data (2023, Zhang et al.)
Media Mix Model Calibration With Bayesian Priors (2024, Zhang et al.)