Suri Chen
Suri Chen is a Principal Data Scientist at PepsiCo eCommerce. With a background in Operations Research from Columbia University, she possesses expertise in areas including optimization, neural networks, bayesian modeling, consumer clustering, and text mining. As an applied scientist in PepsiCo's cross-functional team, Suri addresses business challenges by harnessing the power of data and machine learning. Beyond her professional role, she is passionate about generative AI research, particularly in the realm of music generation.
Sessions
Abstract: In this talk, we will explore the world of Media Mix Modeling (MMM) and examine the application of Bayesian and Frequentist regression methods to derive valuable marketing insights. MMM plays a pivotal role in marketing strategy, enabling businesses to measure marketing effectiveness and optimize budget allocation across various channels. The presentation will offer an overview of both Bayesian and Frequentist approaches, comparing their principles and applications within the MMM context. We will present a real-world case, showcasing how these two models were used to deconstruct sales driven by several factors and generate actionable insights. Finally, we will share reflections and recommendations for marketers and data scientists regarding further exploration and adoption of different techniques in MMM, empowering businesses to make informed decisions and effectively allocate their marketing resources.