Hajime Takeda
I started my career as a data analyst at a global consumer goods company. Currently, I am a leader in data analytics, web development, and digital marketing at a startup.
Sessions
Media Mix Modeling, also called Marketing Mix Modeling (MMM), is a technique that helps advertisers to quantify the impact of several marketing investments on sales.
If a company advertises in multiple media (TV, digital ads, magazines, etc.), how can we measure the effectiveness and make future budget allocation decisions? Traditionally, regression modeling has been used, but obtaining actionable insights with that approach has been challenging.
Recently, many researchers and data scientists have tackled this problem using Bayesian statistical approaches. For example, Google has published multiple papers about this topic.
In this talk, I will show the key concepts of a Bayesian approach to MMM, its implementation using Python, and practical tips.