A Bayesian Approach to Media Mix Modeling by Michael Johns & Zhenyu Wang
Speakers: Michael Johns & Zhenyu Wang
This talk describes how we built a Bayesian Media Mix Model of new customer acquisition using PyMC3. We will explain the statistical structure of the model in detail, with special attention to nonlinear functional transformations, discuss some of the technical challenges we tackled when building it in a Bayesian framework, and touch on how we use it in production to guide our marketing strategy.
Part of PyMCon2020.
More details at http://www.pymcon.com
Discourse Discussion
https://discourse.pymc.io/t/a-bayesian-approach-to-media-mix-modeling-by-michael-johns-zhenyu-wang/6024
Видео A Bayesian Approach to Media Mix Modeling by Michael Johns & Zhenyu Wang канала PyMC Developers
This talk describes how we built a Bayesian Media Mix Model of new customer acquisition using PyMC3. We will explain the statistical structure of the model in detail, with special attention to nonlinear functional transformations, discuss some of the technical challenges we tackled when building it in a Bayesian framework, and touch on how we use it in production to guide our marketing strategy.
Part of PyMCon2020.
More details at http://www.pymcon.com
Discourse Discussion
https://discourse.pymc.io/t/a-bayesian-approach-to-media-mix-modeling-by-michael-johns-zhenyu-wang/6024
Видео A Bayesian Approach to Media Mix Modeling by Michael Johns & Zhenyu Wang канала PyMC Developers
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
![The Bayesian Workflow: Building a COVID-19 Model by Thomas Wiecki [Part 1]](https://i.ytimg.com/vi/ZxR3mw-Znzc/default.jpg)
![Cartesian Webinar: Marketing Mix Modeling (MMM)](https://i.ytimg.com/vi/5O3I7WtN-Ak/default.jpg)
![Microbial Cell Counting in a Noisy Environment by Cameron Davidson-Pilon](https://i.ytimg.com/vi/Oc6cgRwPEzU/default.jpg)
![What Is Probability? A Philosophical Question With Practical Implications for Bayesians by Max Sklar](https://i.ytimg.com/vi/cv2TvH7r6W0/default.jpg)
![Bayesian Dynamic Modeling: Sharing Information Across Time and Space](https://i.ytimg.com/vi/LVPikT58meg/default.jpg)
![Bayesian nonparametrics in document and language modeling](https://i.ytimg.com/vi/FO0fgVS9OmE/default.jpg)
![PyMCon 2020 Welcome by Ravin Kumar](https://i.ytimg.com/vi/LTLfeNyioR8/default.jpg)
![The Why and How of One Domain-Specific PyMC3 Extension by Dan Foreman-Mackey](https://i.ytimg.com/vi/ESyo2eeo-UM/default.jpg)
![Using Hierarchical Multinomial Regression to Predict Elections in Paris districts by Alex Andorra](https://i.ytimg.com/vi/EYdIzSYwbSw/default.jpg)
![Industry Preview 2015 - Panel: "The Colliding Worlds of Attribution and Marketing Mix Modeling"](https://i.ytimg.com/vi/VNsmFYu9Qrk/default.jpg)
![Media Marketing Mix Modeling](https://i.ytimg.com/vi/TsLQTA5dkTQ/default.jpg)
![ThinkVine: A breakthrough approach to marketing mix optimisation](https://i.ytimg.com/vi/f4UYdZKy0-8/default.jpg)
![Building an ordered logistic regression model for toxicity prediction by Elizaveta Semenova](https://i.ytimg.com/vi/fxydbmTfsk4/default.jpg)
![Frequentism and Bayesianism: What's the Big Deal? | SciPy 2014 | Jake VanderPlas](https://i.ytimg.com/vi/KhAUfqhLakw/default.jpg)
![Bayesian Networks](https://i.ytimg.com/vi/TuGDMj43ehw/default.jpg)
![Hierarchical Time Series With Prophet and PyMC3 by Matthijs Brouns](https://i.ytimg.com/vi/appLxcMLT9Y/default.jpg)
![Learning Bayesian Statistics With Pokemon GO by Tushar Chandra](https://i.ytimg.com/vi/v0PiWcnEpiw/default.jpg)
![Market Mix Modeling and ROI Optimization](https://i.ytimg.com/vi/bw992U0VlMQ/default.jpg)
![Marketing Mix Modeling](https://i.ytimg.com/vi/PwAxg_IIPDM/default.jpg)
![Calibr8: Going Beyond Linear Ranges With Non-Linear Calibration Curves and Multilevel Modeling](https://i.ytimg.com/vi/14Ca--VJKxI/default.jpg)