From 0a4b8c107c5254114b1087cfd3c59e5885aac254 Mon Sep 17 00:00:00 2001 From: BerylKanali <50364045+BerylKanali@users.noreply.github.com> Date: Mon, 1 Aug 2022 21:35:35 +0300 Subject: [PATCH] Add timestamps for video 12: Michael-Zhenyu Media Mix Modelling ### Reference Toward #11 ### Description Add timestamps for video 12: Michael-Zhenyu Media Mix Modelling --- videos-list/12-michael-zhenyu.md | 15 ++++++++++++--- 1 file changed, 12 insertions(+), 3 deletions(-) diff --git a/videos-list/12-michael-zhenyu.md b/videos-list/12-michael-zhenyu.md index 469ecd0..99bf2d2 100644 --- a/videos-list/12-michael-zhenyu.md +++ b/videos-list/12-michael-zhenyu.md @@ -20,12 +20,21 @@ https://discourse.pymc.io/t/a-bayesian-approach-to-media-mix-modeling-by-michael - Model applications ## Timestamps -0:00 Outline of presenation +0:00 Introduction and outline of presentation 1:16 Marketing at HelloFresh (funnels, conversion, channels) 2:40 Measuring the effectiveness of marketing -5:00 Multivariate regression model +5:00 What is Media Mix Modelling? +6:20 Structure of a Media Mix Model +7:51 Transformation functions (Reach function and Adstock function) +10:53 Benefits of using bayesian methods to build a Media Mix Model +13:07 Hellofresh's Media Mix Model structure +19:46 Geometric Adstock Function +20:54 Nonlinear Saturation Function +21:16 The bayesian MMM workflow +22:39 Applications of HelloFresh's Media Mix Model +26:41 Constrained optimization algorithm +29:18 Thank you! -x:xx Help us add timestamps here: https://github.com/pymc-devs/video-timestamps Speaker info: Michael Johns is a data scientist at HelloFresh US. His work focuses on building statistical models for business applications, such as optimizing marketing strategy, customer acquisition forecasting and customer retention.