Machine Learning in Marketing - Juan Orduz

We talked about:

00:00 DataTalks.Club intro
02:08 Juan’s background
07:31 Typical problems in marketing that are solved with ML
10:18 Attribution model
13:03 Media Mix Model – detecting uplift and channel saturation
20:49 Changes to privacy regulations and its effect on user tracking
23:04 User retention and churn prevention
30:45 A/B testing to detect uplift
35:15 Statistical approach vs machine learning (setting a benchmark)
37:05 Does retraining MMM models often improve efficiency?
38:11 Attribution model baselines
39:41 Choosing a decay rate for channels (Bayesian linear regression)
40:46 Learning resource suggestions
42:06 Bayesian approach vs Frequentist approach
48:06 Suggestions for creating a marketing department
55:12 Most challenging problems in marketing
57:02 The importance of knowing marketing domain knowledge for data scientists
58:48 Juan’s blog and other learning resources
1:00:22 Finding Juan online

Links:

[Tingtvph]

I have no idea for this kind of marketing but thank you for sharing this video. Watching from republic of the philippines.