Marketing Mix Modeling fight: Cassandra vs PyMC Marketing

Marketing Mix Modeling using Python - PyMC Marketing vs Cassandra a MMM software

Find the resources used in the video here:

Data request checklist: https://bit.ly/3Udaopi
MMM Dataset: https://bit.ly/44l5WcE
Colab (code): https://bit.ly/3QoroYE
Cassandra: https://www.cassandra.app/

PyMC Marketing Repo: https://www.pymc-marketing.io/en/stable/
Cassandra: https://cassandra.app


Here is the agenda of the video:

0:00 Intro
0:40 MMM Data Request Checklist
2:08 Installing pymc-marketing
4:15 MMM data cleaning - Python
6:15 Extract Seasonality function - Python
10:15 MMM feature selection - PyMC Marketing
12:55 Py-MC configuration & training
13:15 Cassandra MMM
13:48 MMM feature selection - Cassandra
14:31 Automatic EDA Analysis - Cassandra
15:03 Data iteration
16:00 MMM training - Cassandra
17:22 PyMC re-training after data iteration
18:02 Contribution Decomposition over time - PyMC Marketing
20:14 Diminishing returns - PyMC Marketing
22:13 MMM Prediction vs Actual sales - PyMC Marketing
25:22 ROAS probability distribution analysis - PyMC Marketing
26:00 Model selection - Cassandra
27:50 ROI analysis - Cassandra
29:00 AI MMM suggestions - Cassandra
30:30 Seasonality analysis - Cassandra
31:00 Contribution over time - Cassandra
33:00 Results comparison between PyMc Marketing & Cassandra
37:00 Predict on test data - PyMC Marketing
38:25 Budget allocator - PyMC vs Cassandra
42:00 Conclusions and evaluation grades