Timecodes 0:00-Introduction 1:30-Dataset Background , Data Loading & Data Clean-Up 3:12-Selecting The Right Time Granularity 5:39-Exploratory Data Analysis 8:00-Train/Test Split 8:50-Recency Frequency Monetary Analysis 14:05-Simple Average Customer Lifetime Value 15:12-PyMC Marketing Python Library 17:00-Fitting A Buy Till You Die BG-NBD Model To Training Data For Purch. Freq & Drop Out Rate 23:31-Plot Of Probability Of Active/Inactive For Individual Customer 24:39-Fitting A Buy Till You Die GG Model To Training Data For Monetary Value 26:42-Evaluating The Model Performance Against Test Data Results 28:48-Forecasting Future Purchasing Behaviours & Customer Lifetime Value 32:27-Wrap Up
@@coltallen309 oh my gosh this is a "senpai noticed me" moment. On a serious note, thank you and the team working on pymc marketing for creating a great enabler for better marketing analytics and clear documentation. Happy to be part of the user community. I wrote the article as part of a Feynman Technique experiment - to improve my own understanding by writing not just a how-to piece but also covering the why and so- what.
Timecodes
0:00-Introduction
1:30-Dataset Background , Data Loading & Data Clean-Up
3:12-Selecting The Right Time Granularity
5:39-Exploratory Data Analysis
8:00-Train/Test Split
8:50-Recency Frequency Monetary Analysis
14:05-Simple Average Customer Lifetime Value
15:12-PyMC Marketing Python Library
17:00-Fitting A Buy Till You Die BG-NBD Model To Training Data For Purch. Freq & Drop Out Rate
23:31-Plot Of Probability Of Active/Inactive For Individual Customer
24:39-Fitting A Buy Till You Die GG Model To Training Data For Monetary Value
26:42-Evaluating The Model Performance Against Test Data Results
28:48-Forecasting Future Purchasing Behaviours & Customer Lifetime Value
32:27-Wrap Up
Great video! I'm the lead developer for the CLV module of pymc-marketing, and left a detailed comment on your Medium article.
@@coltallen309 oh my gosh this is a "senpai noticed me" moment. On a serious note, thank you and the team working on pymc marketing for creating a great enabler for better marketing analytics and clear documentation. Happy to be part of the user community. I wrote the article as part of a Feynman Technique experiment - to improve my own understanding by writing not just a how-to piece but also covering the why and so- what.