Full Tutorial: Customer Lifetime Value (CLV) in Python (Feat. Lifetimes + Pycaret)

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Table of Contents:
00:00 Introduction: Customer Lifetime Value for Data Scientists with Python
1:51 Agenda: What we are covering today
4:20 Why listen to me
8:29 Customer Lifetime Value and Machine Learning
10:10 Quick Concepts: Customer Lifetime Value
15:46 Full Code Tutorial: Customer Lifetime Value for Retail
16:30 Project Setup: 3 CLV Scripts + 2,600,000 Row Transactions Data
18:14 Part 1: Descriptive CLV Models
25:30 Aggregation CLV Models (Descriptive)
36:25 Cohort CLV Models (Descriptive)
42:15 Probabilistic CLV Models with Lifetimes (Predictive)
56:45 Machine Learning CLV Models with Pycaret (Predictive)
1:11:58 Conclusions

[@dhananjaygowda171]

Hey Matt, In reg.predict_model, you have included the dataframe that contains the target variable "sales_90_value", isn't it obvious that the model will be easily influenced by this value and predict almost nearest values as the actual values? shouldn't the target variable be excluded from the data when passing it for prediction? Can you please clarify here why you have included it. Thank You😄

[@BusinessScience]

It’s not included in the predictors. So the xgboost model won’t use it. Only as a regression label.