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Sec 1: Introduction
Problem Statement
Download Resources
Sec 2: Understanding Data
Packages used
Load Data
Data Cleaning Part - 1
Data Cleaning Part - 2
Sec 3: Feature Engineering
Feature Engineering Part 1 - List price, payday, etc
Outlier Treatment
Data Preprocessing - Week finder
Adstock variables
EMA and SMA variables
NPS Score
Sales Calendar
Climate Data
Payday week and Holiday week
Course Review
Sec 4: Exploratory Data Analysis (EDA)
EDA Insights Part 1
EDA Insights Part 2
EDA Insights Part 3
Sec 5: Model Building
Approach 1 - Building Additive models
Stepwise model selection logic Theory
Approach 2 - Customized stepwise selection - Code Demo
Multicollinearity problems
Model building for Home Audio and Camera Accessory
Approach 3 - Building Multiplicative models
Sec 6: Distributive Lags Models
Approach 4 - Koyck Model of Distributed Lags
Determining the net effect of Influencers - Elasticity
Koyck Model part 2
Approach 5 - Distributive Lag Model (Additive)
Approach 6 - Distributive Lag Model (Multiplicative)
Sec 7: Non-Linear Modeling with GAM
Introduction to GAM modelling - Theory
Build GAM Models Part 1 - Code Demo
Build GAM Models Part 2 - Code Demo
Sec 8: Budget Optimization Strategies
Strategy 1 - Unconstrained Budget optimization one lever at a time (Demo)
Strategy 2 - Budget optimization with multiple levers (Demo)
Strategy 3 - Optimize multiple channels in presence of total budget constraint