Table of Contents
Chapter 1 - Introduction
- The Subject of Algorithmic Marketing
- The Definition of Algorithmic Marketing
- Historical Backgrounds and Context
- Programmatic Services
- Who Should Read This Book?
- Summary
Chapter 2 - Review of Predictive Modeling
- Descriptive, Predictive, and Prescriptive Analytics
- Economic Optimization
- Machine Learning
- Supervised Learning
- Representation Learning
- More Specialized Models
- Summary
Chapter 3 - Promotions and Advertisements
- Environment
- Business Objectives
- Targeting Pipeline
- Response Modeling and Measurement
- Building Blocks: Targeting and LTV Models
- Designing and Running Campaigns
- Resource Allocation
- Online Advertisements
- Measuring the Effectiveness
- Architecture of Targeting Systems
- Summary
Chapter 4 - Search
- Environment
- Business Objectives
- Building Blocks: Matching and Ranking
- Mixing Relevance Signals
- Semantic Analysis
- Search Methods for Merchandising
- Relevance Tuning
- Architecture of Merchandising Search Services
- Summary
Chapter 5 - Recommendations
- Environment
- Business Objectives
- Quality Evaluation
- Overview of Recommendation Methods
- Content-based Filtering
- Introduction to Collaborative Filtering
- Neighborhood-based Collaborative Filtering
- Model-based Collaborative Filtering
- Hybrid Methods
- Contextual Recommendations
- Non-Personalized Recommendations
- Multiple Objective Optimization
- Architecture of Recommender Systems
- Summary
Chapter 6 - Pricing and Assortment
- Environment
- The Impact of Pricing
- Price and Value
- Price and Demand
- Basic Price Structures
- Demand Prediction
- Price Optimization
- Resource Allocation
- Assortment Optimization
- Architecture of Price Management Systems
- Summary
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