Book: Introduction to Algorithmic Marketing / I.Katcov

Introduction to Algorithmic Marketing: Artificial Intelligence for Marketing OperationsDo you look for the most complete text book to understand A.I. tools for marketing? Below is one of the first such books.

The author provides the definition of algorithmic marketing, makes review of predictive modeling, tells about artificial intelligence for advertisements, pricing and product assortiment. So it is one of the first book that describes all marketing tools through machine learning.

Introduction to Algorithmic Marketing: Artificial Intelligence for Marketing Operations / Ilia Katcov

Author: Ilia Katcov
Publisher: Ilia Katcov, Grid Dynamic (2017)
Language: English
Pages: 506 pages

Table of Contents:

1. Introduction

1.1 The Subject of Algorithmic Marketing
1.2 The Definition of Algorithmic Marketing
1.3 Historical Backgrounds and Context
1.4 ProgrammaticServices
1.5 Who Should Read This Book?
1.6 Summary

2. Review of predictive modeling 

2.1 Descriptive, Predictive, and Prescriptive Analytics
2.2 Economic Optimization
2.3 Machine Learning
2.4 Supervised Learning
2.5 Representation Learning
2.6 More Specialized Models
2.7 Summary

3. Promotions and advertisements

3.1 Environment
3.2 Business Objectives
3.3 Targeting Pipeline
3.4 Response Modeling and Measurement
3.5 Building Blocks: Targeting and LTV Models
3.6 Designing and Running Campaigns
3.7 Resource Allocation
3.8 OnlineAdvertisements
3.9 Measuring the Effectiveness
3.10 Architecture of Targeting Systems
3.11 Summary

4. Search

4.1 Environment
4.2 Business Objectives
4.3 Building Blocks: Matching and Ranking
4.4 Mixing Relevance Signals.
4.5 Semantic Analysis
4.6 Search Methods for Merchandising
4.7 Relevance Tuning.
4.8 Architecture of Merchandising Search Services
4.9 Summary

5 Recommendations

5.1 Environment
5.2 Business Objectives
5.3 Quality Evaluation
5.4 Overview of Recommendation Methods
5.5 Content-basedFiltering
5.6 Introduction to Collaborative Filtering
5.7 Neighborhood-based Collaborative Filtering
5.8 Model-based Collaborative Filtering

6. Pricing and assortment

6.1 Environment
6.2 The Impact of Pricing
6.3 Price and Value
6.4 Price and Demand
6.5 Basic Price Structures
6.6 Demand Prediction
6.7 Price Optimization
6.8 Resource Allocation
6.9 Assortment Optimization.
6.10 Architecture of Price Management Systems
6.11 Summary


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