Artificial intelligence marketing and predicting consumer choice: an overview of tools and techniques

Table of contents
Section - 01: Who Should Read this Book and Why?;
Section - 02: Getting the Project Going;
Section - 03: Conjoint, Discrete Choice and Other Trade-offs: Let’s Do an Experiment;
Section - 04: Creating the Best, Newest Thing: Discrete Choice Modelling;
Section - 05: Conjoint Analysis and its Uses;
Section - 06: Predictive Models: Via Classifications that Grow on Trees;
Section - 07: Remarkable Predictive Models with Bayes Nets;
Section - 08: Putting it Together: What to Use When;

The ability to predict consumer choice is a fundamental aspect to success for any business. In the context of artificial intelligence marketing, there are a wide array of predictive analytic techniques available to achieve this purpose, each with its own unique advantages and disadvantages. Artificial Intelligence Marketing and Predicting Consumer Choice serves to integrate these widely disparate approaches, and show the strengths, weaknesses, and best applications of each. It provides a bridge between the person who must apply or learn these problem-solving methods and the community of experts who do the actual analysis. It is also a practical and accessible guide to the many remarkable advances that have been recently made in this fascinating field.

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