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Artificial Intelligence Marketing and Predicting Consumer Choice
An Overview of Tools and Techniques
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About the book
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.
Online resources: bonus chapters on AI, ensembles and neural nets, and finishing experiments, plus single and multiple product simulators.
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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;
Reviews
- Full of hard-won practical wisdom, this is a comprehensive guide to navigating the complexity of market forecasting. Foregoing the hyperbole that so often characterizes discussions of artificial intelligence, Dr. Struhl thoroughly explains a wide range of methods, where their difficulties lie, and how to get the best insights from each.
- Peter Goldstein, Software Engineer, Google
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