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Artificial Intelligence Marketing and Predicting Consumer Choice

Artificial Intelligence Marketing and Predicting Consumer Choice

An Overview of Tools and Techniques

Steven Struhl


The goal of Artificial Intelligence Marketing and Predicting Consumer Choice is to explain and contrast the widely differing approaches to predictive analytics and predicting consumer choice, in practical terms that are grounded in business reality.

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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.

Table Of Contents

    • Chapter - 01: Who Should Read This Book and Why?
    • Chapter - 02: Getting the Project Going;
    • Chapter - 03: Conjoint, Discrete Choice, and Other Trade-Offs: Let's Do an Experiment;
    • Chapter - 04: Creating the Best, Newest Thing: Discrete Choice Modelling;
    • Chapter - 05: Conjoint Analysis and its Uses;
    • Chapter - 06: Finishing Experiments and On to the Non-Experimental World;
    • Chapter - 07: Machine Learning and Classifications that Grow on Trees;
    • Chapter - 08: Remarkable Predictive Models With Bayes Nets;
    • Chapter - 09: Artificial Intelligence, Ensembles and Neural Nets


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Book Details

  • EAN: 9780749479558
  • Edition: 1
  • Published: 3rd April 2017
  • Paperback
  • Dimensions: 234x156
  • 256 pages

About the Author

Dr. Steven Struhl PhD, MBA, MA has more than 25 years' experience in consulting and research, specializing in practical solutions based on statistical models of decision-making and behavior. In addition to text analytics and data mining, his work addresses how buying decisions are made, optimizing service delivery and product configurations and finding the meaningful differences among products and services. Steven also has taught graduate courses on statistical methods and data analysis. He speaks at conferences and has given numerous seminars on pricing, choice modelling, market segmentation and presenting data.

Steven Struhl

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