- Serves to integrate widely disparate approaches to predicting consumer choice via artificial intelligence marketing, showing the strengths, weaknesses and best applications of each method and point of view.
- Covers methods and techniques including Discrete Choice Modelling, Conjoint Analysis and Machine Learning Models, placing all of these in the wider context of predictive analytics and artificial intelligence marketing.
- Explores the human side of advanced analytics - using data to predict what people will choose.
- Includes extensive diagrams and charts, pointers on tools and techniques, definition boxes and practical hints and tips.
- Online resources: bonus chapters on AI, ensembles and neural nets, and finishing experiments, and a range of multiple or single product simulators
Artificial Intelligence Marketing and Predicting Consumer Choice
An Overview of Tools and Techniques
Compare and contrast the widely differing approaches to predictive analytics and predicting consumer choice with this comprehensive guide to marketing analytics.
Key features at a glance
EAN: 9780749479558
Edition: 1
Published:
Format: 234x154
272 pages
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.
About the authors
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.
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.
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