- 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