Marketing Analytics: A Machine Learning Approach
- Length: 350 pages
- Edition: 1
- Language: English
- Publisher: Apple Academic Press
- Publication Date: 2023-02-02
- ISBN-10: 1774910888
- ISBN-13: 9781774910887
- Sales Rank: #0 (See Top 100 Books)
With businesses becoming ever more competitive, marketing strategies need to be more precise and performance oriented. Companies are investing considerably in analytical infrastructure for marketing. This new volume, Marketing Analytics: A Machine Learning Approach, enlightens readers on the application of analytics in marketing and the process of analytics, providing a foundation on the concepts and algorithms of machine learning and statistics. The book simplifies analytics for businesses and explains its uses in different aspects of marketing in a way that even marketers with no prior analytics experience will find it easy to follow, giving them to tools to make better business decisions.
This volume gives a comprehensive overview of marketing analytics, incorporating machine learning methods of data analysis that automates analytical model building. The volume covers the important aspects of marketing analytics, including segmentation and targeting analysis, statistics for marketing, marketing metrics, consumer buying behavior, neuromarketing techniques for consumer analytics, new product development, forecasting sales and price, web and social media analytics, and much more.
This well-organized and straight-forward volume will be valuable for marketers, managers, decision makers, and research scholars, and faculty in business marketing and information technology and would also be suitable for classroom use.
Cover Half Title Title Page Copyright Page About the Editors Table of Contents Contributors Abbreviations Introduction Preface 1. Introduction to Marketing Analytics 2. Statistics for Marketing 3. Evolution of Data Analytics 4. Segmentation and Targeting Analysis 5. Important Marketing Metrics: A Snapshot 6. Consumer Buying Behavior 7. Understanding Consumer Behavior Using Market Basket Analysis 8. Neuromarketing Techniques for Consumer Analytics 9. New Product Development 10. Natural Language Processing for Branding 11. Forecasting Sales and Price 12. Sales Prediction and Conversion 13. Role of Supply Chain Analytics in Marketing Analytics 14. Web and Social Media Analytics 15. Marketing Analytics and Its Applications Index
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