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Marketing Analytics: A Machine Learning Approach

Unknown Author
4.9/5 (32717 ratings)
Description: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 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.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Marketing Analytics: A Machine Learning Approach. To get started finding Marketing Analytics: A Machine Learning Approach, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.
Pages
0
Format
PDF, EPUB & Kindle Edition
Publisher
Release
ISBN
1000608891

Marketing Analytics: A Machine Learning Approach

Unknown Author
4.4/5 (1290744 ratings)
Description: 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 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.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Marketing Analytics: A Machine Learning Approach. To get started finding Marketing Analytics: A Machine Learning Approach, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.
Pages
0
Format
PDF, EPUB & Kindle Edition
Publisher
Release
ISBN
1000608891
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