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Predictive Analytics for Marketers: Using Data Mining for Business Advantage


Predictive Analytics for Marketers: Using Data Mining for Business Advantage

Paperback by Leventhal, Barry

Predictive Analytics for Marketers: Using Data Mining for Business Advantage

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£22.94

ISBN:
9780749479930
Publication Date:
3 Feb 2018
Language:
English
Publisher:
Kogan Page Ltd
Pages:
272 pages
Format:
Paperback
For delivery:
Estimated despatch 3 - 5 May 2024
Predictive Analytics for Marketers: Using Data Mining for Business Advantage

Description

Predictive analytics has revolutionized marketing practice. It involves using many techniques from data mining, statistics, modelling, machine learning and artificial intelligence, to analyse current data and make predictions about unknown future events. In business terms, this enables companies to forecast consumer behaviour and much more. Predictive Analytics for Marketers will guide marketing professionals on how to apply predictive analytical tools to streamline business practices. Including comprehensive coverage of an array of predictive analytic tools and techniques, this book enables readers to harness patterns from past data, to make accurate and useful predictions that can be converted to business success. Truly global in its approach, the insights these techniques offer can be used to manage resources more effectively across all industries and sectors. Written in clear, non-technical language, Predictive Analytics for Marketers contains case studies from the author's more than 25 years of experience and articles from guest contributors, demonstrating how predictive analytics can be used to successfully achieve a range of business purposes.

Contents

Section - 00: Introduction to predictive analytics; Section - 01: How can predictive analytics help your business?; Section - 02: Using data mining to build predictive models; Section - 03: Managing the data for predictive analytics; Section - 04: The analytical modelling toolkit; Section - 05: Software solutions for predictive analytics; Section - 06: Predicting customer behaviour using analytical models; Section - 07: Predicting lifetimes - from customers to machines; Section - 08: How to build a customer segmentation; Section - 09: Accounts, baskets, citizens or businesses - applying predictive analytics in various sectors; Section - 10: From people to products - using predictive analytics in retail; Section - 11: How to benefit from social network analysis; Section - 12: Testing the benefits of predictive models and other marketing effects; Section - 13: Top tips for gaining business value from predictive analytics;

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