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Effective CRM using Predictive Analytics By Antonios Chorianopoulos
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- Sales Rank: #312357 in eBooks
- Published on: 2015-10-26
- Released on: 2015-10-26
- Format: Kindle eBook
Review
Need to learn how to apply data mining to CRM? Just read "Effective CRM using Predictive Analytics"@DataMiningBlog June 12 2016
From the Back Cover
"Data science should become less scientific and more practical - and this is what this book strives for. It gives marketing experts the necessary background to apply predictive analytics in CRM and improve business outcomes with techniques like cross-selling and customer segmentation."Dr. Ingo Mierswa, Founder & CTO of RapidMiner.
"Effective CRM using Predictive Analytics demonstrates how organizations can become customer centric, while driving profitable revenue. The book is a great introduction to the predictive analytics technology that provides deep customer insight and data driven recommended actions. It is full of practical examples describing a variety of use cases, what data is required and what models are deployed. Inspiration for anybody who pursues customer centricity as a route to success!"
Vivian Braun, WW Predictive Customer Intelligence Marketing Lead, IBM Analytics.
A step-by-step guide to data mining applications in CRM.
Following a handbook approach, this book bridges the gap between analytics and their use in everyday marketing, providing guidance on solving real business problems using data mining techniques.
The book is organized into three parts. Part one provides a methodological roadmap, covering both the business and the technical aspects. The data mining process is presented in detail along with specific guidelines for the development of optimized acquisition, cross/ deep/ up selling and retention campaigns, as well as effective customer segmentation schemes.
In part two, some of the most useful data mining algorithms are explained in a simple and comprehensive way for business users with no technical expertise. Part three is packed with real world case studies which employ the use of three leading data mining tools: IBM SPSS Modeler, RapidMiner and Data Mining for Excel. Case studies from industries including banking, retail and telecommunications are presented in detail so as to serve as templates for developing similar applications.
Key Features:
- Includes numerous real-world case studies which are presented step by step, demystifying the usage of data mining models and clarifying all the methodological issues.
- Topics are presented with the use of three leading data mining tools: IBM SPSS Modeler, RapidMiner and Data Mining for Excel.
- Accompanied by a website featuring material from each case study, including datasets and relevant code.
About the Author
Antonios Chorianopoulos, Alpha Bank Greece.
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