Data Mining for Managers : How to Use Data (Big and Small) to Solve Business Challenges

Big Data is a growing business trend, but there little advice available on how to use it practically. Written by a data mining expert with over 30 years of experience, this book uses case studies to help marketers, brand managers and IT professionals understand how to capture and measure data for marketing purposes. In today's business and marketing worlds, there's big talk about big data. As companies' capacities to amass information continue to grow and improve, the process of mining the data has become more and more vital. All are abuzz about data mining's importance and potential and for good reason but the field is still in its infancy, and there's an urgent need to spread and grow the skills, know-how, and strategies to best optimize data mining's results. In "Data Mining for Managers", industry-veteran Richard Boire provides streamlined insights and techniques for making the most of the masses of information and mining techniques that technology has enabled. Chock-full of engaging stories and case studies involving some of the world's top companies, "Data Mining for Managers "sets itself apart in more ways than one. A guide for business managers who need to understand the concepts of data mining as well as the potential it has for providing strategic guidance, Boire delivers a uniquely simple, 4-step process for identifying when data mining is the appropriate tool and then designing, implementing, and measuring your mining. Through hands-on analysis of best practices, "Data Mining for Managers" demonstrates how to interpret your results into actionable learning and target your mining to achieve appropriate business solutions solutions that lead directly to optimized customer ROI and other tangible results. Boire also takes pains to outline the common pitfalls of data mining and detail vital approaches for sidestepping them. Among other warnings, he advises managers about the investment in intellectual capital required for effective data mining, urging them against focusing solely on technology and unenlightened, de-contextualized numbers analysis. "Data Mining for Managers" is a book for marketers, IT professionals, analysts, and anyone else who wants to ride the revolution of big data not just get swept along by it. It's an invaluable handbook for those looking to learn more about how to convert data mining into actionable insights and business solutions Front Matter....Pages i-xiii Introduction....Pages 1-6 Growth of Data Mining—An Historical Perspective....Pages 7-14 Data Mining in the New Economy....Pages 15-21 Using Data Mining for CRM Evaluation....Pages 23-27 The Data Mining Process: Problem Identification....Pages 29-40 The Data Mining Process: Creation of the Analytical File....Pages 41-57 Data Mining Process: Creation of the Analytical File with External Data Sources....Pages 59-62 Data Storage and Security....Pages 63-64 Privacy Concerns Regarding the Use of Data....Pages 65-73 Types and Quality of Data....Pages 75-82 Segmentation....Pages 83-94 Applying Data Mining Techniques....Pages 95-113 Gains Charts....Pages 115-120 Using RFM as One Targeting Option....Pages 121-123 The Use of Multivariate Analysis Techniques....Pages 125-132 Tracking and Measuring....Pages 133-140 Implementation and Tracking....Pages 141-142 Value-Based Segmentation and the Use of CHAID....Pages 143-149 Black Box Analytics....Pages 151-154 Digital Analytics: A Data Miner’s Perspective....Pages 155-163 Organizational Considerations: People and Software....Pages 165-180 Social Media Analytics....Pages 181-184 Credit Cards and Risk....Pages 185-191 Data Mining in Retail....Pages 193-200 Business-to-Business Example....Pages 201-205 Financial Institution Case Study....Pages 207-210 Using Marketing Analytics in the Travel/Entertainment Industry....Pages 211-213 Data Mining for Customer Loyalty: A Perspective....Pages 215-219 Text Mining: The New Data Mining Frontier....Pages 221-227 Analytics and Data Mining for Insurance Claim Risk....Pages 229-230 Future Thoughts: The Big Data Discussion and the Key Roles in Analytics....Pages 231-236 Back Matter....Pages 237-242 Cover -- Data Mining for Managers -- Contents -- List of Figures -- Foreword -- Acknowledgments -- Chapter 1 Introduction -- Chapter 2 Growth of Data Mining-An Historical Perspective -- Chapter 3 Data Mining in the New Economy -- Chapter 4 Using Data Mining for CRM Evaluation -- Chapter 5 The Data Mining Process: Problem Identification -- Chapter 6 The Data Mining Process: Creation of the Analytical File -- Chapter 7 Data Mining Process: Creation of the Analytical File with External Data Sources -- Chapter 8 Data Storage and Security -- Chapter 9 Privacy Concerns Regarding the Use of Data -- Chapter 10 Types and Quality of Data -- Chapter 11 Segmentation -- Chapter 12 Applying Data Mining Techniques -- Chapter 13 Gains Charts -- Chapter 14 Using RFM as One Targeting Option -- Chapter 15 The Use of Multivariate Analysis Techniques -- Chapter 16 Tracking and Measuring -- Chapter 17 Implementation and Tracking -- Chapter 18 Value-Based Segmentation and the Use of CHAID -- Chapter 19 Black Box Analytics -- Chapter 20 Digital Analytics: A Data Miner's Perspective -- Chapter 21 Organizational Considerations: People and Software -- Chapter 22 Social Media Analytics -- Chapter 23 Credit Cards and Risk -- Chapter 24 Data Mining in Retail -- Chapter 25 Business-to-Business Example -- Chapter 26 Financial Institution Case Study -- Chapter 27 Using Marketing Analytics in the Travel/Entertainment Industry -- Chapter 28 Data Mining for Customer Loyalty: A Perspective -- Chapter 29 Text Mining: The New Data Mining Frontier -- Chapter 30 Analytics and Data Mining for Insurance Claim Risk -- Chapter 31 Future Thoughts: The Big Data Discussion and the Key Roles in Analytics -- Index