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customer data management
CIO Best Practices in Customer Data Management
of clear business objectives relating to customer data management. Too often, the ... direction for customer data management and analytics projects. Stated one ...
Master Data Management for Customer and Client Data
profitable customers from less profitable ones, and an overall loss in brand value. Master data management (MDM) for customer data allows companies ...
CUSTOMER MASTER DATA MANAGEMENT PROCESS ...
PIP) is a collection of core processes to support out of the box Customer Master. Data Management (MDM) integration processes across Oracle Customer Hub ...
ORACLE CUSTOMER HUB
by T MASTER
Magic Quadrant for Master Data Management of Customer Data
Master Data Management of Customer Data. Gartner RAS Core Research Note G00167733, John Radcliffe, 16 June 2009, R3097 12172009. IBM and Oracle ...
Client Data Management
Client Data Management. Overview Managing Customer Contact Data. In recent years, an emerging shift has been occurring within property and casualty (P&C) ...
PayLeap Recurring Billing and Subscription Customer Data ...
PayLeap Recurring Billing and Subscription Customer Data Management API | PRODUCT BROCHURE. 877- 4 PAYLEAP ( 877-472-9532 ) email@example.com ...
Vendor Landscape Customer Data Management - Hypatia Research
Selection of a customer data management solution will vary according to industry, ... Selecting the Right Approach Effective management of customer data is a ...
Customer Data Management System Improves Service to BIG ...
Resource Efficiency Helps. Businesses Become Sustainable. OWRD Workshop. October 25, 2001. Bend, Oregon. Teri Liberator. Senior. Engineering Associate ...
The Data Standards Approach to Master Data Management
subsequent shared use of “master data”. ∎ Customers. ∎ Products. ∎ Vendors. ∎ Documents. ∎ Contact mechanisms. ∎ Management information ...
Introduction to Master Data Management
Manage both transactional and analytic master data. / MDM products now brought together into Oracle Master Data Management Suite. ‣ Customer Data Hub ...
Infosys - Master data Management| Retail
Master Data Management - enabling Customer Data Integration (CDI). “How your ... the ability to manage customer master data as a strategic asset. Disjointed ...
IBM DB2 Spatial Extender and Geodetic Data Management Feature ...
Spatial Extender and Geodetic Data Management Feature. User's Guide and Reference. Version 9. Linux, UNIX, and Windows. SC18-9749-00 ...
Nokia Siemens Networks Subscriber Data Management
By separating application logic from the subscriber data, Subscriber Data Management liberates and unifies customer data that is currently locked away in ...
Data Management in Telecoms - from asset to revenue
to Revenue. By discussing three areas of data management. – data consolidation and optimization, Customer. Experience Management and new business ...
Microsoft SQL Server Master Data Services FAQs
product, customer, location, cost center, equipment, employee, and vendor. Using MDS, customers can manage critical data assets by enabling proactive ...
Master Data Management and Governance
Definition – What is Master Data Management? Definitions. Master Data. ∎ Is the key entity to defining core business entities such as customer, employee, ...
iPad at Work Customer Relationship Management
immediate access to your company's customer relationship management (CRM) data—whether you're onsite at a customer meeting, in the office, or on the road.
2011 European Industry Survey on the Current State of Customer Data
White Paper. 2. A White Paper on European. Trends & Challenges in Customer. Data Management Within the Life. Sciences Industry ...
11.0 CRM Data Strategies The Critical Role of Quality Customer ...
of two containers that were bigger than the customer recipient's entire warehouse. Many executives find the subject of data management to be boring or ...
Transform your business into a customer-centric enterprise
Gain a complete and timely understanding of your customers using MDM-CDI and the real-world information contained in this comprehensive volume. Master Data Management and Customer Data Integration for a Global Enterprise explains how to grow revenue, reduce administrative costs, and improve client retention by adopting a customer-focused business framework.
Learn to build and use customer hubs and associated technologies, secure and protect confidential corporate and customer information, provide personalized services, and set up an effective data governance team. You'll also get full details on regulatory compliance and the latest pre-packaged MDM-CDI software solutions.
The leading introductory book on data mining, fully updated and revised!
When Berry and Linoff wrote the first edition of Data Mining Techniques in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new edition—more than 50% new and revised— is a significant update from the previous one, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company.
Data Mining Techniques, Third Edition covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results.
"Berry and Linoff lead the reader down an enlightened path of best practices." -Dr. Jim Goodnight, President and Cofounder, SAS Institute Inc.
"This is a great book, and it will be in my stack of four or five essential resources for my professional work." -Ralph Kimball, Author of The Data Warehouse Lifecycle Toolkit
Mastering Data Mining
In this follow-up to their successful first book, Data Mining Techniques, Michael J. A. Berry and Gordon S. Linoff offer a case study-based guide to best practices in commercial data mining. Their first book acquainted you with the new generation of data mining tools and techniques and showed you how to use them to make better business decisions. Mastering Data Mining shifts the focus from understanding data mining techniques to achieving business results, placing particular emphasis on customer relationship management.
In this book, you'll learn how to apply data mining techniques to solve practical business problems. After providing the fundamental principles of data mining and customer relationship management, Berry and Linoff share the lessons they have learned through a series of warts-and-all case studies drawn from their experience in a variety of industries, including e-commerce, banking, cataloging, retailing, and telecommunications.
Through the cases, you will learn how to formulate the business problem, analyze the data, evaluate the results, and utilize this information for similar business problems in different industries.
Berry and Linoff show you how to use data mining to:Retain customer loyaltyTarget the right prospectsIdentify new markets for products and servicesRecognize cross-selling opportunities on and off the Web
The companion Web site at http://www.data-miners.com features:Updated information on data mining products and service providersInformation on data mining conferences, courses, and other sources of informationFull-color versions of the illustrations used in the book.
A complete and comprehensive handbook for the application of data mining techniques in marketing and customer relationship management. It combines a technical and a business perspective, bridging the gap between data mining and its use in marketing.
It guides readers through all the phases of the data mining process, presenting a solid data mining methodology, data mining best practices and recommendations for the use of the data mining results for effective marketing. It answers the crucial question of 'what data to use' by proposing mining data marts and full lists of KPIs for all major industries.Data mining algorithms are presented in a simple and comprehensive way for the business users along with real-world application examples from all major industries.
The book is mainly addressed to marketers, business analysts and data mining practitioners who are looking for a how-to guide on data mining. It presents the authors' knowledge and experience from the "data mining trenches", revealing the secrets for data mining success.
"Customers are the heart of any business. But we can't succeed if we develop only one talk addressed to the 'average customer.' Instead we must know each customer and build our individual engagements with that knowledge. If Customer Relationship Management (CRM) is going to work, it calls for skills in Customer Data Integration (CDI). This is the best book that I have seen on the subject. Jill Dych? is to be complimented for her thoroughness in interviewing executives and presenting CDI."
-Philip Kotler, S. C. Johnson
Distinguished Professor of International Marketing Kellogg School of Management, Northwestern University
"In this world of killer competition, hanging on to existing customers is critical to survival. Jill Dych?'s new book makes that job a lot easier than it has been."
-Jack Trout, author, Differentiate or Die
"Jill and Evan have not only written the definitive work on Customer Data Integration, they've made the business case for it. This book offers sound advice to business people in search of innovative ways to bring data together about customers-their most important asset-while at the same time giving IT some practical tips for implementing CDI and MDM the right way."
-Wayne Eckerson, The Data Warehousing Institute author of Performance Dashboards: Measuring, Monitoring, and Managing Your Business
Whatever business you're in, you're ultimately in the customer business. No matter what your product, customers pay the bills. But the strategic importance of customer relationships hasn't brought companies much closer to a single, authoritative view of their customers. Written from both business and technicalperspectives, Customer Data Integration shows companies how to deliver an accurate, holistic, and long-term understanding of their customers through CDI.
In this book, authors Dalton Cervo and Mark Allen show you how to implement Master Data Management (MDM) within your business model to create a more quality controlled approach. Focusing on techniques that can improve data quality management, lower data maintenance costs, reduce corporate and compliance risks, and drive increased efficiency in customer data management practices, the book will guide you in successfully managing and maintaining your customer master data. You'll find the expert guidance you need, complete with tables, graphs, and charts, in planning, implementing, and managing MDM.
Practical and informal, this manual clearly defines Master Data Management (MDM), a set of processes and tools that consistently define and manage the nontransactional data entities of an organization. Demonstrating how to implement MDM and how to make it complement other IT solutions, this handbook proves that MDM is a fascinating and up-and-coming approach that allows organizations to run customer-centric business operations. With chapters on data governance, MDM data domains, and customer-data case studies, this reference will appeal to programmers, chief information officers, and information technology architects and managers.
NAMED BEST MARKETING BOOK OF 2011 BY THE AMERICAN MARKETING ASSOCIATION
How organizations can deliver significant performance gains through strategic investment in marketing
In the new era of tight marketing budgets, no organization can continue to spend on marketing without knowing what's working and what's wasted. Data-driven marketing improves efficiency and effectiveness of marketing expenditures across the spectrum of marketing activities from branding and awareness, trail and loyalty, to new product launch and Internet marketing. Based on new research from the Kellogg School of Management, this book is a clear and convincing guide to using a more rigorous, data-driven strategic approach to deliver significant performance gains from your marketing.
With every department under the microscope looking for results, those who properly use data to optimize their marketing are going to come out on top every time.
The latest techniques for building a customer-focused enterprise environment
"The authors have appreciated that MDM is a complex multidimensional area, and have set out to cover each of these dimensions in sufficient detail to provide adequate practical guidance to anyone implementing MDM. While this necessarily makes the book rather long, it means that the authors achieve a comprehensive treatment of MDM that is lacking in previous works." -- Malcolm Chisholm, Ph.D., President, AskGet.com Consulting, Inc.
Regain control of your master data and maintain a master-entity-centric enterprise data framework using the detailed information in this authoritative guide. Master Data Management and Data Governance, Second Edition provides up-to-date coverage of the most current architecture and technology views and system development and management methods. Discover how to construct an MDM business case and roadmap, build accurate models, deploy data hubs, and implement layered security policies. Legacy system integration, cross-industry challenges, and regulatory compliance are also covered in this comprehensive volume.
Increase profits and reduce costs by utilizing this collection of models of the most commonly asked data mining questions
In order to find new ways to improve customer sales and support, and as well as manage risk, business managers must be able to mine company databases. This book provides a step-by-step guide to creating and implementing models of the most commonly asked data mining questions. Readers will learn how to prepare data to mine, and develop accurate data mining questions. The author, who has over ten years of data mining experience, also provides actual tested models of specific data mining questions for marketing, sales, customer service and retention, and risk management. A CD-ROM, sold separately, provides these models for reader use.