2 When I first read Nathaniel Lin s Applied Business Analytics, I thought, I wish I had written this. The points Nathaniel makes about analytics deciders hit a unique target managers who today don t realize what it takes to drive business using data. Having analytics deciders engaged at the intersections makes it possible for innovation to flow throughout the organization, like traffic cops in downtown Manhattan. This is one of those books that you keep on your desk and refer to as you build an analytics team. Here are all the things I loved about this book: the Advanced Analytics Layer (it has immediate applicability); the case studies (which are practical); and the hands-on approach with KNIME (the real-world experience). Theresa Kushner, Vice President Enterprise Information Management, VMware and former Sr. Director of Customer Intelligence, Cisco Nathaniel has done a terrific job of capturing the key components needed to build high-performing analytics to drive business growth. This is a must read for senior executives involved in analytics for decision-making. John F Carter, Senior Vice President, Analytics, Insight & Loyalty, Charles Schwab Making analytics mainstream: There are scores of books on the application of analytics to organizations, however, Applied Business Analytics is unique in two respects. First, it identifies why organizations fail to truly leverage analytics to achieve transformational outcomes. Second, it proposes a framework in which business processes are modified to accommodate analytics through a continuous dialogue, rather than isolated analytical experiments. Forward-looking business leaders who want to truly leverage Big Data and analytics to transform and lead their organizations would do well to take to heart the core message of this book. Prat Moghe, CEO of Cazena and former Senior Vice President of IBM Netezza Business analytics has developed into an area of intense focus for many organizations, yet its successful application remains more art than science. Nathaniel Lin s Applied Business Analytics represents a significant step forward in remedying that situation by enabling business leaders to create the teams and business processes required to succeed with analytics. Business analytics is by its nature a deeply technical topic, and Dr. Lin does not skimp on the technical details, including meaty yet approachable hands-on exercises. Applied Business Analytics keeps the technical discussion where it belongs: in clear service of wellarticulated and relevant business problems that provide the necessary context for analytics projects to create meaningful value. No mere how-to guide, Dr. Lin s book provides a complete picture of the analytical organization, as well as the conditions and processes required to develop and enable analytics deciders, the data-driven
3 change agents who propel organizations to move from gut-based decision making to rational, evidence based decision making. Packed with numerous real-world case studies and war stories, Nathaniel Lin s Applied Business Analytics is a solid starting point for any executive seeking to transform an organization with analytics. Adam Ferrari, CTO Crisply and Strategic Advisor Big Data and Vice President of Product Development, Oracle, Former CTO, Endeca Technologies Leaders who are establishing a data-driven culture will benefit from the lucid analytical process and methodologies that Nathaniel demonstrates in Applied Business Analytics. The chapter about Analytics Eco-system includes a fantastic comparison of different team structures that exist today. Jane Chen, Head of Analytics Center of Excellence, Analog Devices I am positively impressed by Nathaniel s book. This book has a unique position in the marketplace, standing out as an insightful perspective balancing an evangelist book and technical how-to cookbook. I appreciate Nathaniel s thought leadership and guidance. Applied Business Analytics is 70% business and technical context discussion and 30% of how to be effective in organizational framework. The most challenging part of analytics leaders in today s world is still the conflict or tension between business drivers and technical details. That is why analytics deciders are critical for maximizing analytics functional impact on businesses. Balancing technical details (how) with why analytics is critical to your success and what result you can (expect to) achieve by building analytics capabilities is challenging. Nathaniel s personal stories, case studies, and real-world success are helpful. I believe this book can be a great reference guide for emerging analytics leaders. G ary Cao, Vice President, Information Services & Analytics Strategy, Cardinal Health, Inc.
4 Applied Business Analytics
5 This page intentionally left blank
6 Applied Business Analytics Integrating Business Process, Big Data, and Advanced Analytics Nathaniel Lin
7 Editor-in-Chief: Amy Neidlinger Executive Editor: Jeanne Glasser Levine Operations Specialist: Jodi Kemper Cover Designer: Chuti Prasertsith Managing Editor: Kristy Hart Project Editor: Deadline Driven Publishing Copy Editor: Nancy Sixsmith Proofreader: Deadline Driven Publishing Indexer: Angie Martin Compositor: Jake McFarland Manufacturing Buyer: Dan Uhrig 2015 by Nathaniel Lin Upper Saddle River, New Jersey For information about buying this title in bulk quantities, or for special sales opportunities (which may include electronic versions; custom cover designs; and content particular to your business, training goals, marketing focus, or branding interests), please contact our corporate sales department at or (800) For government sales inquiries, please contact For questions about sales outside the U.S., please contact Company and product names mentioned herein are the trademarks or registered trademarks of their respective owners. All rights reserved. No part of this book may be reproduced, in any form or by any means, without permission in writing from the publisher. Printed in the United States of America First Printing December ISBN-10: ISBN-13: Pearson Education LTD. Pearson Education Australia PTY, Limited. Pearson Education Singapore, Pte. Ltd. Pearson Education Asia, Ltd. Pearson Education Canada, Ltd. Pearson Educación de Mexico, S.A. de C.V. Pearson Education Japan Pearson Education Malaysia, Pte. Ltd. Library of Congress Control Number:
8 To my parents Tah-Fu and Paw-Chu Lin, who have spent years encouraging me to do something special. Even though this book is nothing special, it is a token of my appreciation for their love and nurturing since they brought me into the world 60 years ago. Last, to the one who really matters, I would use the same dedication from my PhD thesis: Jehovah, who stretches forth the heavens and lays the foundations of the earth and forms the spirit of man within him. Zechariah 12:1
9 This page intentionally left blank
10 Contents Foreword xv Acknowledgments xviii About the Author xix Preface xxi Why Another Book on Analytics? xxi How This Book Is Organized xxii After Reading and Working Through This Book xxvi Chapter 1 Introduction Raw Data, the New Oil Data Big and Small Is Not New Definition of Analytics Top 10 Business Questions for Analytics Financial Management Customer Management HR Management Internal Operations Vital Lessons Learned Use Analytics Reasons Why Analytics Are Not Used Linking Analytics to Business Business Analytics Value Chain Integrated Approach Hands-on Exercises Reasons for Using KNIME Workflows Conclusion Chapter 2 Know Your Ingredients Data Big and Small Garbage in, Garbage out Data or Big Data Definition of Big Data Data Types Company Data Individual Customer Data
11 X APPLIED BUSINESS ANALYTICS Sensor Data Syndicated Data Data Formats Structured, Poorly Structured, and Unstructured Data Conclusion Chapter 3 Data Management Integration, Data Quality, and Governance Data Integration Data Quality Data Security and Data Privacy Data Security Data Privacy Data Governance Data Preparation Data Manipulation Types of Data Categorize Numerical Variables Dummy Variables Missing Values Data Normalization Data Partitions Exploratory Data Analysis Multidimensional Cube Slicing Dicing Drilling Down/Up Pivoting Visualization of Data Patterns and Trends Popularity of BI Visualization Selecting a BI Visualization Tool Beyond BI Visualizations Conclusion Chapter 4 Handle the Tools: Analytics Methodology and Tools Getting Familiar with the Tools Master Chefs Who Can t Cook Types of Analytics
12 CONTENTS xi Descriptive and Diagnostic Tools: BI Visualization and Reporting Advanced Analytics Tools: Prediction, Optimization, and Knowledge Discovery A Unified View of BI Analysis, Advanced Analytics, and Visualization Two Ways of Knowledge Discovery Types of Advanced Analytics and Applications Analytics Modeling Tools by Functions Modeling Likelihood Modeling Groupings Supervised Learning Value Prediction Other Models Conclusion Chapter 5 Chapter 6 Analytics Decision-Making Process and the Analytics Deciders Time to Take Off the Mittens Overview of the Business Analytics Process (BAP) Analytics Rapid Prototyping Analytics Sandbox for Instant Business Insights Analytics IT Sandbox Database People and the Decision Blinders Risks of Crossing the Chasms The Medici Effect Analytics Deciders How to Find Analytics Deciders Becoming an Analytics Decider Conclusion Business Processes and Analytics (by Alejandro Simkievich) Overview of Process Families Enterprise Resource Planning Customer Relationship Management Product Lifecycle Management Shortcomings of Operational Systems
13 XII APPLIED BUSINESS ANALYTICS Embedding Advanced Analytics into Operational Systems Example 1: Forecast Example 2: Improving Salesforce Decisions Example 3: Engineers Get Instant Feedback on Their Design Choices Conclusion Chapter 7 Identifying Business Opportunities by Recognizing Patterns Patterns of Group Behavior Importance of Pattern Recognition in Business Group Patterns by Clustering and Decision Trees Three Ways of Grouping Recognize Purchase Patterns: Association Analysis Association Rules Business Case Patterns over Time: Time Series Predictions Time Series Models Conclusion Chapter 8 Knowing the Unknowable Unknowable Events Unknowable in Business Poor or Inadequate Data Data with Limited Views Business Case Predicting Individual Customer Behaviors in Real-Time Lever Settings and Causality in Business Start with a High Baseline Causality with Control Groups Conclusion Chapter 9 Demonstration of Business Analytics Workflows: Analytics Enterprise A Case for Illustration Top Questions for Analytics Applications
14 CONTENTS xiii Financial Management Human Resources Internal Operations Conclusion Chapter 10 Demonstration of Business Analytics Workflows Analytics CRM Questions About Customers Know the Customers Actionable Customer Insights Social and Mobile CRM Issues CRM Knowledge Management Conclusion Chapter 11 Analytics Competencies and Ecosystem Analytics Maturity Levels Analytics Organizational Structure The Centralized Model The Consulting Model The Decentralized Model The Center of Excellence Model Reporting Structures Roles and Responsibilities Analytics Roles Business Strategy and Leadership Roles Data and Quantitative Roles Analytics Ecosystem The In-House IT Function External Analytics Advisory and Consulting Resources Analytics Talent Management Conclusion Chapter 12 Conclusions and Now What? Analytics Is Not a Fad Acquire Rich and Effective Data Start with EDA and BI Analysis Gain Firsthand Analytics Experience Become an Analytics Decider and Recruit Others
15 XIV APPLIED BUSINESS ANALYTICS Empower Enterprise Business Processes with Analytics Recognize Patterns with Analytics Know the Unknowable Imbue Business Processes with Analytics Acquire Competencies and Establish Ecosystem Epilogue Appendix A KNIME Basics Data Preparation Types of Variable Values Dummy Variables Missing Values Data Partitions Exploratory Data Analysis (EDA) Multi-Dimensional Cube Slicing Dicing Drilling Down or Up Pivoting Index
16 Foreword This book is well-timed for the current business analytics zeitgeist the spirit of the times in a variety of ways. Analytics and big data have become accepted tools for business strategy and competition. In surveys, virtually every manager agrees that they are important resources for business. If you are not a believer in data and analytics as guides to decision making, it is becoming embarrassing or politically incorrect to say so. This is all good news, at least from my perspective. The only problem with this broad-scale consensus is that many managers and organizations still lack the skills and understanding to make analytics work for them. Lin s book is directed at just this issue. As he says, there have been a variety of books that attempt to get managers excited about analytics and textbooks that delve into the details of analytics without much sense of the business context. This book is a bridge between those extremes. It s for managers who already believe that analytics are important, but who don t yet know enough to practice them personally. This transition is important and, indeed, necessary. In sophisticated companies, it is becoming difficult to draw the line anymore between analytics and the way work is done. Business is analytics, analytics is business. This book is designed to enable regular business people to create and consume analytics, even advanced ones. The detailed modeling and analysis of data may continue to be left up to professional quants, but the framing, interpreting, and communicating of the analytical work will be a highly collaborative effort among deciders, as Lin puts it, and quantitative experts. Another way in which the book fits with the contemporary analytical mood is its focus on business and analytical processes. Lin correctly points out that analytics are increasingly being embedded within key business processes. In that sense, they are becoming
17 XVI APPLIED BUSINESS ANALYTICS somewhat invisible; as I write today, in fact, Gartner named advanced, pervasive, and invisible analytics as one of the Top 10 Strategic Technology Trends for This invisibility makes the importance of management understanding even greater; if your business is heavily dependent on analytics in the underlying technology and process infrastructure, someone needs to constantly ask intelligent questions about underlying assumptions, methods, and outcomes. To continue the process orientation, many of the topics and insights in this book are structured in terms of an analytics process that ranges from data preparation to data analysis and interpretation. The idea of a process fits the current analytics environment well. For too long, analytics have been pursued as a slow, one-off, painstaking process that would be difficult to institutionalize. Today, however, many companies are beginning to create analytical factories that emphasize speed, scale, and repeatability. The means to do this is to view analytics as a process with clear steps, handoffs, and modules. That is the focus in the book, and it s buttressed by examples using the open source analytics tool KNIME, which is itself structured in terms of processes. If we adopt Lin s model of thinking about analytics in process terms, our analytics will have higher productivity and impact. A final linkage between this book and the current set of analytics themes is the focus on both big data and small. Most current books are on traditional, small data analytics or big data, but few cross that chasm to address both. Lin moves comfortably between analytics on traditional data (for example, marketing propensity models) and such big data types as social media and text from online product reviews. It s clear to me that before long, we won t use the term big data, but we will certainly want to deal with unstructured, large-volume data. In any case, you ll be well-prepared for a world that integrates and analyzes all types of data if you read this book. Lin helpfully supplies a list of likely data elements that an organization might employ for typical analyses in different business areas.
18 FOREWORD xvii This book is not only up-to-the-moment, but extremely comprehensive. There is scarcely an area of business analytics that is not discussed. You may want to read it quickly when you acquire it, and then use it as a reference book as you encounter a variety of analytics situations over the next several years. The ideas are both classical and contemporary, and they won t go out of fashion or relevance for a long time. Thomas H. Davenport, Distinguished Professor, Babson College Author of Competing on Analytics and Big Work
19 Acknowledgments I would like to thank the following people: My wife, Lu, for her confidence and encouragement. Alejandro Simkievich, a good friend and fellow Sloanie, who wrote Chapter 6. Any errors or omissions are solely mine. I want to thank also FT Times, and Victor for reading the draft and providing valuable suggestions.
20 About the Author Dr. Nathaniel Lin is a recognized leader in marketing and business analytics across various industries worldwide. He has over 20 years of frontline experience applying actionable advanced analytics strategies to the world s largest companies in technology, finance, automotive, telecommunications, retail, and across many other businesses, including IBM, Fidelity Investments, OgilvyOne, and Aspen Marketing Analytics. Nathaniel is currently the Chief Customer Insights Officer of Attract China. He is leading the efforts to develop leading edge Big Data Analytics technology and knowledge assets to deliver unparalleled values to Chinese travelers and U.S. clients. Nathaniel is widely recognized as an expert, teacher, author, and hands-on leader and senior executive in the application of data and advanced analytics in a wide variety of businesses. He is also the Founder and President of Analytics Consult, LLC (www.analyticsconsult.com). He leverages his rich and unique expertise in business analytics to help companies optimize their customer, marketing, and sales strategies. Together with his team, Nathaniel serves as a trusted strategic advisor to senior management teams. He is frequently invited as the keynote speaker in analytics events and advised over 150 CEOs in the U.S. and aboard on analytics and Big Data issues. He was invited by WWW2010 as one of the four expert panelists (together with the heads of Google Analytics, ebay Analytics, and Web Analytics Association) on the Future of Predictive Analytics.
21 XX APPLIED BUSINESS ANALYTICS As a recognized analytics expert, Nathaniel has partnered with Professor Tom Davenport to benchmark analytics competencies of major corporations across different industries. He also demonstrates his passion in cultivating future analytics leaders by teaching Strategic CRM and Advanced Business Analytics for MBA students at the Georgia Tech College of Management, Boston College Carroll School of Management, and Quant III Advanced Business Analytics at Bentley University. Nathaniel holds a PhD in Engineering from Birmingham University (UK) and an MBA from MIT Sloan School of Management.
22 Preface I have to admit that this book turned out to be much harder to write than I had envisioned. Having spent decades applying analytics and building and leading analytics teams, I thought it would be simply a summary of what I had learned and done before. Unf ortunately, I find myself constantly struggling to find the Goldilocks approach am I covering too much technical detail or too little? The latter, in my opinion, is worse because the lack of details might prevent business readers from doing the hands-on analytics exercises. However, the former with too many technical details would likely discourage business readers from reading the book altogether! After several rounds of revisions, I hope I have managed to strike a balance to ensure the original objective of writing an analytics hands-on book for business readers has been met. However, in the event you find the content either too technical or not sufficiently technical, I beg for your indulgence. My advice is that you simply skip over the offending sections and go onto the next section. I am sure there are enough examples and business cases in this book that any serious business reader aspiring to be analytical would find relevant and helpful. Why Another Book on Analytics? Despite the many titles on analytics, a quick survey reveals that most broadly fall into two categories. One group focuses on promoting xxi
23 xxii APPLIED BUSINESS ANALYTICS how businesses benefit from analytics. These are usually written by evangelists promoting the virtues of analytics. At the opposite end are those books written by quants for other analytics quants. These contain too much technical detail for business readers. Few books are written to bridge the gap. There is a need for a book with hands-on applications of business analytics that solve real business problems that business readers can understand, practice, and use. I often hear the laments of business leaders: I am sold after reading books promoting the power of analytics, but none can show me how it is done and how to actually apply it in my business without requiring me to go back to school and getting an advanced degrees in analytics and statistics! If you share the same sentiments, then this book is for you. How This Book Is Organized Before getting your hands dirty with hands-on exercises, this book devotes the first four chapters to the basics, that is, the data, analytics tools (from simple to leading edge), and their relationships to the various business processes. The book continues with how to embed analytics and integrate the findings in existing or new strategic processes. With this in mind, the chapters are organized as follows: Chapter 1, Introduction, is an introduction to analytics. It shows how analytics as the refining of data will transform business the way refining of oil transformed the twentieth century. It also addresses definitions, potential areas of applications, some vital lessons learned, how analytics are positioned in the business context, and how analytics are integrated into the business process. Chapter 2, Know Your Ingredients Data Big and Small, discusses everything you need to know about the basic ingredients of successful business analytics. It defines the differences between Big Data and the various types of data that may be
24 PREFACE xxiii useful to business analytics. It also describes data formats and the increasing importance of poorly or unstructured data to business insights and how to handle them. Chapter 3, Data Management Integration, Data Quality, and Governance, provides everything you need to manage and analyze data, from processing diverse data, to the importance of governance on data security and privacy, to good data versus bad data, to quality and latency, and to where to go beyond internal data sources. Chapter 4, Handle the Tools: Analytics Methodology and Tools, discusses the most commonly used analytics models and tools, and provides hands-on exercises for some of the most commonly used analytics modeling techniques so you can see and feel how they work within real business cases. Its coverage spans basic models such as regressions, clustering, decision trees to the more sophisticated Big Data analytics such as text mining, and sentiment analysis on real data including online reviews on Amazon Fine Food and TripAdvisor hotels. A value prediction methodology using Ensemble Regression Tree model is also presented. Chapter 5, Analytics Decision-Making Process and the Analytics Deciders, elucidates the differences between the conventional and the analytics decisioning process. It starts by exploring how conventional decision processes often falls short. It also describes the analytics decisioning process, known in this book as the BAP (Business Analytics Process), and how the right analytics deciders are needed to work in the intersection between silos to ensure the BAP s success. It ends with notes on how to become, identify, recruit, and retain analytics deciders. Chapter 6, Business Processes and Analytics, discusses the business processes that can benefit from analytics. It also covers
25 xxiv APPLIED BUSINESS ANALYTICS today s ERP (Enterprise Resource Planning) that is fueled by analytics. It includes CRM (Customer Relationship Management), SCM (Supply Chain Management), Financial Management, PLM (Product Cycle Management), and Human Capital Management. Chapter 7, Identifying Business Opportunities by Recognizing Patterns, explains why the current way of dividing customers into segments just won t cut it. It tells you how to leverage advanced analytics tools to detect patterns of behaviors, events, trends, topics, preferences, and other critical factors that can impact business. Finally, it discusses pattern detection and how the group behavior of customers may help marketers plan more effective engagements using insights from the Market Basket Analysis and customer segment persona discovered using analytics. Chapter 8, Knowing the Unknowable, discusses those topics and questions that are often deemed unknowable or unique (UU). These may involve little or limited data, predicting individual behavior in real time, and determining causality and lever settings for complex situations. This chapter provides real-life business cases and actual analytics workflows to illustrate how enlightened businesses can know and leverage analytics in these apparent unknowable events, thus, gaining a competitive edge over the competition. A novel methodology is also described to predict customer wallets and how to use that to form effective strategies. Chapter 9, Demonstration of Business Analytics Workflows Analytics Enterprise, uses the proper ingredients and tools to answer the top business questions except CRM (Customer Relationship Management), which is discussed in Chapter 10. You are encouraged to download and modify the workflows so that you can try to run them and adapt them to your own needs.
THE HR GUIDE TO IDENTIFYING HIGH-POTENTIALS What makes a high-potential? Quite possibly not what you think. The HR Guide to Identifying High-Potentials 1 Chapter 1 - Introduction If you agree people are
OPTIMUS SBR CHOICE TOOLS. PRECISION AIM. BOLD ATTITUDE. Optimizing Results with Business Intelligence Governance This paper investigates the importance of establishing a robust Business Intelligence (BI)
Books in the FT Press Project Management Series Mastering Project, Program, and Portfolio Management: Models for Structuring and Executing the Project Hierarchy Lister (ISBN: 0133839745) Mastering Principles
3 7 Pillars for Successful Analytics Implementation 3 3 3 34 + A leader s guide to incorporating Big Data across the organization Jesse Harriott firstname.lastname@example.org You may remember the days before
Using Predictive Analytics to Increase Profitability Part II Jay Roy Chief Strategy Officer Practical Intelligence for Ensuring Profitability Fall 2011 Dallas, TX Table of Contents A Brief Review of Part
Location Analytics for Financial Services An Esri White Paper October 2013 Copyright 2013 Esri All rights reserved. Printed in the United States of America. The information contained in this document is
Ventana Research: Predictive Analytics Enters the Mainstream Predictive Analytics Enters the Mainstream Taking Advantage of Trends to Gain Competitive Advantage White Paper Sponsored by 1 Ventana Research
ROI of Customer, 2014 CX Highly Correlates to Loyalty Across 19 Industries, Delivers Up To $460M Over 3 Years By Bruce Customer Transformist & Managing Partner Group September 2014 Group email@example.com
IBM Software Business Analytics Customer Analytics Achieving customer loyalty with customer analytics 2 Achieving customer loyalty with customer analytics Contents 2 Overview 3 Using satisfaction to drive
What If Customer Experience Has No ROI? By Bruce Temkin Customer Experience Transformist & Managing Partner Temkin Group www.temkingroup.com I m often asked the question: What s the ROI of customer experience?
IBM Software Business Analytics Social Analytics Social Business Analytics Gaining business value from social media 2 Social Business Analytics Contents 2 Overview 3 Analytics as a competitive advantage
White Paper Series Developing a Business Analytics Roadmap A Guide to Assessing Your Organization and Building a Roadmap to Analytics Success March 2013 A Guide to Assessing Your Organization and Building
Harnessing Big Data to Improve Customer Service By Marty Tibbitts The goal is to apply analytics methods that move beyond customer satisfaction to nurturing customer loyalty by more deeply understanding
Managing the Next Best Activity Decision James Taylor CEO, Decision Management Solutions Treating customers right, every time More information at: www.decisionmanagementsolutions.com No matter what the
WHITE PAPER The 7 Deadly Sins of Dashboard Design Overview In the new world of business intelligence (BI), the front end of an executive management platform, or dashboard, is one of several critical elements
Customer Experience Management Best Practices for Voice of the Customer (VoC) Programmes Jörg Höhner Senior Vice President Global Head of Automotive SPA Future Thinking The Evolution of Customer Satisfaction
THE STATE OF Customer Analytics Taking A Proactive Approach To Loyalty & Retention By Kerry Doyle An Exclusive Research Report UBM TechWeb research conducted an online study of 339 marketing professionals
The Art & Science of Buyer Personas What is a buyer persona? is a question we often field at D Custom. Buyer persona development is shaping the future of content marketing today. However, many CMOs and
Research Brief Elevating Customer Analytics Initiatives and Building the Coveted Holistic Customer View November 2014 Written By: Christy Maver, Actian Key Takeaways 1. The evolution of Big Data and analytics
www.pwc.com Implementation of Big Data and Analytics Projects with Big Data Discovery and BICS Agenda Big Data Discovery Oracle Business Intelligence Cloud Services (BICS) Use Cases How to start and our
Leveraging UX Insights to Influence Product Strategy Frank Guo, PhD Many UX researchers and analysts aspire to influencing not only design implementation, but also product strategy. However, it is rather
Foreword I ve always wanted to start a company. I grew up watching my father build a chain of apparel stores, and I started my first business, Liberty Software, when I was 15. A friend and I wrote computer
Just-in-Time Marketing: Lessons from the Masters Marketers have changed the way they engage consumers, but have their changes taken them all the way back to the factory floor where marketing is produced?
Predictive Analytics: Too Important to Ignore The six secrets to success with predictive analytics Webinar December 18, 2013 Sponsored by: Tony Cosentino VP & Research Director, Business Analytics Ventana
HR STILL GETTING IT WRONG BIG DATA & PREDICTIVE ANALYTICS THE RIGHT WAY OVERVIEW Research cited by Forbes estimates that more than half of companies sampled (over 60%) are investing in big data and predictive
Marketers About This White Paper Expectations for business-to-business ( B2B ) organizations to measure return on marketing investments and to justify marketing decisions have never been greater. New marketing
A Forrester Consulting Thought Leadership Paper Commissioned By Google July 2015 Moments That Matter Intent-Rich Moments Are Critical To Winning Today s Consumer Journey Table Of Contents Executive Summary...
WHITE PAPER Turning Insight Into Action The Journey to Social Media Intelligence Turning Insight Into Action The Journey to Social Media Intelligence From Data to Decisions Social media generates an enormous
IBM SPSS Modeler Three proven methods to achieve a higher ROI from data mining Take your business results to the next level Highlights: Incorporate additional types of data in your predictive models By
Call Center Analytics Revealed Why Technology is not Your Actionable Business Intelligence Panacea Customer Relationship Metrics 1 Dr. Jodie Monger is the president of Customer Relationship Metrics and
Moving the NPS Needle - How to Use Customer Feedback to Drive Improvement Content Introduction: NPS for the Digital Enterprise 3 Chapter Three: Taking Action with Net Promoter Online 12 Chapter One: Vanity
Forecasting Sales at Ska Brewing Company Matthew J. Drake with Eric Huggins, Fort Lewis College Vice President, Publisher: Tim Moore Associate Publisher and Director of Marketing: Amy Neidlinger Executive
Growth Services Selling Power: Better Sales Leads and Conversion Rates in a 360-Degree World Better Sales Leads and Conversion Rates in a 360-Degree World THE LEADERSHIP CHALLENGE: A WEALTH OF DATA Today,
The Fundamentals of Managed Service Provider (MSP) Programs Part 3 of 3 Part 3: Business Case and Readiness By Jennifer Spicher contents This is the final of a three-part series designed to outline key
The Essential CMO Guide to an Agile B2B Marketing Plan Executive Brief 7600 N. Capital of Texas Hwy Bldg C, Ste 250, Austin, TX 78731 877.402.9199 Fax: 512.652.2558 Executive Brief The Essential CMO Guide
WHITEPAPER Creating and Deploying Predictive Strategies that Drive Customer Value in Marketing, Sales and Risk Overview Angoss is helping its clients achieve significant revenue growth and measurable return
Global Insights on Succeeding in the Customer Experience Era 1 Contents Introduction 3 Methodology 4 Executive Summary 6 Findings 7 Our Take 16 Industry & Regional Appendix 18 2 Introduction Today s consumers
G00271717 Agenda Overview for Multichannel Marketing, 2015 Published: 19 December 2014 Analyst(s): Adam Sarner, Jennifer S. Beck Multichannel marketing is where content and context meet and where brand
Seilevel Whitepaper Forward Thinking for Tomorrow s Projects Requirements for Business Analytics By: Joy Beatty, VP of Research & Development & Karl Wiegers, Founder Process Impact We are seeing a change
SAP Executive Insight Best Practices of the Best-Run Sales Organizations Sales Opportunity Blueprinting Why are we talking about blueprints? After all, blueprints are used in the construction of buildings,
Powering Marketing Transformation The Five Tenets of Modern Marketing in Financial Services and Insurance Targeting Engagement Conversion Analytics Marketing Technology THE FIVE TENETS OF MODERN MARKETING
Data Driven Marketing B2B MARKETING AUTOMATION BENCHMARKS FIND. NURTURE. CONVERT. The most challenging obstacles to B2B Marketing Automation success and how marketers will overcome them in the year ahead.
IBM Software Thought Leadership White Paper July 2011 The case for Centralized Customer Decisioning A white paper written by James Taylor, Decision Management Solutions. This paper was produced in part
Solution in Detail Healthcare Executive Summary Contact Us Patient Relationship Management 2013 2014 SAP AG or an SAP affiliate company. Attract and Delight the Empowered Patient Engaged Consumers Information
I D C A N A L Y S T C O N N E C T I O N Dan Vesset Program Vice President, Business Analytics and Big Data Self-Service Big Data Analytics for Line of Business March 2015 Big data, in all its forms, is
Exceptional Customer Experience AND Credit Risk Management: How to Achieve Both Lynn Brunner Experian and the marks used herein are service marks or registered trademarks of Experian Information Solutions,
2015 Social Media Marketing Trends A 2015 survey and report on social media marketing practices and software usage By Megan Headley Research Director, TrustRadius First Published May 2015 2015 TrustRadius.
CRM Expert Advisor White Paper 3 Keys to Preparing for CRM Success: Avoid the Pitfalls and Follow Best Practices Ten years ago, when CRM was nascent in the market, companies believed the technology alone
3 day course to cover fundamentals and practices you need to know about data science and using R. #1 JOIN THE DATA REVOLUTION! Every object on earth is generating data, including our homes, our cars and
THE GENERAL MANAGERS PROGRAM Session Descriptions January 18-28, 2016 * Information subject to change ORIENTATION DINNER Professor Enz begins the program with a brief presentation on learning expectations.
GLOBAL BUSINESS EXCELLENCE Overview Executing a great strategy can be just as challenging if not more than formulating it. Today, strategy discussions are often perceived as the glamorous work, but knowing
A Forrester Consulting October 2014 Thought Leadership Paper Commissioned By Infosys Simplify And Innovate The Way You Consume Cloud Table Of Contents Executive Summary... 1 Cloud Adoption Is Gaining Maturity
Minutes on Modern Finance Best Practice Series Real-Time Versus Right-Time Decision Making A New Competitive Advantage The Analytics Advantage Real-Time Versus Right-Time Decision Making: A New Competitive
The State of Analytics Maturity for Healthcare Providers The DELTA Powered TM Analytics Assessment Benchmark Report - February 24, 2014 - The International Institute for Analytics and HIMSS Analytics iianalytics.com
PRACTICES REPORT BEST PRACTICES SURVEY: AGGREGATE FINDINGS REPORT Business Intelligence and Analytics: Leveraging Information for Value Creation and Competitive Advantage April 2007 Table of Contents Program
GUIDE Wealth Management 9 Social Media Guidelines for Wealth Management Firms Wealth Management 9 Social Media Guidelines for Wealth Management Firms Wealth management firms that embrace social media can
Delivering Customer Value Faster With Big Data Analytics Tackle the challenges of Big Data and real-time analytics with a cloud-based Decision Management Ecosystem James Taylor CEO Customer data is more
G00270685 Agenda Overview for Digital Commerce, 2015 Published: 18 December 2014 Analyst(s): Jennifer Polk Marketing is making a greater impact on, and taking more responsibility for, digital commerce.
1 CNBC s list of the Top 10 Most Stressful Jobs of 2011 revealed that the sixth most stressful job was that of an advertising account executive. The reason today s account executives are so stressed is
Benchmark Report Content Marketing in 2014: Sponsored By: 2014 Demand Metric Research Corporation in Partnership with Ascend2. All Rights Reserved. TABLE OF CONTENTS 3 Executive Summary 10 Content Campaign
IBM Software Group Introduction to Business Intelligence Vince Leat ASEAN SW Group 2007 IBM Corporation Discussion IBM Software Group What is Business Intelligence BI Vision Evolution Business Intelligence
Revitalizing Your CRM Initiative In this three article series, we re considering a few of the most relevant Customer Relationship Management (CRM) practices that can impact the effectiveness of small and
2.0 Big Data and Data Analytics (Volume 18, Number 3) By Heather A. Smith James D. McKeen Sponsored by: Introduction At a time when organizations are just beginning to do the hard work of standardizing
Get Better Business Results From the Four Stages of Your Customer Lifecycle Stage 1 Acquisition A white paper from Identify Unique Needs and Opportunities at Each Lifecycle Stage It s a given that having
Big Data Putting data to productive use Fast Forward What is big data, and why should you care? Get familiar with big data terminology, technologies, and techniques. Getting started with big data to realize
Kea Analyst Relations Industry analysts play a key role in defining markets and educating buyers. We work with clients to identify and track the most influential and relevant industry analysts, and advise
Discover How a 360-Degree View of the Customer Boosts Productivity and Profits eguide eguide Discover How a 360-Degree View of the Customer Boosts Productivity and Profits A guide on the benefits of using
2015 2015 South African Cloud Based Solutions to the Contact Centre Product Leadership Award Contents Background and Company Performance... 3 Industry Challenges... 3 Implementation Excellence... 4 Product
PRODUCT ANALYSIS REPORT IBM COGNOS BUSINESS INTELLIGENCE DATA VISUALIZATION: When Data Speaks Business Jorge García, TEC Senior BI and Data Management Analyst Technology Evaluation Centers Contents About
IBM Software Group White Paper Insurance Insurance customer retention and growth Leveraging business analytics to retain existing customers and cross-sell and up-sell insurance policies 2 Insurance customer
Measuring How Consumers Interact with Your Brand: Brand Engagement Monitor M er kl e Tho u g ht L eader s hip S e r i e s A Database Marketing Agency Executive Summary: Marketers face a challenging new
The Customer Experience: The Holy Grail of Competitive Advantage. 1 A great customer experience has emerged as the holy grail of competitive advantage. Providing a great customer experience has emerged
Business Trends in Location Analytics Exploring the Impact of Geographic Context On Business Processes Research Report Executive Summary Copyright Ventana Research 2013 Do Not Redistribute Without Permission
XRM: From Fragmentation to Integration Executive Summary Relationship management is dead! Long live relationship management! But it s not just about customers anymore. The value chain has grown so long
PREDICTIVE ANALYTICS AND THE AGE OF THE NEW KNOW 312.756.1760 firstname.lastname@example.org www.spr.com SPR Consulting In today s volatile, global economy, the ability to predict outcomes is more vital than ever. Competition
5 PRACTICES That Improve the Business Impact of Research 1. ALIGN DIRECTLY WITH KEY STAKEHOLDERS 2. LINK THE WHYS TO THE WHATS OF BIG DATA 3. FOCUS ON METRICS THAT MATTER 4. PROVE RESEARCH ROI 5. GET TO
Managing Customer Relationships A guide to help you identify a range of areas to address in order to get the most from your relationships with your customers Managing customer relationships should be seen
kincaidtoc.fm Page vii Friday, September 20, 2002 1:25 PM C ONTENTS Preface Acknowledgments xxi xxvii Part 1 CRM: Is It Right for Your Company? 1 Chapter 1 Commerce in the 21st Century 3 1.1 Understanding
G00270544 Agenda Overview for Customer Experience, 2015 Published: 22 December 2014 Analyst(s): Jake Sorofman Customer experience has emerged as a top priority for marketers. This overview summarizes how