{"product_id":"win-with-advanced-business-analytics-isbn-9781118370605","title":"Win with Advanced Business Analytics","description":"\u003cb\u003ePlain English guidance for strategic business analytics and big data implementation\u003c\/b\u003e  \u003cp\u003eIn today's challenging economy, business analytics and big data have become more and more ubiquitous. While some businesses don't even know where to start, others are struggling to move from beyond basic reporting. In some instances management and executives do not see the value of analytics or have a clear understanding of business analytics vision mandate and benefits. \u003ci\u003eWin with Advanced Analytics\u003c\/i\u003e focuses on integrating multiple types of intelligence, such as web analytics, customer feedback, competitive intelligence, customer behavior, and industry intelligence into your business practice.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eProvides the essential concept and framework to implement business analytics\u003c\/li\u003e \u003cli\u003eWritten clearly for a nontechnical audience\u003c\/li\u003e \u003cli\u003eFilled with case studies across a variety of industries\u003c\/li\u003e \u003cli\u003eUniquely focuses on integrating multiple types of big data intelligence into your business\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eCompanies now operate on a global scale and are inundated with a large volume of data from multiple locations and sources: B2B data, B2C data, traffic data, transactional data, third party vendor data, macroeconomic data, etc. Packed with case studies from multiple countries across a variety of industries, \u003ci\u003eWin with Advanced Analytics\u003c\/i\u003e provides a comprehensive framework and applications of how to leverage business analytics\/big data to outpace the competition.\u003c\/p\u003e \u003cp\u003ePreface xv\u003c\/p\u003e \u003cp\u003eAcknowledgments xvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 The Challenge of Business Analytics 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Challenge from Outside 5\u003c\/p\u003e \u003cp\u003eThe Challenge from Within 9\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Pillars of Business Analytics Success: The BASP Framework 15\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBusiness Challenges Pillar 18\u003c\/p\u003e \u003cp\u003eData Foundation Pillar 20\u003c\/p\u003e \u003cp\u003eAnalytics Implementation Pillar 22\u003c\/p\u003e \u003cp\u003eInsight Pillar 26\u003c\/p\u003e \u003cp\u003eExecution and Measurement Pillar 29\u003c\/p\u003e \u003cp\u003eDistributed Knowledge Pillar 31\u003c\/p\u003e \u003cp\u003eInnovation Pillar 32\u003c\/p\u003e \u003cp\u003eConclusion 33\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Aligning Key Business Challenges across the Enterprise 35\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eMission Statement 36\u003c\/p\u003e \u003cp\u003eBusiness Challenge 38\u003c\/p\u003e \u003cp\u003eIdentifying Business Challenges as a Consultative Process 39\u003c\/p\u003e \u003cp\u003eIdentify and Prioritize Business Challenges 41\u003c\/p\u003e \u003cp\u003eAnalytics Solutions for Business Challenges 45\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 Big and Little Data: Different Types of Intelligence 51\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBig Data 57\u003c\/p\u003e \u003cp\u003eLittle Data 61\u003c\/p\u003e \u003cp\u003eLaying the Data Foundation: Data Quality 62\u003c\/p\u003e \u003cp\u003eData Sources and Locations 65\u003c\/p\u003e \u003cp\u003eData Definition and Governance 69\u003c\/p\u003e \u003cp\u003eData Dictionary and Data Key Users 72\u003c\/p\u003e \u003cp\u003eSanity Check and Data Visualization 72\u003c\/p\u003e \u003cp\u003eCustomer Data Integration and Data Management 73\u003c\/p\u003e \u003cp\u003eData Privacy 74\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Who Cares about Data? How to Uncover Insights 77\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe IMPACT Cycle 79\u003c\/p\u003e \u003cp\u003eCuriosity Can Kill the Cat 82\u003c\/p\u003e \u003cp\u003eMaster the Data 86\u003c\/p\u003e \u003cp\u003eA Fact in Search of Meaning 87\u003c\/p\u003e \u003cp\u003eActions Speak Louder Than Data 88\u003c\/p\u003e \u003cp\u003e“Eat Like a Bird, Poop Like an Elephant” 89\u003c\/p\u003e \u003cp\u003eTrack Your Outcomes 91\u003c\/p\u003e \u003cp\u003eThe IMPACT Cycle in Action: The Monster Employment Index 92\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Data Visualization: Presenting Information Clearly: The CONVINCE Framework 95\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eConvey Meaning 97\u003c\/p\u003e \u003cp\u003eObjectivity: Be True to Your Data 99\u003c\/p\u003e \u003cp\u003eNecessity: Don’t Boil the Ocean 101\u003c\/p\u003e \u003cp\u003eVisual Honesty: Size Matters 103\u003c\/p\u003e \u003cp\u003eImagine the Audience 104\u003c\/p\u003e \u003cp\u003eNimble: No Death by 1,000 Graphs 107\u003c\/p\u003e \u003cp\u003eContext 107\u003c\/p\u003e \u003cp\u003eEncourage Interaction 109\u003c\/p\u003e \u003cp\u003eConclusion 109\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Analytics Implementation: What Works and What Does Not 113\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAnalytics Implementation Model 117\u003c\/p\u003e \u003cp\u003eVision and Mandate 118\u003c\/p\u003e \u003cp\u003eStrategy 119\u003c\/p\u003e \u003cp\u003eOrganizational Collaboration 121\u003c\/p\u003e \u003cp\u003eHuman Capital 122\u003c\/p\u003e \u003cp\u003eMetrics and Measurement 123\u003c\/p\u003e \u003cp\u003eIntegrated Processes 124\u003c\/p\u003e \u003cp\u003eCustomer Experience 125\u003c\/p\u003e \u003cp\u003eTechnology and Tools 125\u003c\/p\u003e \u003cp\u003eChange Management 126\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Voice-of-the-Customer Analytics and Insights 131\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eBy Abhilasha Mehta, PhD\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eCustomer Feedback is Invaluable 132\u003c\/p\u003e \u003cp\u003eThe Makings of an Effective Voice-of-the-Customer Program 137\u003c\/p\u003e \u003cp\u003eStrategy and Elements of the VOC System 152\u003c\/p\u003e \u003cp\u003eCommon VOC Program Pitfalls 162\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Leveraging Digital Analytics Effectively 165\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eBy Judah Phillips\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eStrategic and Tactical Use of Digital Analytics 173\u003c\/p\u003e \u003cp\u003eUnderstanding Digital Analytics Concepts 174\u003c\/p\u003e \u003cp\u003eDigital Analytics Team: People are Most Important for Analytical Success 184\u003c\/p\u003e \u003cp\u003eDigital Analytics Tools 187\u003c\/p\u003e \u003cp\u003eAdvanced Digital Analytics 191\u003c\/p\u003e \u003cp\u003eDigital Analytics and Voice of the Customer 192\u003c\/p\u003e \u003cp\u003eAnalytics of Site and Landing Page Optimization 194\u003c\/p\u003e \u003cp\u003eCall to Action: Unify Traditional and Digital Analytics 195\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Effective Predictive Analytics: What Works and What Does Not 199\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhat is Predictive Analytics? 201\u003c\/p\u003e \u003cp\u003eUnlocking Stage 203\u003c\/p\u003e \u003cp\u003ePrediction Stage 206\u003c\/p\u003e \u003cp\u003eOptimization Stage 210\u003c\/p\u003e \u003cp\u003eDiverse Applications for Diverse Business Problems 213\u003c\/p\u003e \u003cp\u003eFinancial Service Industries as Pioneers 214\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 Predictive Analytics Applied to Human Resources 223\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eBy Jac Fitz-enz, PhD\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eStaff Roles 225\u003c\/p\u003e \u003cp\u003eAssessment: Beyond People 226\u003c\/p\u003e \u003cp\u003ePlanning Shift 229\u003c\/p\u003e \u003cp\u003eCompetency versus Capability 229\u003c\/p\u003e \u003cp\u003eProduction 230\u003c\/p\u003e \u003cp\u003eHR Process Management 231\u003c\/p\u003e \u003cp\u003eHR Analysis and Predictability 232\u003c\/p\u003e \u003cp\u003eElevate HR with Analytics 233\u003c\/p\u003e \u003cp\u003eValue Hierarchy 235\u003c\/p\u003e \u003cp\u003eHR Reporting 237\u003c\/p\u003e \u003cp\u003eHR Success through Analytics 238\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12 Social Media Analytics 247\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eBy Judah Phillips\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eSocial Media is Multidimensional 249\u003c\/p\u003e \u003cp\u003eUnderstanding Social Media Analytics: Useful Concepts 251\u003c\/p\u003e \u003cp\u003eIs Social Media about Brand or Direct Response? 254\u003c\/p\u003e \u003cp\u003eSocial Media “Brand” and “Direct Response” Analytics 255\u003c\/p\u003e \u003cp\u003eSocial Media Tools 259\u003c\/p\u003e \u003cp\u003eSocial Media Analytical Techniques 262\u003c\/p\u003e \u003cp\u003eSocial Media Analytics and Privacy 265\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13 The Competitive Intelligence Mandate 271\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCompetitive Intelligence Defined 273\u003c\/p\u003e \u003cp\u003ePrinciples for CI Success 275\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14 Mobile Analytics 285\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eBy Judah Phillips\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eUnderstanding Mobile Analytics Concepts 290\u003c\/p\u003e \u003cp\u003eHow is Mobile Analytics Different from Site Analytics? 291\u003c\/p\u003e \u003cp\u003eImportance of Measuring Mobile Analytics 295\u003c\/p\u003e \u003cp\u003eMobile Analytics Tools 296\u003c\/p\u003e \u003cp\u003eBusiness Optimization with Mobile Analytics 298\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 15 Effective Analytics Communication Strategies 301\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCommunication: The Gap between Analysts and Executives 303\u003c\/p\u003e \u003cp\u003eAn Effective Analytics Communication Strategy 305\u003c\/p\u003e \u003cp\u003eAnalytics Communication Tips 314\u003c\/p\u003e \u003cp\u003eCommunicating through Mobile Business Intelligence 316\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 16 Business Performance Tracking: Execution and Measurement 321\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAnalytics’ Fundamental Questions 324\u003c\/p\u003e \u003cp\u003eAnalytics Execution 325\u003c\/p\u003e \u003cp\u003eBusiness Performance Tracking 332\u003c\/p\u003e \u003cp\u003eAnalytics and Marketing 336\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 17 Analytics and Innovation 343\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhat is Innovation? 344\u003c\/p\u003e \u003cp\u003eWhat is the Promise of Advanced Analytics? 347\u003c\/p\u003e \u003cp\u003eWhat Makes Up Innovation in Analytics? 348\u003c\/p\u003e \u003cp\u003eIntersection between Analytics and Innovation 352\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 18 Unstructured Data Analytics: The Next Frontier 359\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhat is Unstructured Data Analytics? 360\u003c\/p\u003e \u003cp\u003eThe Unstructured Data Analytics Industry 363\u003c\/p\u003e \u003cp\u003eUses of Unstructured Data Analytics 364\u003c\/p\u003e \u003cp\u003eHow Unstructured Data Analytics Works 365\u003c\/p\u003e \u003cp\u003eWhy Unstructured Data is the Next Analytical Frontier 366\u003c\/p\u003e \u003cp\u003eUnstructured Analytics Success Stories 372\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 19 The Future of Analytics 377\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eData Become Less Valuable 379\u003c\/p\u003e \u003cp\u003ePredictive Becomes the New Standard 380\u003c\/p\u003e \u003cp\u003eSocial Information Processing and Distributed Computing 381\u003c\/p\u003e \u003cp\u003eAdvances in Machine Learning 382\u003c\/p\u003e \u003cp\u003eTraditional Data Models Evolve 383\u003c\/p\u003e \u003cp\u003eAnalytics Becomes More Accessible to the Nonanalyst 384\u003c\/p\u003e \u003cp\u003eData Science Becomes a Specialized Department 385\u003c\/p\u003e \u003cp\u003eHuman-Centered Computing 386\u003c\/p\u003e \u003cp\u003eAnalytics to Solve Social Problems 387\u003c\/p\u003e \u003cp\u003eLocation-Based Data Explosion 388\u003c\/p\u003e \u003cp\u003eData Privacy Backlash 388\u003c\/p\u003e \u003cp\u003eAbout the Authors 391\u003c\/p\u003e \u003cp\u003eIndex 393\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eJEAN PAUL ISSON\u003c\/b\u003e is an internationally recognized speaker and an expert in advanced business analytics. He is Global Vice President of BI and predictive analytics at Monster Worldwide, Inc., where he has built his team from the ground up and successfully conceived and implemented advanced analytics and web mining solutions. Prior to joining Monster, Isson led the global customer behavior modeling team at Rogers Wireless, implementing churn models and pioneering the Customer Lifetime Value segmentation to optimize services marketing and sales activities. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eJESSE S. HARRIOTT, P\u003csmall\u003eH\u003c\/small\u003eD,\u003c\/b\u003e is Chief Analytics Officer for Constant Contact. Previously, Jesse was Chief Knowledge Officer at Monster Worldwide where he helped drive annual revenue from $300 million to over $1.3 billion. Harriott started an international analytics division at Monster and created the Monster Employment Index, now tracked in the United States, Europe, and Asia by millions of people. He also led web analytics, business intelligence, competitive intelligence, data governance, marketing research, and sales analytics departments for Monster. Jesse has taught at the University of Chicago and was named one of Boston's Top 40 Under 40.   \u003c\/p\u003e\u003cp\u003eToday's companies operate on a global scale and are inundated with an overwhelming volume of data from a number of multiple locations and sources: B2B data, B2C data, traffic data, transactional data, third-party vendor data, and macroeconomic data, among others. While some businesses don't even know where to start, others are still struggling to move beyond basic reporting. In some instances, management and executives don't have a clear understanding of business intelligence and don't see the value of analytics. \u003c\/p\u003e\u003cp\u003eWith invaluable insights from authors Jean Paul Isson and Jesse Harriott—renowned business intelligence (BI) leaders—\u003ci\u003eWin with Advanced Business Analytics: Creating Business Value from Your Data\u003c\/i\u003e provides CFOs, chief marketing officers, directors of marketing, and business managers with a new way of looking at integrating the multiple types of intelligence into their business practice. \u003c\/p\u003e\u003cp\u003eWritten clearly for the nontechnical professional, this definitive guide shows you how to gain the most opportunity and value from \u003ci\u003eevery\u003c\/i\u003e type of business intelligence, with essential guidance on: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eThe challenge of business analytics\u003c\/li\u003e \u003cli\u003eThe BASP framework: pillars of business analytics success\u003c\/li\u003e \u003cli\u003eBig and little data—different types of intelligence\u003c\/li\u003e \u003cli\u003eLeveraging digital analytics effectively\u003c\/li\u003e \u003cli\u003eWinning with predictive analytics\u003c\/li\u003e \u003cli\u003eSocial media analytics\u003c\/li\u003e \u003cli\u003eMobile analytics\u003c\/li\u003e \u003cli\u003eThe future of analytics\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eUse data more effectively. Take your analytics to the next level. Unleash the potential buried in your company's data. Do it all with the visionary guidance found in \u003ci\u003eWin with Advanced Business Analytics\u003c\/i\u003e. \t   \u003c\/p\u003e\u003cp\u003eToday's companies operate on a global scale and are inundated with an overwhelming volume of data from a number of multiple locations and sources: B2B data, B2C data, traffic data, transactional data, third-party vendor data, and macroeconomic data, among others. While some businesses don't even know where to start, others are still struggling to move beyond basic reporting. In some instances, management and executives don't have a clear understanding of businessintelligence and don't see the value of analytics. \u003c\/p\u003e\u003cp\u003eWith invaluable insights from authors Jean Paul Isson and Jesse Harriott—renowned businessintelligence (BI) leaders—\u003ci\u003eWin with Advanced Business Analytics: Creating Business Value from Your Data\u003c\/i\u003e provides CFOs, chief marketing officers, directors of marketing, and business managers with a new way of looking at integrating the multiple types of intelligence into their business practice. \u003c\/p\u003e\u003cp\u003eWritten clearly for the nontechnical professional, this definitive guide shows you how to gain the most opportunity and value from \u003ci\u003eevery\u003c\/i\u003e type of business intelligence, with essential guidance on: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eThe challenge of business analytics\u003c\/li\u003e \u003cli\u003eThe BASP framework: pillars of business analytics success\u003c\/li\u003e \u003cli\u003eBig and little data—different types of intelligence\u003c\/li\u003e \u003cli\u003eLeveraging digital analytics effectively\u003c\/li\u003e \u003cli\u003eWinning with predictive analytics\u003c\/li\u003e \u003cli\u003eSocial media analytics\u003c\/li\u003e \u003cli\u003eMobile analytics\u003c\/li\u003e \u003cli\u003eThe future of analytics\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eUse data more effectively. Take your analytics to the next level. Unleash the potential buried in your company's data. Do it all with the visionary guidance found in \u003ci\u003eWin with Advanced Business Analytics\u003c\/i\u003e.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47990493937893,"sku":"NP9781118370605","price":60.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118370605.jpg?v=1761788050","url":"https:\/\/k12savings.com\/products\/win-with-advanced-business-analytics-isbn-9781118370605","provider":"K12savings","version":"1.0","type":"link"}