Customer Data Platforms: Use People Data to Transform the Future of Marketing Engagement

ISBN-13: 9781119790112 / Angielski / Twarda / 2020 / 240 str.

Christopher B. O'Hara

Spis treści

Introduction 1The Pizza Challenge 1The Perils of Personalization 4Rise of the Avoidant Customer 5The Disconnected Data Dilemma 6Crossing the Customer Data Chasm 7Customer Data Platform (CDP) 8Chapter 1 The Customer Data Conundrum 11Data Silos 11Known Data 14Customer Relationship Management (CRM) 15Customer Resolution 15Data Portability 16Unknown Data 16Cross-Device Identity Management (CDIM) 19Connecting the Known and Unknown 20Data Onboarding 21People Silos 22Customer-Driven Thinker: Kevin Mannion 24Summary: The Customer Data Problem 26Chapter 2 The Brief, Wondrous Life of Customer Data Management 29Customer Data on Cards and Tape? 29Direct Mail and Email: The Prototypes of Modern Marketing 31A Brief History of Customer Data Management 32Relational Databases 34The Rise of CRM and Marketing Automation 35Marketing Automation 36Improved User Interface (UI) 37The Multichannel Multiverse of the Thoroughly Modern Marketer 38The Growth of Digital 38Today's Landscape 40Today's Martech Frankenstack 41Customer-Driven Thinker: Scott Brinker 43Summary: The Brief, Wondrous Life of Customer Data Management 44Chapter 3 What is a CDP, Anyway? 47Rise of the Customer Data Platform 47What Marketers Really Want from the CDP 51The Great RFP Adventure 52"We Want a Platform, Not a Product" 53Building a Platform Solution 54CDP Capabilities 54Data Collection 54Data Management 55Profile Unification 56Segmentation and Activation 56Insights/AI 57The Two (Actually Three) Types of CDPs 58A System of Insights 58System of Engagement 60The Third Type: Enterprise Holistic CDP 62Known and Unknown (CDMP) Data Must Be Unified 62A Business-User Friendly UI 62A Platform Ecosystem 63The Future is Here 64Customer-Driven Thinker: David Raab 65Summary: What is a CDP? 66Chapter 4 Organizing Customer Data 69Munging Data in the Midwest 69Elements of a Data Pipeline 71Data Management Steps 721 Data Ingestion 722 Data Harmonization 74Using an Information Model 753 Identity Management 76Benefits of Identity Management 77Spectrum of Identity 78Identity Management in Practice 794 Segmentation 79The Importance of Attributes 825 Activation 83Getting It Done 84Different Spheres of Influence 84Customer-Driven Thinker: Brad Feinberg 86Summary: Organizing Customer Data 88Chapter 5 Build a First-Party Data Asset with Consent 91Privacy-First is Customer-Driven 91Privacy Police: Browsers and Regulators 93Web Browsers and Standards Bodies 93Intelligent Tracking Prevention 94Enhanced Tracking Prevention and Brave 94Google's Chrome and AdID 94Government Regulators 95The Mistrustful Consumer 96How Can a Marketer Gain Trust? 98Attitudes Around the World 99The Privacy Paradox 100What Exactly is the Privacy Paradox? 101How Do You Solve the Paradox? 101Four Privacy Tactics to Try 102Customer-Driven Thinker: Sebastian Baltruszewicz 103Summary: Build a First-Party Data Asset with Consent 104Chapter 6 Building a Customer-Driven Marketing Machine 107Know, Personalize, Engage, and Measure 107Know ("the Right Person") 108Personalize ("the Right Message") 109Engage ("the Right Channel") 111Measure (and Optimize) 113Organizational Transformation 114The CDP Working Model 114Team 114Platform 116Use Cases 116Methodology 117Operating Model 118The People at the Center (the Center of Excellence Model) 119Marketing 120IT/CRM 121Analytics 122How the COE Works 123How to Get There from Here: A Working Maturity Model 124Channel Coordination Stages 126Engagement Maturity Stages 126Touchpoints: That Was Then 127Journeys: This is Now 127Experiences: This is the Future 128Summary: Build a Customer-Driven Marketing Machine 128Chapter 7 Adtech and the Data Management Platform 131The Magic Coffee Maker 131Background/Evolution of the DMP 132Five Sources of Value in DMP 133Advertising as Part of the Marketing Mix 134Role of Pseudonymous IDs in the Enterprise 135Advertising in "Walled Gardens" with First-Party Data 135End-to-end Journey Management: The CDMP 136Customer-Driven Thinker: Ron Amram 137Summary: Adtech and the Data Management Platform 138Chapter 8 Beyond Marketing 141The Expanding Role of Customer Data Across the Enterprise 141Service: Frontline Engagement with the Customer 144Commerce: The Storefront and the Nexus of Response 146Use of Commerce Data for Modeling and Scoring 147Sales: The B2B Context, and What That Means for Customer Data 149Sources of Truth 150Householding 150Targetable Attributes 151Marketing: The Brand Stewards, Revenue, and the Engagement Engine 151Customer-Driven Thinker: Kumar Subramanyam 152Summary: Beyond Marketing: Putting Sales, Service, and Commerce Data to Work 153Chapter 9 Machine Learning and Artificial Intelligence 155Once Upon a Time . . . in Silicon Valley 155Deep Learning and AI 156Back to the Hot Dogs 157Cast of Characters 157Customer-Driven Machine Learning and AI 159Data Science in Marketing 160Machine Learning Vs. Artificial Intelligence? 161What Does a Marketing Data Scientist Do? 161Customer Data and Experimental Design 161Customer Data, Machine Learning, and AI 162What is a Model? 162Labeled Vs. Unlabeled Data 162Fitting a Model to Data 162Making Predictions 163Regression 163Classification 163Finding Structure 164Clustering 164Dimensionality Reduction 164Neural Networks 164Applying Machine Learning and AI in Marketing 165Machine-Learned Segmentation 165Machine-Learned Attribution 167Image Recognition and Natural Language Processing (NLP) 168Importance of Customer Data for AI 169AI/ML in the Organization: Data Science Teams 170Customer-Driven Thinker: Alysia Borsa 171Summary: Machine Learning and Artificial Intelligence 173Chapter 10 Orchestrating a Personalized Customer Journey 175The Rise of Context Marketing 175Prescriptive Journeys 177Predictive Journeys 178Real-Time Interaction Management (RTIM) Journeys 180Customer-Driven Thinker: Laura Lisowski Cox 181Summary: Orchestrating a Personalized Customer Journey 183Chapter 11 Connected Data for Analytics 185Customer Data for Marketing Analytics 185Analytical Capabilities 188Analytics Data Sources 188Beyond the Basics 189Key Types of Analytics 190Marketing/Email Analytics 190DMP Analytics 191Multitouch Attribution (MTA) 192Media Mix Modeling (MMM) 193Marketing Analytics Platforms 194Enterprise Analytics/BI 195Customer-Driven Thinker: Vinny Rinaldi 197Summary: Connected Data for Analytics 199Chapter 12 Summary and Looking Ahead 201Summary 201Looking Ahead 204Category Shake-Out! 205Aggregate-Level Data and "FLOCtimization" 206A Fresh Start for Multitouch Attribution 206AI Finally Takes Over 207The Future 208Further Reading 209Acknowledgments 211About the Authors 213Index 215

O autorze

MARTIN KIHN is SVP, Strategy, Marketing Cloud at Salesforce. Previously, he spent 5 years as a leading Gartner analyst covering marketing, advertising, and data.CHRIS O'HARA is Vice President, Global Product Marketing at Salesforce for the Data & Identity Group, covering all things data-driven marketing and customer experience.