Architecting experience : a marketing science and digital analytics handbook / Scot R. Wheeler.

Format:

Book

Author/Creator:

Wheeler, Scot R., author.

Series:

Advances and opportunities with big data and analytics ; Volume 1.

Advances and Opportunities with Big Data and Analytics ; Volume 1

Language:

English

Subjects (All):

Communication in marketing.

Digital media.

Physical Description:

1 online resource (281 p.)

Place of Publication:

Hackensack, New Jersey : World Scientific, 2016.

Summary:

"In a world with a seemingly infinite amount of content and scores of methods for consuming that content, marketing communication today is about appealing to individuals, person by person. Effectively appealing to customers requires delivery of brand experiences built on relevance and recognition of context. Just as in any conversation, delivering relevance in context requires understanding the person one is speaking with and shared environment. Wheeler answers the biggest question facing digital marketers today: "with an ever expanding array of digital touch points at one's disposal, how does one deliver content and experiences around one's brand that build relationships and drives results?" The quick answer to this is "through the application of data and analytics to drive highly relevant, contextual targeted content and adaptive experience", but since this answer is not as easy to achieve as it is to say, Architecting Experience has been designed to help readers develop the understanding of marketing data, technology and analytics required to make this happen."-- Provided by publisher.

Contents:

Contents; About the Author; Introduction; Chapter ONE The Foundations of Personalization; 1.1 The New Business Value: Analytics Increase Relevance; 1.2 Introducing the "Demand Chain"; 1.3 The Customer Journey; 1.4 Research and Analytics; Chapter TWO Strategy, Technology, Science & Art; 2.1 Paid, Earned, or Owned Breakdown; The Challenge to "Collect & Connect"; 2.2 The Changing Nature of Marketing Data; Velocity; Variety; 2.3 The Fundamental Analytics Architecture: The Analytics Pyramid; Descriptive Analytics; Prescriptive Analytics; Predictive Analytics; Adaptive Analytics

Chapter THREE The Applied Digital Analytics Playbook (ADAP) Part One3.1 ADAP Section One: Problem Definition; Business Problem/Business Case; Business Objectives & Key Performance Indicators; Marketing Objectives & Key Performance Indicators; 3.2 ADAP Section Two: Solution Definition; Personas Aligned to Customer Objectives; Customer Problem; The Consumer Decision Journey Aligned to Touch-points; ADAP Part One Summary; Chapter FOUR The Changing World of Owned Media; 4.1 Web Architecture & Web Data Collection; 4.2 Client-side Tagging; Software Solutions Overview; Implementing Page Analytics

Implementing More Detailed Data Collection4.3 Tagging Design & Deployment; Tagging Approach: Annotations & Tag Matrix; Adding Other Tags; Tag Management; Implementation and Validation; 4.4 Mobile Marketing; 4.5 Email Marketing; Email Strategy; Email Data Collection; 4.6 Introducing Cookies; 4.7 Applying Owned Channel Metrics; Descriptive Owned Analytics; Chapter FIVE Earned Media: Organic Social & SEO; 5.1 History; 5.2 Organic vs. Paid Social Media; 5.3 Organic Social Media Strategy; 5.4 Inbound Organic Social Data Sources for Key Objectives

Sidebar: Structured vs. Unstructured Data, & Machine Learning5.5 Applying Social Metrics; Context & Research: Defining & Understanding Target Audiences; Social Media Aggregation and Listening Platforms; Network Dashboards; Social Network Application Programming Interfaces; Facebook Social Graph API; Social API Analytics Context & Research Objectives; Optimizing Social Engagement Delivery; Social Media Performance: Evaluating Social Influence & ROI; 5.6 Search Engine Optimization; Chapter SIX Paid Media Analytics; 6.1 Digital Paid Media Touch-points; 6.2 The Paid Media Ecosystem; CPM

CTR/VTR/CPCCost-per-Acquisition (CPA); 6.3 Targeting & Retargeting; Targeting; Retargeting; Paid Social Media; Facebook Ad Manager; Facebook Marketing API; 6.4 DSPs and Programmatic Real-time Bidding (RTB); Chapter SEVEN Testing & Optimization. Marketing Automation. Attribution; 7.1 Prescriptive Analytics: Testing & Optimization; Sidebar: Statistical Significance and Sample Size; Designing a Test; Context, Context, Context; Common Test Tool Functionality; Blind Spots and Dark Patterns; 7.2 Marketing Automation; Data Integration; Marketing Automation Platforms; 7.3 Cross-channel Attribution

Chapter EIGHT Data Management, Models, and Algorithms

Notes:

Includes index.

Description based on print version record.

Includes bibliographical references and index.

ISBN:

9789814678421

9814678422