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Building a Digital Analytics Organization Create Value by Integrating Analytical Processes, Technology, and People into Business Operations

ISBN-10: 0133372782

ISBN-13: 9780133372786

Edition: 2014

Authors: Judah Phillips

List price: $49.99
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Description:

Drive maximum business value from digital analytics, web analytics, site analytics, and business intelligence! In Building a Digital Analytics Organization, pioneering expert Judah Phillips thoroughly explains digital analytics to business practitioners, and presents best practices for using it to reduce costs and increase profitable revenue throughout the business. Phillips covers everything from making the business case through defining and executing strategy, and shows how to successfully integrate analytical processes, technology, and people in all aspects of operations. This unbiased and product-independent guide is replete with examples, many based on the author’s own extensive experience. Coverage includes: key concepts; focusing initiatives and strategy on business value, not technology; building an effective analytics organization; choosing the right tools (and understanding their limitations); creating processes and managing data; analyzing paid, owned, and earned digital media; performing competitive and qualitative analyses; optimizing and testing sites; implementing integrated multichannel digital analytics; targeting consumers; automating marketing processes; and preparing for the revolutionary “analytical economy.” For all business practitioners interested in analytics and business intelligence in all areas of the organization.
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Book details

List price: $49.99
Copyright year: 2014
Publisher: Pearson Education
Publication date: 7/30/2013
Binding: Hardcover
Pages: 336
Size: 6.50" wide x 9.50" long x 1.25" tall
Weight: 1.650
Language: English

Using Digital Analytics to Create Business Value
Big Data and Data Science Requires Digital Analytics
Defining Digital Analytics
Analytics Value Chain and the P's of Digital Analytics
Explaining the P's of Digital Analytics
The Analytics Value Chain: Process for Tactical and Strategic Success
The Analytics Work Request Process
Building an Analytics Organization
Justifying Investment in the Analytics Team
Creating the Analytics Team Business Justification and Investment Consideration
Reporting to Executives and Other Teams about Analytics Value Generation
Creating Analytics Team Roles and Responsibilities
Enhancing Your Career: Methods for Success
What Are Analytics Tools?
To Build or to Buy?
Balancing Management of Analytics Technology: Should "the Business" or IT Run It?
Selecting an Analytics Tool
Succeeding with Tool Deployment
Business Concerns: Maintenance
Why Do Digital Analytics Tools and Data Decay?
Methods and Techniques for Digital Analysis
Storytelling Is Important for Analysis
Tukey's Exploratory Data Analysis Is an Important Concept in Digital Analytics
Types of Data: Simplified
Looking at Data: Shapes of Data
Analyzing Digital Data Using Statistics and Machine Learning
Defining, Planning, Collecting, and Governing Data in Digital Analytics
Defining Digital Data: How to Do It
What Are Business Definitions for Digital Data?
What Are Operational Definitions for Digital Data?
What Are Technical Definitions for Digital Data?
Creating and Maintaining Data Definitions
Planning for Digital Data: What Should You Do?
Collecting Digital Data: What You Need to Know
Governing Digital Data: The Data Governance Function
The Data Governance Team: What Do They Do?
The Process for Data Governance Across Programs, Projects, and Teams
The Difficulty of Testing and Verifying Data
Reporting Data and Using Key Performance Indicators
What Is Reporting and How Does It Happen?
The Five Elements of Excellent Reporting: RASTA
The Difference Between Reporting and Dashboarding
What Is Dashboarding and How Does It Happen?
The Five Elements of Excellent Dashboarding: LIVES
Understanding Key Performance Indicators (KPIs)
Where Does Reporting and Dashboarding Fit in the Analytics Value Chain?
Example KPIs: Averages, Percentages, Rates/Ratios, "Per X", and Derivatives
Real-Time Versus Timely Data: A Practitioner Perspective
Optimization and Testing with Digital Analytics: Test, Don't Guess
Reviewing the AB Test: Start Here
Expanding to Multivariate Testing
Creating a Testing and Optimization Plan
The Process of AB and Multivariate Testing
Technologies and Methods for Measuring, Analyzing, and Reporting Results of AB and Multivariate Testing
Types of Optimization Enabled Through Testing
Setting Up a Digital Optimization Program
Developing Controlled Experiments and Digital Data Science
Tips for Testing and Optimizing Digital Experiences
Qualitative and Voice of Customer Data and Digital Analytics
Listening to Your Customer Is More Important Today Than Ever Before
Tools of the Trade: Market Research and Qualitative Data Collection Methods and Techniques
Creating Customer Feedback Systems Such as Call Centers and Online Feedback Forms
What Does a Qualitative Data Team Do and How Does It Work with Digital Analytics?
Integrating Digital Behavioral Data with Qualitative Data
Working Successfully Together and with the Business: Qualitative and Quantitative Data, Research, and Analytics Teams
Competitive Intelligence and Digital Analytics
Competitive Intelligence Versus Digital Intelligence
Types of Digital Competitive Intelligence: Real-World Examples
Digital Competitive Intelligence Tools and Methods
The Process for Digital Competitive Intelligence
Integrating Digital Behavioral Data with Competitive Intelligence
Targeting and Automation with Digital Analytics
Types of Targeting
Where in Digital Does Targeting Occur?
What Is Retargeting?
Types of Retargeting
How Can the Digital Analytics Team Assist the Process of Targeting and Retargeting?
Suggestions When Targeting and Retargeting: Lessons Learned
Converging Omnichannels and Integrating Data for Understanding Customers, Audiences, and Media
Types of Omnichannel Data
Omnichannel Data Metrics
Denning Customer Analytics: Enabled by Omnichannel Data Integration
Questioning Customers Using Their Data and Your Analytics
The Unified Customer Life Cycle
Work Activities in Customer Analytics via Omnichannel Data Integration
Challenges to Customer Analytics
What's Required for the Digital Analytics Team to Do Customer Analytics via Omnichannel Integration?
Future of Digital Analytics
Predictive Personalization
Closed-Loop Behavioral Feedback Systems
Real-Time, Addressable, Relevant Content and Advertising Delivered Unified Across Multiscreens
Sensing and Responding
Interacting and Alerting
Geo-Specific Relevance and Intent Targeting
Automated Services and Product Delivery
Data-Interactive Shopper and Customer Experiences
The Future of Analytics Requires Privacy and Ethics
Works Cited
Index