Log In
Or create an account -> 
Imperial Library
  • Home
  • About
  • News
  • Upload
  • Forum
  • Help
  • Login/SignUp

Index
Ask, Measure, Learn Dedication Dedication Introduction
The Fourth V of Data The Promise The Data Focus
More Data Better Technology
Analytics Focus What This Book Covers
Chapter Outline
Safari® Books Online How to Contact Us
Acknowledgments I. Media Measurement by Function
1. Marketing
Marketing and Social Media: The Promise and the Reality Three Myths about Social Media
Social Media Is Cheap Social Media Is Fast Social Media Is Just Another Channel
Branding
Social Media: A New Class of Metrics Reach Does Not Equal Awareness Case: Virgin Atlantic Airways
Where is Linda? Return on Investment: Was Linda Worth It?
Purchase Intent
How to Find Purchase Intent Behavioral Targeting Social Targeting
You Say It... You Like It... Your Friends Like It...
Homophily versus Influence Social Connections versus Behavior The Influencer
Summary
Workbook
2. Sales
Introduction
Social Sales Data-Driven Sales
Reach Versus Intention
Social Confirmation Creates Trust
User Ratings User comments
Peer Pressure Do Social Confirmation and Peer Pressure Work? What—or Who—Would Make You Buy?
Recommendation Systems
Collaborative Recommendations Content-Based Recommendations
The Technology of Recommendation Systems
The Cold-Start Problem Not Enough Data No Surprises How to Build a Recommendation System: Start Small
Trust, Personality, and Reason
Personal Relationships Reason
Summary
Workbook
3. Public Relations
PR Often Has No Measurable ROI Measuring People
Reach in PR Context in PR
Context of the content Context of the author
Journalism CRM Communication Is Human
Six principles of influence
Measuring Distributing
Clipping The Myth of Number of Articles Reading Lists Engagement
Clicking Sharing, Liking, Thumbs Up Commenting Copying
Effort versus Impact Case: Spread of the Idea of “Resilient India”
PR to Warn
Examples of PR disasters
Inappropriate selling Underestimation of virality Self-censorship Impersonation
No Early Warning Systems
Nondeterministic Speed to disaster
Case: McDonald’s Warning Signals
Summary
Workbook
4. Customer Care
New Voice of the Customer
Dell Hell United Breaks Guitars
Customer Care 2.0
Knowledge Bases and Customer Self-Service Happier Employees Smart Selection Positive Publicity
Dos and Don’ts
Get Clients into Your Service Channel Mind the Trolls Resources and Scaling
Is Social Customer Care the New Commodity? Automation and Business Intelligence
A Case of Airline Customer Satisfaction Sentiment Algorithm
Anaphora Algorithm Context
Can we use it at all?
Case Sony Ericsson—special words
A Dynamic Approach to Machine Learning
Case: newBrandAnalytics Case: Dell’s customer care
Summary
Workbook
5. Social CRM: Market Research
Case Study: Customer Lifecycle Analytical CRM: The New Frontier
Issues with the Traditional Way Turning CRM Around Facebook and Open Graph
Which Data?
Social Media: Too Shallow? Personal Data: Too Sensitive?
Summary
Workbook
6. Gaming the System
Spam and Robots Creating Reach How to Spot Bots Smearing Opponents
John Sununu Follower Scandals
Creating Influence and Intention
A Turing Test on Twitter The US Military’s Search for Social Media Robots
Spreading Paid Opinions: Grassroots and Astroturfing
SOPA and PIPA Act: A Modern Grassroots Movement Microsoft’s Antitrust Case China’s 50-Cent Bloggers Cause, Access, and Reach
Contagiousness
Kony2012 Viral by Design The Truth about the Truth How to Spot Attempts to Create Contagiousness
The Opposite of Virality: Suppressing Messages Blurry Lines
The Case of Facebook
Summary
Workbook
7. Predictions
Predicting the Future Prediction of Learning Predicting Elections
Selection Bias Bad PR Bias Predicting Voting Behavior
Predicting Box Offices
The Movie Industry Insights with Caution Conclusion
Predicting the Stock Market Closing Predictions Workbook Questions
II. Build Your Own Ask-Measure-Learn System
8. Ask the Right Question
Case Study: Major Telecom Company
Background Knowledge Was He Heard?
Formulate the Question
Creative Discovery Domain Knowledge The Right Question
An Industry in Search of a Question Summary
Workbook Questions
9. Use the Right Data
Which Data Is Important?
Causation
Correlation versus causation
Direct effect Reverse effect The unknown third All of the above
Testing for Correlation Error, or Why Structured Data Is Superior
Structured Unstructured
Cost and Insider Knowledge Case: A Matchmaking Engine
Data Selection
Sampling Subsets
I know keywords No truth
Case: Haiti
Summary
Workbook
10. Define the Right Measurement
Examples of Social Media Metrics
Influence Consumer Preference The Quest for ROI
The Risks of Metrics
Influencing the metric Wrong behavior Changes Over Time and Space Overcoming the issues
Summary
Workbook
III. Appendix
A. All Names
Endorsement Introduction Chapter 1, Marketing Chapter 2, Sales Chapter 3, Public Relations Chapter 4, Customer Care Chapter 5, Social CRM: Market Research Chapter 6, Gaming the System Chapter 7, Predictions Chapter 8, Ask the Right Question Chapter 9, Use the Right Data Chapter 10, Define the Right Measurement
Index About the Authors Colophon Copyright
  • ← Prev
  • Back
  • Next →
  • ← Prev
  • Back
  • Next →

Chief Librarian: Las Zenow <zenow@riseup.net>
Fork the source code from gitlab
.

This is a mirror of the Tor onion service:
http://kx5thpx2olielkihfyo4jgjqfb7zx7wxr3sd4xzt26ochei4m6f7tayd.onion