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Ask, measure, learn : using social media analytics to understand and influence customer behavior /
You can measure practically anything in the age of social media, but if you don't know what you're looking for, collecting mountains of data won't yield a grain of insight. This non-technical guide shows you how to extract significant business value from big data with Ask-Measure-Lear...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Sebastopol :
O'Reilly,
[2014]
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Copyright
- Table of Contents
- 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
- Part I. Media Measurement by Function
- Chapter 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
- Purchase Intent
- How to Find Purchase Intent
- Behavioral Targeting
- Social Targeting
- Homophily versus Influence
- Social Connections versus Behavior
- The Influencer
- Summary
- Workbook
- Chapter 2. Sales
- Introduction
- Social Sales
- Data-Driven Sales
- Reach Versus Intention
- Social Confirmation Creates Trust
- 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
- Chapter 3. Public Relations
- PR Often Has No Measurable ROI
- Measuring People
- Reach in PR
- Context in PR
- Journalism CRM
- Communication Is Human
- Measuring Distributing
- Clipping
- The Myth of Number of Articles
- Reading Lists
- Engagement
- Effort versus Impact
- Case: Spread of the Idea of "Resilient India"
- PR to Warn
- Examples of PR disasters
- No Early Warning Systems
- Case: McDonald's
- Warning Signals
- Summary.
- Workbook
- Chapter 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
- Can we use it at all?
- A Dynamic Approach to Machine Learning
- Summary
- Workbook
- Chapter 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
- Chapter 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
- Chapter 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
- Part II. Build Your Own Ask-Measure-Learn System
- Chapter 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
- Chapter 9. Use the Right Data
- Which Data Is Important?
- Causation
- Testing for Correlation
- Error, or Why Structured Data Is Superior
- Cost and Insider Knowledge
- Case: A Matchmaking Engine
- Data Selection
- Sampling
- Subsets
- Case: Haiti
- Summary
- Workbook
- Chapter 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
- Part III. Appendix
- 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.