Synopses & Reviews
On average, large companies have 178 corporate accounts on various social networks, and the data they collect is exploding more and more each year. Sound vaguely familiar? This practical book—written from a business perspective, rather than a technical one—shows you how to mine social media data and apply useful analytics to business planning.
Every day, your customers, employees, and stakeholders comment on your company, your products, your brands, and other issues. How can you analyze this information and put it to work? Authors Lutz Finger and Soumitra Dutta have helped large international organizations use analytics for core functions beyond marketing, such as customer care and product development.
With this book, you will:
- Learn how to achieve business goals by creating appropriate measures in social media
- Examine real-world case studies that demonstrate how social media analysis was applied to a particular business need
- Discover state-of-the-art analysis tools and their potential limitations
Make sense of your companys social media data with Data Mining.
Synopsis
You can measure practically anything in the age of social media, but if you dont know what youre looking for, collecting mountains of data wont yield a grain of insight. This non-technical guide shows you how to extract significant business value from big data with Ask-Measure-Learn, a system that helps you ask the right questions, measure the right data, and then learn from the results.
Authors Lutz Finger and Soumitra Dutta originally devised this system to help governments and NGOs sift through volumes of data. With this book, these two experts provide business managers and analysts with a high-level overview of the Ask-Measure-Learn system, and demonstrate specific ways to apply social media analytics to marketing, sales, public relations, and customer management, using examples and case studies.
About the Author
Lutz Finger is head of Social and Unstructured Data Analytics at LinkedIn. Lutz is co-founder and former CEO of Fisheye Analytics, a media data mining company. As an expert for data analytics he has supported various industries, from Brands such as Telefonica or the Daily Mail Group to the governments and NGO s such as the World Economic Forum and the Olympic Committee .
Before building up Fisheye Analytics, Lutz led Dells online merchandizing business in Europe. Lutz is an Intra/Entrepreneur by heart. He has successfully built up several businesses such as a new sales center for Dell in Germany, an incubator for mobile applications for Ericsson and a start up selling online individualized Cards.
Lutz has a Masters in Quantum Physics and an MBA from INSEAD. Currently he is writing a book on how to use data analytics within a business together with Soumitra Dutta.
Soumitra Dutta is the Roland Berger Chaired Professor of Business and Technology at INSEAD and the founding director of INSEAD eLab, a center of excellence in the digital economy. From 1 July 2012, he will join the Samuel Curtis Graduate School of Management at Cornell University as its 11th Dean. Professor Dutta obtained his Ph.D. in computer science and his M.Sc. in business administration from the University of California at Berkeley. His current research is on technology strategy and innovation at both corporate and national policy levels. Professor Dutta has authored and co-authored several books, including “Throwing Sheep in the Boardroom: How Online Social Networking Will Transform Your Life, Work and World” (Fraser & Dutta 2008) investigating the implications of social network services for the enterprise. He has won several awards for research and pedagogy and is actively involved in policy development at national and European levels. His research has been showcased in the international media and he has taught in and consulted with international corporations.
Table of Contents
Praise for Ask, Measure, Learn; Introduction; The Fourth V of Data; The Promise; The Data Focus; Analytics Focus; What This Book Covers; Safari® Books Online; How to Contact Us; Acknowledgments; Media Measurement by Function; Chapter 1: Marketing; 1.1 Marketing and Social Media: The Promise and the Reality; 1.2 Three Myths about Social Media; 1.3 Branding; 1.4 Purchase Intent; 1.5 Summary; Chapter 2: Sales; 2.1 Introduction; 2.2 Reach Versus Intention; 2.3 Recommendation Systems; 2.4 The Technology of Recommendation Systems; 2.5 Trust, Personality, and Reason; 2.6 Summary; Chapter 3: Public Relations; 3.1 PR Often Has No Measurable ROI; 3.2 Measuring People; 3.3 Measuring Distributing; 3.4 PR to Warn; 3.5 Summary; Chapter 4: Customer Care; 4.1 New Voice of the Customer; 4.2 Customer Care 2.0; 4.3 Dos and Don'ts; 4.4 Is Social Customer Care the New Commodity?; 4.5 Automation and Business Intelligence; 4.6 Summary; Chapter 5: Social CRM: Market Research; 5.1 Case Study: Customer Lifecycle; 5.2 Analytical CRM: The New Frontier; 5.3 Which Data?; 5.4 Summary; Chapter 6: Gaming the System; 6.1 Spam and Robots; 6.2 Creating Reach; 6.3 How to Spot Bots; 6.4 Smearing Opponents; 6.5 Creating Influence and Intention; 6.6 Spreading Paid Opinions: Grassroots and Astroturfing; 6.7 Contagiousness; 6.8 The Opposite of Virality: Suppressing Messages; 6.9 Blurry Lines; 6.10 Summary; Chapter 7: Predictions; 7.1 Predicting the Future; 7.2 Prediction of Learning; 7.3 Predicting Elections; 7.4 Predicting Box Offices; 7.5 Predicting the Stock Market; 7.6 Closing Predictions; 7.7 Workbook Questions; Build Your Own Ask-Measure-Learn System; Chapter 8: Ask the Right Question; 8.1 Case Study: Major Telecom Company; 8.2 Formulate the Question; 8.3 An Industry in Search of a Question; 8.4 Summary; Chapter 9: Use the Right Data; 9.1 Which Data Is Important?; 9.2 Data Selection; 9.3 Summary; Chapter 10: Define the Right Measurement; 10.1 Examples of Social Media Metrics; 10.2 The Risks of Metrics; 10.3 Summary; Appendix; 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; Colophon;