1. S OCIAL M EDIA S CORECARDS C HAPTERS 07 & 08 OF S OCIAL M EDIA A NALYTICS W / OTHER M ATERIAL 1 Ravi K. Vatrapu Director, Computational Social Science Laboratory (CSSL) Associate Professor, Dept. of IT Management Copenhagen Business School Copenhagen Business School Phone: +45-2479-4315 Email: vatrapu@cbs.dk (preferred) Web: http://www.itu.dk/people/rkva/vatrapu@cbs.dkhttp://www.itu.dk/people/rkva/ Zeshan Jaffari zeshan.jaffari@gmail.com Friday, 04-November-2011 T17: SMA: Lecture 13 ITU: Auditorium 3, Copenhagen, Denmark

2. S OCIAL M EDIA S CORECARDS  Provide  Monitoring  Measurement  Include  Social Data  Web Analytics  Organic Search Queries  Also Include (Local Social Mobile)  QR Code  Mobile Check-Ins  House Data 2

3. S CORECARDS & A UTOMATION  Meaningful & Actionable  Coding: Manual vs. Automatic  Time + Expense vs. Efficiency + Accuracy  Scorecards as Automations  But then: What is Automation? 3

4. Definition of Automation Chapter 16 of “An Introduction to Human Factors Engineering (Second Edition)” 4 “Automation characterizes the circumstances when a machine (nowadays often a computer) assumes a task that is otherwise performed by the human operator” (p.418)  Aviation Industry Joke: Dog and Pilot in the Cockpit  Home Automation  Office Automation  Factory Automation  Social Media Analysis Automation

5. Reasons for Automation 5  Impossible or Hazardous  Difficult or Unpleasant  Extend Human Capability  Technically Possible

6. Stages of Automation 6 Stage 1: Information Acquisition, Selection, and Filtering Stage 2: Information Integration Stage 3: Action Selection and Choice Stage 4: Control and Action Execution

7. Levels of Automation 7 From Complete Manual Control to Complete Automatic Control 1.Automation Offers No Aid 2.Automation Suggests Multiple Alternatives 3.Automation Selects an Alternative 4.Automation Carries Out an Action if the Person Approves 5.Automation Provides the Person with Limited Time to Veto Action before it Carries Out the Action 6.Automation Carries Out an Action and then Informs the Person 7.Automation Carries Out an Action and Informs the Person Only if Asked 8.Automation Selects Method, Executes Task, and Ignores the Human

8. Problems in Automation 8  Automation Reliability  Calibration and Mistrust  Overtrust and Complacency  Workload and Situation Awareness  Training and Certification  Loss of Human Cooperation  Job Satisfaction

9. Functional Allocation : Person and Automation 9  Fitts List http://www.cse.sys.t.u-tokyo.ac.jp/furuta/teaching/csd/CSD06.pdf

10. Progress of Automation 10 http://www.cse.sys.t.u-tokyo.ac.jp/furuta/teaching/csd/CSD06.pdf

11. Principles of Human Centered Automation 11 1.Keeping the Human Informed 2.Keeping the Human Trained 3.Keeping the Operator in the Loop 4.Selecting Appropriate Stages and Levels When Automation is Imperfect 5.Making Automation Flexible and Adaptive 6.Maintaining a Positive Management Philosophy

12. Implications for Social Media Scorecards 12  Participant Observation  Qualitative Analysis  Interpersonal Communication  Establishing “Ground Truth”  Coding + Counting

13. Three Phases of Social Media Scorecards 13  Data Gathering  Data Analysis  Data Reporting

14. Examples of Social Media Scorecards 14  Ogilvy Conversation Impact  Razorfish Fluent  Zocalo Group’s Digital Footprint Index

15. Ogilvy Conversation Impact http://blog.ogilvypr.com/2009/06/introducing-conversation-impact-social-media-measurement-for-marketers/ http://blog.ogilvypr.com/2009/06/introducing-conversation-impact-social-media-measurement-for-marketers/ 15  Reach and Positioning  Unique monthly visits  Time on site  Overall volume  Share of voice within category or brand family  Search visibility  Preference  Sentiment index (% positive - % negative) in social media  Share of positive voice in social media, within category  Relative Net Promoter Score, absolute or within category  Action  Registrations  Sales  Advocacy

16. Razorfish Fluent http://fluent.razorfish.com/publication/?m=6540&l=1 http://fluent.razorfish.com/publication/?m=6540&l=1 16  Social Influence Marketing (SIM)  Reach  Sentiment  Social ads are “about infusing social content and a user’s social graph directly into the ad unit itself.”  Social graph is “the network of personal connections through which people com­municate and share information online. These personal connections can be based on common interests, professional experiences and offline social relationships.”

17. Zacolo Group’s Digital Footprint Index http://zocalogroup.com/ http://zocalogroup.com/ 17  Volume of Conversations  Location of Conversations  Level of Engagement  Message Adoption  Tonality  Height + Width + Depth

18. Example of DFI 18 http://www.webmetricsguru.com/archives/2009/09/a-social-media-scorecard-based-on-digital-footprint-index/

19. Questions to Clien 19 http://vigilmetrics.com/App_Themes/Default/images/gallery/Social%20Media%20Scorecard.PNG

20. Questions to Clients 20  General Requirements  Specific Requirements  Keywords and Volume Analysis  Reporting

21. Social Media Maturity of the Clients 21 Level 1: Monitoring Level 2: Online Research Level 3: Social Targetting and Data Management Level 4: Social Business Collaborations

22. Three Analytical Phases 22  Culling  Classifying  Contextualizing

23. Q&A for the Social Media Analyst 23 1.Which organizational unit is your analytics report oriented towards? 2.How sophisticated is the case company’s industry regarding social media? 3.How mature is the case company when it comes to socia media marketing, analytics, and management? 4.What is the budget, if any, allocated for socia media marketing, analytics, and management? 5.How much time is allocated to deliver results? 6.How much integration with other data sources? 7.What are the languages and regions for monitoring and measuring?

24. Discussion 24