Social Media and the Analytics Opportunity Frank Cotignola (@fco24) March 13, 2013

1. Social Media and the Analytics OpportunityFrank Cotignola (@fco24)March 13, 2013

2. Agenda • Data mining for social sites • Social media listening (platforms, text analytics/sentiment analysis) • Social media data as big data component

3. “The same digital and social data that are revolutionizing ad targeting and relationship building offer us researchers the opportunity of a lifetime. It is the chance to make the bemoaning go away… that we are too slow, that our findings aren’t actionable, and that we are genetically modified versions of accountants who don’t get what the business is about.” Joel Rubinson http://goo.gl/yxUES

4. Data mining for social sites

5. What is “social media listening?”

6. Understanding Consumers Via: 1. Social Media Conversations2. Search Behavior3. Integration With Other Data

7. How can this uncover opportunities?By going beyond brands and typical dig sites

8. Can we understand consumer needs without asking consumers?

9. “Pick me up” eating occasions

10. Energy drinks describe “pick me up” and “wake me up” (and negatively)Time of day also important Mentions Likes/Dislikes 4,223,452 Mentions 68,340 mentions 423,750 mentions 99,510 mentions NetBase December 18, 2012

11. Taste is polarizing Likes Dislikes NetBase December 18, 2012

12. Facebook and Twitter far outweigh other domains people are using to talk about “Pick Me Up” Twitter FB NetBase December 18, 2012

13. Conversations are morning/food dominated NetBase December 18, 2012

14. Hashtags/what to solve?

15. Social Media Listening (Platforms, Text Analytics, Sentiment Analysis)

16. What is your goal? Sentiment? Managed Internally? Use Agency? Tracking? Brand Reputation? Mentions? Measure Influence? Insights? BI? Because We’re Supposed To?

17. Different goals require different solutions

19. Things to consider • Interested in tracking mentions, sentiment, engagement, etc., most large services work well • Cost, deployment a consideration • Free tools? • If true BI and insights are your goal, you need to go beyond mentions and sentiment • How to integrate with more traditional insights? • Starting or ending point?

20. Barriers 20

21. Flavors

22. What Flavors are being talked about? Mint Source: Tracx 30 days ending 2-19-13

23. Blogs dominate flavor conversations Source: Tracx 30 days ending 2-19-13

24. Mint also dominates search Source: Google Trends Through 2-19-13

25. Sentiment mostly neutral, although some strong negatives/positives Source: Tracx 30 days ending 2-19-13

26. Focus on Parmesan, Basil conversationsingredient, cooking focus Source: Tracx 30 days ending 2-19-13

27. Social media as big data component

28. The “Big Data” RealityWe still live in a world of small data • Use of tools hasn’t caught up to the promise (world of Excel) • Can’t put my finger on all the data we have • Big data confused with knowledge management • What are the common elements? • How do we integrate? • “How is this different from what I am doing already?”

29. What’s typically done:Overlay conversations onto sales dataDoes this tell us anything? Net Sentiment # Of Comments Source: NetBase

30. What’s possible http://goo.gl/hIrTs

31. http://www.sickweather.com/

32. Forecasting the Economy

33. “Destroy”Positive vs. negative behaviors about the economy Source: NetBase 52 Weeks Ending September 1, 2012

34. Sentiment about the economy grew more positive in Q4 (but still overall negative) Top Sources of Buzz Source: NetBase January 3, 2013,

35. “Strong” and “Weak” dominated (but not “destroyed”) Source: NetBase January 3, 2013,

36. “Government” dominates (expected after election) but still focus on “jobs” and “taxes” Source: NetBase January 3, 2013,

37. IN THE END… • Social Media Can Provide Insights on Its Own • It Can Also Enhance “Asking” Research

38. Thank you! Frank Cotignola @fco24 www.frankcotignola.com

39. Hed Text • Bullets • If • Needed