Case Study: social search, sentiment analysis, and classification, using Churnbar tools (http:://churnbar.com)

1. ChurnBar

3. Churn: 10.3%

4. Customer: 9.9m

5. £450.7m

8. Manual Classification: existing systems

9. Bayesian Classifier or independent probability model: to be developed.

10. Link to CRM system – to be developed. We will need to work with a CRM operator in order to test the system with real data.

12. Used our unique social media listening tool to collect posts;

13. Only used Microblogs (twitter and Friendfeed);

14. 1 week – 19th – 25th July;

15. Classifier

16. 200 randomly selected posts classified as positive, neutral, or negative – used to train classifier;

18. “@MarpleLeafPoynton residents campaigned fiercly to stop Tesco & won.They weren't anywhere near…”

19. “RT @Scotty_McTweety : note to self, tesco value plastic spoons are not designed for stirring”

20. 1541 positive; 422 high confidence

21. “@ Dan_Phillips93 oh :( Yeah, well I enjoy having to get permission to sell alcohol in tesco ...”

23. “ASDA CHOSEN BY YOU DEEP FILL BACON QUICHE ... Doesn’t actually taste that good. Stop”

24. “@asda why hasn't my never say never dvd fans directors cut been delivered to my house yet??”

25. 813 positive; 126 high confidence

26. “@JaidakissLOOOLsooooo.... i think we needa go asdaim start dancing agen :p ima bad gyal dancer”

28. “@ iChazzer I was going to get nesquik powder from sainsburys but thought it was rather expensive “

29. “in sainsburys while with my gran. Basterd”

30. 1491 positive, 626 high confidence

31. “@LouiseStewart No because the middle class shop at quality supermarkets like Sainsbury’s”

33. Sainsbury’s posts classified to call / no call – results offer obvious actions.

34. Criteria can be: a complaint; an insult - burning down the store; a problem; or a query... not always –ve.

36. “Had two mishaps at Sainsburys. Pack of Carling collapsed and damaged my little finger.Ouch! Also £6…”

37. “@abikaylicious but my own always has kokojare. Hmmm. Do they sell poundo flour at sainsburys ? I…”

39. Using our tools, we can then find out more about the person.

41. Product categories;

42. Product launches;

43. Special offers, etc.

44. Local issues

46. 1000 texts per supermarket per day (PSPD)

47. With 10 action items PSPD

48. Manually classify: (2 microblogs only)

49. 60 sec per text .

50. 60k sec (20 hours) PSPD.

51. Charge out at £40 per hour: £800 PSPD.

53. Automation will reduce costs. People costs are focussed on customer experience.

54. Drivers for multiple platforms (Facebook etc.) future-proofs investment

55. Make this activity practical (reading these texts is mind numbing) for volume brands with 1:100 signal to noise.

56. Sentiment classifiers make the system scalable.