Spies and suits conference peoplebrowsr Sept 2011


Published on

Social Analytics presentation delivered at www.suitsandspooks.com by PeopleBrowsr CEO Jodee Rich

Published in: Technology, Business
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide
  • Insert RS RTA Chart
  • Insert Classifed stamp
  • Spies and suits conference peoplebrowsr Sept 2011

    1. 1. PeopleBrowsr Spies and Suits 2011<br />Jodee Rich<br />CEO PeopleBrowsr<br />
    2. 2.
    3. 3. 3<br />Social Media Strategy<br />LISTEN ENGAGE INFLUENCE<br />
    4. 4. 4<br />Social Media Stats<br />10,000 posts/second<br />Over 10 Billion Conversations- 1% Gold 100% Real<br />Millions of Small related Networks<br />
    5. 5. 5<br />BIG PICTURE<br />Human Socialization<br />Swinging through the trees…<br />
    6. 6. 6<br />BIG PICTURE<br />Emerging from the jungle with Language…<br />
    7. 7. 7<br />BIG PICTURE<br />Thousands of years later we wrote it down…<br />
    8. 8. 8<br />BIG PICTURE<br />PCs, the internet, mobile phones, GPS have come together to enable a vast distributed data network of collective memory <br />
    9. 9. 9<br />BIG PICTURE<br />A collective stream of intelligence…<br />
    10. 10. 10<br />Little Brother<br />Connected Little Brothers will be a higher intelligence than Big Brother<br />
    11. 11. 11<br />Little Brother<br />
    12. 12. 12<br />An Inverted Orwellian Revolution<br />Little Brother has access tovast amounts of data<br />
    13. 13. 13<br />Human Connectedness<br />Viral Streams will add light fiber power to the Collective Intelligence<br />Small Networks close networks will be more powerful than individual Influencers<br />
    14. 14. 14<br />Social Vectors<br />CONNECTEDNESS<br />BREAKING TRENDS<br />SENTIMENT<br />INFLUENCE<br />RELEVANCE<br />TRUST<br />PERSONA<br />
    15. 15. 15<br />Evolution of Influence<br />2009 number of Followers<br />2010 Followers and Engagement (RTs, @Replies)<br />2011 most number of Friends talking about the topic<br />
    16. 16. 16<br />Huffington Post Influence<br />
    17. 17. 17<br />Huffington Post Influence<br />
    18. 18. 18<br />Cartoon Deck – Viral Influence<br />http://bit.ly/hFltVp<br />
    19. 19. 19<br />SOCIAL VECTORS<br />Find Community Champions<br />Architect | Blogger | Cat Lover | Celebrities | CEO | Coffee Lovers | Comcast | Comedy | Cool Brands | Dancers | Dating | Doctor | Dog Lovers | Engineer | Extreme Sports | Finance | Food | Lawyer | Marketing | Mommy Bloggers | Musician | News | Photography | Politics | Religion | Reporter | Social Media | Sport | Travel | VIP | Wall St | Wine Lovers<br />People are 300% more likely to engage when properly targeted<br />
    20. 20. 20<br />Case Studies<br />
    21. 21. 21<br />CASE STUDIES<br />TV Analytics<br />Social TV Analytics will eventually replace Nielsen as the primary data used by Media Buyers…. <br />Here’s Why…<br />
    22. 22. 22<br />CASE STUDIES<br />Objectives<br />Replace Nielsen rating system with Social Media Data<br />Identify TV Show preferences of the Social Audience<br />Implement traditional ratings with Social Data to achieve more accurate results<br />
    23. 23. 23<br />CASE STUDIES<br />The Test Case<br />Filter Social mentions of 900 major TV Shows in the United States<br />Communities Composed of Social Media Users related by their Affinities<br />
    24. 24. 24<br />CASE STUDIES<br />The Solution<br />TV Show Identification<br />Search beyond exact Show Titles<br />AKAs<br />Typos<br />Characters Names<br />Actors Names<br />House OR Gregory House OR GregoryHouse OR Doctor House OR DoctorHouse OR DrHouse OR Dr House OR Doctor Cuddy OR DoctorCuddy OR DrCuddy OR Lisa Cuddy OR Hugh Laurie OR ….<br />
    25. 25. 25<br />CASE STUDIES<br />The Solution<br />TV Show Identification<br />Filter out noise and irrelevant results<br />Contextual <br />Proximity<br />Exclusions<br />NOT the house OR my house OR your house OR *s house OR this house OR that house OR cleaning OR for sale OR buying OR sold OR bought OR dog house OR our house OR full house OR fire OR leave OR party OR white OR …<br />
    26. 26. 26<br />CASE STUDIES<br />The Solution<br />Communities<br />Identify demographics through<br />Declared Age<br />Marital Status<br />Profession<br />Followers of account<br />Under18 = (student OR freshman OR junior OR senior) AND (list of 18K high schools) OR in high school OR I’m 6-17 years old OR I’m a teenager OR student of (high schools) OR studying for the ACTs OR learning to drive OR I want a fake ID OR …<br />
    27. 27. 27<br />CASE STUDIES<br />Data Size<br />Total number of TV Show mentions since January 2011<br />30 Million<br />
    28. 28. 28<br />Data Size<br />Number of people in each Community<br />Under 18 – 1,615,107<br />Age 19-24 – 412,479<br />Age 25-35 – 1,636,156<br />Moms – 370,762<br />Heavy Searchers U. 18 – 132,231<br />Heavy Searchers 19-24 – 40,980<br />Heavy Searchers 25-35 – 201,238<br />100K – 346,537<br />Allergy – 134,585<br />Tech – 5,111,413<br />Adventure + Tech – 1,673,600<br />Active Investors – 5,127<br />Adventurers/Outdoors – 139,121<br />
    29. 29. 29<br />Data Size<br />Number of people in each Community<br />
    30. 30. 30<br />CASE STUDIES<br />TV Shows Analytics<br />TV Show: 60 Minutes<br />
    31. 31. 31<br />CASE STUDIES<br />TV Shows Analytics<br />Communities: Under 18<br />
    32. 32. 32<br />Data Flow - Communities<br />Firehose<br />RabbitMQ<br />Xapian<br />Search Indexer<br />Search Engine<br />Communitiser<br />Text File<br />
    33. 33. 33<br />CASE STUDIES<br />Ad Measurement<br />Industry: Media Entertainment<br />Background: Creation of a Twitter report for studio executives/ impact of promo scheduling<br />Length of Engagement: 8 months<br />Goals:Evaluate the impact of traditional media on the social media sphere<br />PeopleBrowsr Solution: 180 days historical reporting with overlay of traditional ad schedule<br />Performance and Results:<br />75,353 <br /># of Tweets extracted for 180 days<br />12:30p & 7:00p Peak times of engagement <br />60/40 <br />M/F demographic breakdown of tweets<br />
    34. 34. 34<br />CASE STUDIES<br />Champions Campaign<br />Performance and Results:<br />50%<br />Percentage of total registrations from Twitter<br />5,000<br /># of new followers<br />36%<br /># of CTR<br />Industry: Computer Software <br />Background: Large software company aiming to promote itself on social media channels<br />Engagement: 12 months<br />Goals: Maximize participation to online seminars and increase awareness<br />PeopleBrowsr Solution: Extract all users aligned with SAP target audience; most influential selected for engagement<br />
    35. 35. 35<br />CASE STUDIES<br />2011 Super Bowl YTD<br />387,162 vs 99,124<br /> Total Tweets 2011 Total Tweets 2010<br />From last year, total volume of Tweets mentioning Super Bowl brands increased 271%.<br />Doritos had the highest number of mentions in 2010 and was the 3rd top mentioned brand this year, with an 89% increase in volume in 2011.<br />In 2011, most social activity of all ads was in the Auto industry, represented by Volkswagon, Chrysler and Chevrolet. <br />
    36. 36. 36<br />CASE STUDIES<br />Trend Analytics<br />Viral Analytics… RT Acceleration<br />
    37. 37. 37<br />CASE STUDIES<br />
    38. 38. 38<br />CASE STUDIES<br />Trust Triangulation<br />There is a young girl trapped in the basement<br />Location<br />Influence<br />Kredentials<br />
    39. 39. 39<br />CASE STUDIES<br />Bot Detection Metrics<br />Sent Post Count to @Name Mention Ratio<br />Sent Post Count to Key word frequency<br />Velocity<br />
    40. 40. 40<br />CASE STUDIES<br />Human Border Trafficking in the Middle East<br />Classified<br />
    41. 41. 41<br />Kred <br />Influence and Outreach<br />Transparent Activity Statement<br />Community Based<br />Group Kred<br />Outreach Meter<br />Fresh Content<br />Advisory Function<br />Detailed Analysis<br />
    42. 42. 42<br />What is Kred?<br />Kred is measurable Influence<br />Kred offers separate metrics for Influence and Outreach.<br />Influence measures a user’s relative ability to inspire action from others like retweeting, replies or new follows. <br />Outreach measures generosity and rewards actions like interaction with others and willingness to spread the message.<br />
    43. 43. 43<br />KredInfluence<br />Influence is the measure of what others do for you<br />It is reported to on a normalized 1,000 point scale.<br />Influence is measured by <br />Retweets<br />@replies<br />New follows<br />List following<br />Follow/following ratio<br />Influence is outbound – how you inspire others to take action.<br />
    44. 44. 44<br />KredOutreach<br />Outreach is the measure of generosity<br />Outreach points are based in levels and will increase infinitely as users interact and spread messages from others.<br />Outreach is measured by <br />Retweets<br />@replies<br />New follows<br />List following<br />Outreach represents how others inspire you to interact and engage.<br />
    45. 45. 45<br />Kredentials for every @name<br />
    46. 46. 46<br />Swinging through the trees…Language evolved<br />Little Brother will carry the next level of Human Evolution – Influencers and Authorities independent of Institutions<br />@WingDudeJodeeRich@PeopleBrowsr.com<br />
    47. 47. @WingDude<br />jodeerich@peoplebrowsr.com<br />http://slidesha.re/PBSnS<br />