Jodee Rich - Effective Engagement through Analytics

The Collective Stream of
Consciousness and Industry
Disruption
A November 2010 Review
Jodee Rich CEO
PeopleBrowsr

2
HUMAN SOCIALISATION
Collective Consciousness and Industry Disruption – November 2010
Swinging through the trees..

3
HUMAN SOCIALISATION
Emerging from the jungle with Language

4
HUMAN SOCIALISATION
Thousands of years later we wrote it down

5
HUMAN SOCIALISATION
PCs, the internet, cell phones have come
together to enable a vast distributed network of
human intelligence

6
HUMAN SOCIALISATION
A Persistent Stream of Consciousness..

7
HUMAN SOCIALISATION
Established Industry, the Stream and the Cloud

8
HUMAN SOCIALISATION
Persistent Social Framework displaces Industry

9
YEARS TO REACH 50 MILLION SUBSCRIBERS
Radio 38 Years
TV 13 Years
Facebook 100 Million in less than 9 months
Source: Socialnomics09

10
“That’s what social
networking is all
about: worshipping
at the Altar of Self.”
nothing more than an
exercise in unashamed
public vanity for the Look
at Me generation”
Sandra Lee in The Sunday Telegraph - May 25, 2008
PERCEPTION TWO YEARS AGO…

11
1 YEAR OF TWITTER TRAFFIC:
View chart and stats on analytic.ly
Now at 50 Million Tweets/day

12
STREAM SIZE 2010: IT IS DAVID AND GOLIATH
Next to Facebook, the Twitter Stream is still small

13
1 MILLION BRAND MENTIONS PER DAY

14
2010 OPENNESS
Little Twitter is dragging the others out of the cave and into the open

15
OPENNESS
Because it is open, the Twitter Stream will become the core transport layer for rich
MetaData and Cross Network Links

16
SOCIAL VECTORS
Persona
Breaking Trends
Sentiment
Influence and Engagement
Trust
Relevance
Connectedness – Degrees of Separation

17
PERSONA
Individual Profiling and Metadata Analysis
BIO data
Location
Gender
Interests
Twitter Lists
Advocates and Critics

18
BREAKING TRENDS
How to leverage live trends
Matching themes
Influencers buzz
Audience word clouds
Industry trends
Competitors mentions
Shared links

19
SENTIMENT
How to transform positive and negative sentiment
into value
Engage with users
Manage unhappy customers
Build VIP Advocates
Identify critics
Customers support

20
INFLUENCE AND ENGAGEMENT
Influencer targeting to get in touch with opinion leaders
Followers and Following
Relationships
Points of engagement
Klout Scores
Advocates and Critics

21
TRUST
How to find most relevant Tweets
Influence
Geo-Locations
Degrees of Separation
Engagement
Gender
Metadata

22
RELEVANCE
How to find most relevant Tweets and Users
Matching keywords in Tweets
Matching Location
Matching keywords in BIO
Relationships
Shared Links

23
CONNECTEDNESS
Degrees of Separation to spot hub users
Number of connections
Number of interactions
Mutual Friends
Relationships
Shared Links

24
CASE STUDIES
Reaching Mommy
ABC Hotlist
Sony Pictures
Comcast Entertainment
eBay
Toyota Recall
Super Bowl Ads
UK Elections
Music Influencers in New York
A Slide Deck

REACHING MOMMY - PERSONA
How to create hyper-filtered Categories from MetaData
Action Mommies
25Collective Consciousness and Industry Disruption – November 2010

Action Mommies
Expecting or New Mommies
26

Action Mommies
Expecting or New Mommies
Money Mommies
27

MOMMY BLOGGERS
What they say – Tweets Word Cloud
Thanking people
– especially for
RTs and
@Replies

REACHING MOMMY - TRUST
From Mommy to Mommy…
Trusted Mommies
Trusted People in the area
Other Mommies
Followers & Friends

REACHING
MOMMY
-CONNECTEDNES
S
Degrees of
Separation for
spotting connected
Mommys

31
Goal:
Evaluate impact of Traditional Media on the
Social Media sphere
Build engaged audience
Solution: 180 day Historical Analysis of Posts
overlay on TV Ad spend and other channels
Performance and Results
Identified type of ads that
produce the best audience
response
50% fluctuation on engagement
based on time of message
release

32
Industry: Media Entertainment
Goals:
Promote a Network TV Premiere
Create online Buzz during the Event
Performance and Results
Number 1 Twitter Trending Topic
during Premiere
Over 17,000 mentions of the
#Hashtag during the week of the
Premiere

33
Seek an effective way to measure brand sentiment
accurately. The goal is to find a list of influencers
speaking in both positive and negative terms and engage.
Call center to respond to negative sentiment everyday
Velocity
10,000
Mentions/day
filtered to
180
Meaningful
comments
Velocity
10,000
Mentions/day
filtered to
180
Meaningful
comments

34
TOYOTA RECALL SENTIMENT ANALYSIS
Overwhelming negative mainstream media
coverage and very little negative social media
comment

We analyze 18 months of historical data and live streams in real time
We use a special algorithm and then have real people improving
the result up to 95% accuracy.
95%
accuracy
Vs 70-80%
automation
alone
35
US AIRLINE INDUSTRY STUDY JUNE 2009

Analytics:
• Effect of Traditional Media on
Social Media
• Mechanical Turk to measure
accurate Sentiment
•Metrics to measure Success:
• Total Mentions
• Positive Mentions
By Volume
Mullen and Radian6
36
SUPER BOWL

37
SUPER BOWL
Results:
• 103,158 Total Mentions
• Sampled 1000 Tweets from Every Brand and used
Mechanical Turk Human Sentiment to analyze
• Polarized:
• 50% Positive
• 28% Negative
• 18% Neutral

38
SUPER BOWL

39
SUPER BOWL Correlation of Tweets and Ads

40
SUPER BOWL
By Volume
Mullen and Radian6
O’Reilly and PeopleBrowsrO’Reilly and PeopleBrowsr
By VolumeBy Positive

Top Bands:
• Mgmt
• Vampire Weekend
• Passion Pit
• Anamanaguchi
• Animal Collective
• The Strokes
Researched 900 bands in NY
Extracted mentions of each in the
last 6 months Selected most
mentioned
41
NEW YORK MUSIC INDUSTRY
Top Music Influencers:
• @Jimmyfallon
• @Nytimes
• @TheOnion
• @johnlegend
• @maddow
• @InStyle
Influencers – extracted biggest
music labels/accounts followers +
everyone in NY on Twitter
directory + NY users under
music/venues Twitter lists

42
INDUSTRY DISRUPTION Banking
Source:
http://www.nytimes.com/external/readwriteweb/2010/05/17/17readwritewe
b-twitter-forefather-leaves-aims-to-disrupt-b-89770.html

43
INDUSTRY DISRUPTION News
24 of the Top 25 Newspapers are in decline

44
INDUSTRY DISRUPTION News
24 of the Top 25 Newspapers are in decline
Air France Flight 447 Disaster Tweets appeared 6 hours before
Search Google Results

45
INDUSTRY DISRUPTION Advertising
14% of the population Trust an Ad
78% Trust what their Friends say

46
INDUSTRY DISRUPTION Web Search
Facebook has more traffic than Google

47
INDUSTRY DISRUPTION Web Search
Facebook has more traffic than Google
Social Media Search provides a better result than Google for
links and recommendations

48
Source:
http://www.briansolis.com/
INDUSTRY DISRUPTION Marketing and
Brand Management
Top 20 Brands on Twitter – April 2010

49
Source: http://blogs.hbr.org/research/2010/05/why-
gallup-when-you-can-tweet.html
INDUSTRY DISRUPTION Polling
Why Poll when you can extract?

50
INDUSTRY DISRUPTION Entertainment

51
THE NEXT TWO YEARS
Its very early Days..

52
THE NEXT TWO YEARS
Its very early Days
“Google fears Facebook, Facebook fears Twitter,
Twitter fears 4square, 4square fears two men in a garage”

53
SMS is the benchmark
Twitter, Facebook and the other
networks are still small, 150 Million
posts/day combined
SMS is over 7 Billion/day
SCALE

54
Links published in Posts on an interesting topic will have
greater reach than links published in main stream News
>
DISTRIBUTION

55
Mentions, RTs, …
Comments, Sharing,…
Profiles, Comments, …
Status Updates, Comments, …
Pictures, Comments, …
Connections, Comments
Blogs Mentions, …
Fan Pages
SMS
CROSS PLATFORM INTEGRATION

56
TWEETS PER CAPITA
Source: PeopleBrowsr DataMine
A new SocioEconomic KPI

57
THE NEXT TWO YEARS
The Conversation Stream becomes the Conversation Cloud
A real time
historical
record

58
THE NEXT TWO YEARS
The Conversation Cloud becomes the Rich Metadata Cloud
Social Media Stream
will become the core
backbone for people data

59
EXPERIMENTAL APPS
What can we build?
RESEARCH.LY
Contextual Search and Post
Artificial Intelligence - AI
Cloud powered Q and A

60
EXPERIMENTAL APPS AI
What can we build?
In the past the quest for
AI has been driven by
machine learning
projects.
They have been
Training and CPU
intensive

61
EXPERIMENTAL APPS AI
What can we build?
Artificial Intelligence
AI is now
Build a database of Questions
and Answers from the
Twitterverse
Crowdsource Questions without
Answers – Crowdflower
Devote CPU cycles to
contextual analysis and NLP
Artificial Intelligence
AI was
about machine learning or CPU
cycles
For the first time we have a vast
open database of Questions
and Answers
Lets turn the problem upside
down..

62
RESEARCH.LY
Instant Community around what interests you today

63
RESEARCH.LY

64
RESEARCH.LY
Every search shows related and
connected data in the form of images,
videos, @names, #tags, RTs and URLs
Each result can be used to search deeper
just by clicking it or used as content for your
own tweet in the Compose box

65
VAST DYNAMIC DATA STORES POWER
COLLECTIVE CONSCIOUSNESS

66
REFERENCES
This deck – http://bit.ly/analyticly
www.Analytic.ly
Socialnomics09
Social Media in Plain English
PeopleBrowsr Super Bowl Study
PeopleBrowsr Top 20 Brands Study
http://www.slideshare.net/peoplebrows
r/the-twitter-metadata-revolution-and-
collective-consciousness
http://www.nytimes.com/external/read
writeweb/2010/05/17/17readwriteweb-
twitter-forefather-leaves-aims-to-
disrupt-b-89770.html
http://blogs.hbr.org/research/2010/05/
why-gallup-when-you-can-tweet.html
http://www.briansolis.com/2010/05/rep
ort-top-20-brands-on-twitter-april-2010/

Jodee Rich - Effective Engagement through Analytics

Recommandé

Recommandé

Contenu connexe

Similaire à Jodee Rich - Effective Engagement through Analytics

Similaire à Jodee Rich - Effective Engagement through Analytics (20)

Plus de Influence People

Plus de Influence People (20)

Dernier

Dernier (20)

Jodee Rich - Effective Engagement through Analytics

Notes de l'éditeur