Collective Intellect uses semantic analysis to process, in real-time, large volumes of social media conversations. The resulting intelligence provides insights into the social customer: what they're buying, viewing, having problems with, including demographic or life stage data.

1. REAL TIME SOCIAL ANALTYICS
Collective Intellect
The Social Customer is Sharing. Is
Your Business Listening?
December 12, 2012
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2. Can Customer Service Data Come From Unlikely
Sources?
LIKE THE CUSTOMER?
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3. Is There Really Information of Value in a Tweet?
Isn’t it all just RTs, mentions and links to cat
videos?
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4. Customer Voice, Customer Data
Customers are doing more than mentioning, they’re sharing
Brand Selected Social handle
Daypart Gender Location Subjective
Dimensions: Taste, Quality
Sentiment: Negative
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5. Social Feedback – More Than Mentions & RTs
and are providing social feedback that can help your organization
extend your understanding
Social recognition
Ratania Green links online social
• 1396 Henry Dr identities with
• Sullivan’s Island,SC traditional data
• thill@gmail.com records.
• Married, 23
• Income 35 K / Yr
• Twitter ID:
@LoveProfusion13
Student
DISH, HBO user
High Passion Score For
Lady Gaga
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6. Social Feedback Can Provide An Early Indicator
@Collectual partnered with CNBC to track 20 key
retailers using a social conversation index during
Black Friday and Cyber Monday and beyond to
understand intent to shop and problem dimensions
as compared to just buzz
• Kohl’s consistently ranked 14/20 in the Likely to Buy category
• Kohl’s sales data released a week later validated CI’s rank
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7. Social Feedback Can Provide Early Alerts
Consumer conversations
related to “Likely to Buy”
for Best Buy peaked
nearly a week in advance
of Black Friday and a
week in advance of
Cyber Monday.
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8. Best Buy Led the Group in the “Likely to Buy”
Category on Black Friday
What’s important to your
organization consumer
intentions or mentions?
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9. Best Buy Led the Group in the “Likely to Buy”
Category on Cyber Monday
Real-time analysis is
critical but historical
reporting provides
context.
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10. Real-time Social Feedback
How would your organization respond?
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11. REAL TIME SOCIAL ANALTYICS
Social Feedback is Voice of
Customer
Nov 11, 2011
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12. Insights about consumers preferences enable
targeted communication…if companies are listening
Actionable
Topic insight
DISH – Open to
earned media
Technical
Problem
We qualify consumers and understand them.
DISH –
Offer sports-
Problem,
related
Content packaging
Selection
Channel lookup
DISH – content
Looking
for a Entertain
channel community
development
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13. Social Feedback creates new engagement points
throughout the lifecycle
2. Consumers add or subtract brands as they engage in
content and evaluate what they want/need
3. Consumer selects brand
at moment of purchase
INITIAL
CONSIDERATION PURCHASE
SET Loyalty Loop
Enjoy
1. Consumer considers Advocate
initial set of brands based on Bond
perceptions and exposure to
recent touch points
4. After purchase, customer builds expectations based on
Source: McKinsey experience to inform the next decision journey
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14. Social Feedback Resides in All Types of Data
onsumer
Generation
Social Data Enterprise Text Data
r Representative
players
works
§ 20 million unique authors
§ 500 unique forums/boards
al
networks
§ 500,000 posts/day § Survey/Focus Group Verbatim
Representative
players
stomization § 50 million unique authors
and
over-­‐the-­‐top
video
ased
services
§ 2 million fan pages/user groups
§ 1 million+ posts/day
nt
publication
and
aggregation § Private Community
ated
video
Conversations
ing § 15 million unique blogs (External & Internal)
communication
§ 1 million+ posts/day Social:
§ 10,000 new blogs/day § 250M unique authors
§ 300K new authors/day
§ Call Center/Email/
§ 90 million unique authors § 12M posts/day Chat Transcripts
§ 8 million tweets/day
§ 100,000 new authors/day Enterprise:
§ Any text-based data
§ 2.5 million authors § Setup within hours § Text-Translated Video
§ 40,000 unique sites
§ 200,000 posts/day
§ Private news, research,
§ 600 thousand unique consumers feeds
§ 60 thousand reviews/day
§ 25 unique review sites
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15. Mentions Are Just the Start of Social Monitoring
Intentions Interests Psychographics
§ Awareness § Category-Level: Language detection for common
Attributes and ways consumer segments talk:
§ Consideration/
Preference Associations § Age-Based (e.g. millennial)
§ Purchase § Brand-Level: § Gender-Based (e.g. women)
Features and
§ Referral Functions § Combinations (e.g. single mom/
parent)
§ Problem/Issue
§ Life-stage (e.g. Getting Fit,
§ Affinity/Loyalty
Newly Pregnant)
§ Advocacy
Often combined with self-published
demographic information
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16. REAL TIME SOCIAL ANALTYICS
Using Social Intelligence to
Transform an Organization into a
Social Business
Nov 11, 2011
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17. Moving Towards a Social Business
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18. Social Media Perspectives Within the Enterprise
Company's Perception of Social Media
100
90
80 Innovative and
invaluable to
70 business
60 Useful and helpful,
but could live without
50 it
40 Hasn't lived up to the
hype
30
20 Complicated and not
worth the investment
10
0
Have Strategy Don't Have
Strategy
Source: Social Media Examiner
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19. Social Media Perspectives Within the Enterprise
Challenges Implementing a Social Media Strategy
Not enough data or
9%
analytics to develop
ROI
12% Getting buy-in from
senior management
36%
Don't think audience
is active on social
media
21% Social is not part of
strategic roadmap
Can't develop a
compelling business
22% case
Source: Social Media Examiner
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20. Social Business Requires Change
There is a huge opportunity for
marketers to:
a) Learn about social media users’
interests and needs
b) Respond with meaningful and
relevant content and offers
Based on our research, marketers
have been reluctant thus far to use
social media because:
a) lack of familiarity with the nuances of Versus
social media
b) Difficulty in tracking ROI to justify
large budgets
c) Lack of suitable technology that can
scale beyond 1-1 marketing
Source: Nielsen, August 2010
http://socialfresh.com/marketers-are-not-spending-their-money-
where-users-arespending-their-time/#
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21. Social Data Can Support Many Business Functions
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22. REAL TIME SOCIAL ANALTYICS
Using Social Feedback & Insights:
Examples
Nov 11, 2011
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23. Using Social Intelligence - 1:1 Social Engagement
Example: A client can run a digital campaign encouraging new consumers
to follow their official twitter for news and in return follow those people
back. A client can analyze those consumers’ conversations and directly
engage with those consumers as their conversations warrant it
A Pepsi follower tweets “I’m thirsty”. Pepsi can @reply “here is a coupon for
our new drink”.
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24. Using Social Intelligence - Multichannel Marketing
Example: A client receives ~1000 social signals a day and communicates with
the consumers directly in a marketing channel where possible based on
established opt-in privileges
For example, a J Crew follower tweets “I need new jeans”. J Crew can now
email about their new fall sale.
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25. Using Social Intelligence – Socially-append CRM
Consumer Profiles Database
Example: Any promotion campaign or content sharing conducted through
client’s social assets (e.g., Facebook, Twitter), should seek to capture
consumer profile information (e.g. email, cell phone) by providing the
consumer incentive to do so
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26. Using Social Intelligence - Augment Client’s
Existing CRM Consumer Database
§ Overview: Clients can employ matching (e.g. mapping) services,
via a 3rd Party Provider, that look to find social profiles that connect
to their existing email or other personally identifiable records
§ Example: A company in the hospitality industry will look to
augment their email records with twitter profiles in order to
understand how “digitally savvy” their consumers are. Thereafter,
client-identified listening can be implemented, if volumes are
appropriate, to support higher scale 1:1 engagement and multi-
channel marketing.
Process
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27. Using Social Intelligence - Expected Results of
Email Matching
• Typically, CI expects to
achieve ~40% match rates to
social profiles to start
• Client can conduct this form
of matching independently
• Data results can be provided
to Client to assist with
appropriate communication
based on established industry
acceptable privacy/PII policy
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28. REAL TIME SOCIAL ANALTYICS
How CI Supports the Social
Business
Nov 11, 2011
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29. CI’s Text Analytics Product Suite
SIGNAL
On-Demand Enterprise Intelligence (Summer 2012)
§ Executive/Manager/Analyst Console
§ Blended Insight/View Interface
§ Self-Service topic/KPI setup
§ Comprehensive-based
INSIGHT VIEW
Research Insight Interface Executive Dashboard
§ Semantic topic/dimension configuration § KPIs Tracking (text + structured)
§ Blended Qualitative & Quantitative Analytics § Customized & Standard templates
§ Organic/Automated Insight Discovery § Track spikes, trends, anomalies
§ Sample-Based with Projections § Comprehensive-based
Collective Intellect Semantic Analytics Engine
Tens of Millions of social media conversations per day across 200+ million authors
Billions of social media conversations available for back-scoring
Ability to integrate client’s enterprise text data
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30. Why Does the Market Place Choose CI?
§ Precision - 95% categorization accuracy, auto-theming and
granular filters for semantic-based KPIs
§ Performance – processes ten of millions of messages daily, in
real-time
§ Usability – product suite that can support executive dashboards,
drill-down analytics and research reporting
§ Service – market experts and professional services for the last
6+ years
§ Ease of Deployment – accurate results achieve with minimal
configuration and setup (minutes)
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31. CI’s Semantic Engine – Blends 3 Different &
Powerful Technologies
Pre-filter:
§ Narrows large data-sets for analysis with Keyword/Boolean
more sophisticated semantic processing
› Issues with ambiguity
› Difficult to provide granular filtering
LSA
Insight:
§ High Quality Similarity Measures
§ High Performance for Speed and Precision NLP
§ Easier Maintenance
§ Used for Highly Accurate Categorization
§ Spam identification
Speech analysis:
§ Parsing content to diagram context
› Slow on large, unstructured text
› Time consuming to adjust with changing
content
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32. Data Purity = Better Consumer Intelligence
Collective Intellect Semantic Categorization of Reuters-21578, Distribution 1.0
Test Collection (92% correctly categorized in top 2 rankings)
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33. CI View– Key Performance Indicator (KPI)
Dashboard
Key Features
§ Customize KPI Dashboard
§ Compare/Contrast Segments
§ Updated up to hourly
§ CI Comprehensive Data Coverage
Key Use Cases
§ Executive/Lay-person BI Exploration
§ Identify trends, spikes and anomalies to
make course corrections and impact ROI
§ Pull insights/reports consistently and daily
§ See cause and effect of 1:1 Engagement
& Multichannel Marketing Rapidly
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