Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)

INV307 - Big Data meets Social
Analytics - Revolutionizing How
Companies Address Customer Needs
Aya Soffer | Director, Information Management &
Analytics Research | IBM
Mark Heid | Program Director, Social Analytics |
IBM

© 2012 IBM Corporation

Agenda
■ Big Data – what is it, why now, why should I care?

■ Social Analytics – challenges and opportunities

■ Marketing in the era of Big Data and Social Analytics

■ Social Analytics innovation in IBM Research

■ IBM offerings and solutions

2 | © 2012 IBM Corporation

An Explosion of Data

1.3 Billion RFID tags in 2005
30 Billion RFID tags in 4.6 Billion mobile
phones worldwide
2010

Google processes
2 Billion Internet users in 2011
By 2013, annual internet traffic
> 24 Petabytes of data
will reach 667 Exabytes in a single day

Facebook processes
Twitter processes
10 Terabytes of data every 7 Terabytes of data every day
day

Hadron Collider at CERN For every session, NY Stock
generates 40 Terabytes Exchange captures 1 Terabyte
of data / sec of trade information

Information Overload… But Lacking Insight

Business leaders

44 1 in 3 make decisions based
as much Data and on information they
Content don’t trust, or don’t
have
Over Coming Decade

x
say they feel

56% overwhelmed by the
amount of data their
company manages

say they need to

60% do a better job
capturing and
understanding
2020
information rapidly
35 zettabytes
2011 cited “BI & Analytics”
2009 1.8 zettabytes
800,000 petabytes
83% as part of their
visionary plans to
enhance
competitiveness

4

The “BIG Data” Challenge
Extracting insight from
an immense volume, Manage the complexity of
multiple relational and non-
variety and velocity of Variety relational data types and
data, in context, beyond schemas
what was previously
possible.

Streaming data and large
Velocity volume data movement

Scale from terabytes to
Volume zettabytes


5

IBM’s Big Data Solution

Bringing Together a Large Multi-channel customer
Volume and Variety of Data to sentiment and experience
analysis
Find New Insights
 Analyzing a variety of data Detect life-threatening
at enormous volumes conditions at hospitals in
 Insights on streaming data time to intervene
 Large volume un-structured
data analysis Predict weather patterns to
plan optimal wind turbine
usage, and optimize capital
expenditure on asset
placement

Make risk decisions based on
real-time transactional data
IBM Big Data
Platform
 Variety
Identify criminals and threats
 Velocity
from disparate video, audio,
 Volume and data feeds

6

Merging the Traditional and Big Data Approaches
Traditional Approach Big Data Approach
Structured & Repeatable Analysis Iterative & Exploratory Analysis

IT
Business Users
Delivers a platform to
Determine what enable creative
question to ask discovery

IT Business
Structures the Explores what
data to answer questions could be
that question asked
Monthly sales reports Brand sentiment
Profitability analysis Product strategy
Customer surveys Maximum asset utilization


7

The intersection of social media and big data


Agenda






We have Many Challenges…and Opportunities

Years to reach Tablet
 Channels proliferate… 50M users: 2 Yrs

Facebook
 The Internet evolves… 3 Yrs

Internet
 The consumer is in control… 4 Yrs
Network of pages Network of people
TV
 The rate of change accelerates… 13 Yrs

Clearly organizations must evolve…

10

Social Analytics Has Extensive Potential

August 28, 2011 by R "Ray" Wang, Constallation Research

Customer Maturity Curve
Quantify & Predict & Integrate
Monitor & Engage
Operationalize Integrate Transparently
Business Outcomes

 Predict & Improve  Seamless Integration of
Outcomes With Internal, Extranet &
Continuous Feedback Public Social Media
 Identify & Measure ROI  Quantitatively Optimize Analysis & Action
 Operationalize Insight  Systemic Governance
Decisions Across
 Identify & Track KPIs via Business Processes Functions
 Qualitatively Improve  Quantitatively Improve  Limited Governance
Marketing Decisions  Embedded Social
Marketing Decisions
 Open-up Social Media Analytics
 Full Sentiment  “Targeted Crowd
Marketing Channel
 Geo-Spatial Analysis Sourcing”
 Limited sentiment  Platform Analysis
 Network & influencer  Predictive Modeling
analysis  SaaS & On Premise
Capabilities

 Monitor & Engage  Limited back-end
 Lightweight “Domain-  Partner / Ecosystem
process integration
Specific” Analytics Datasets
 SaaS & On Premise
 SaaS-Only  Complete Back-End
Sourcing: ERP, HR, etc
 Broad Public Social Media  3rd-Party Datasets
Sources

Sourcing (“Big Data”)  OEM-Level Sourcing of
Data

 Mainstream Social  Enterprise CRM & “Big Data”
Media Transactional Data

Organizational Maturity & Sophistication 12 | © 2012 IBM Corporation

Understanding the Customer and Answering: “Why”
High-value, dynamic approach
- source of competitive differentiation

Interaction data Attitudinal data
- E-Mail / chat transcripts -Market Research
How?
- Call center notes
- Web Click-streams
Why?
-Social Media

- In person dialogues

Descriptive data Behavioral data
- Attributes - Orders

Who? What?
- Characteristics - Transactions
- Self-declared info - Payment history
- (Geo)demographics - Usage history

“Traditional approach” 13 | © 2012 IBM Corporation

Agenda






Expanding marketing’s role, and contribution
to the business

+ Transformative CMO

Traditional CMO Agenda:
+ Understand the customer in real time,
across the business
Agenda: + Anticipate customer needs
 Understand the market and the + Drive consistent, compelling interactions
customer across all channels
 Build awareness and demand + Steward the customer experience across
 Steward the company’s brand all touch points
+ Monitor and harness customer evangelism
 Drive brand strategy and
+ Accountable for business outcomes and
execution
return on investment 15 | © 2012 IBM Corporation

15

The vast majority of CMOs are
underprepared to manage the impact of key
changes in the marketing arena
Underpreparedness
Percent of CMOs reporting underpreparedness

50%
Data explosion 71%
Social media 68%
Growth of channel and device choices 65%
Shifting consumer demographics 63%
Financial constraints 59%
Decreasing brand loyalty 57%
Growth market opportunities 56%
ROI accountability 56%
Customer collaboration and influence 56%
Privacy considerations 55%
Global outsourcing 54%
Regulatory considerations 50%
Corporate transparency 47%
Source: Q8 How prepared are you to manage the impact of the top 5 market factors that will have the most impact on your marketing organization over the next 3 to 5 years?
n=149 to 1141 (n = number of respondents who selected the factor as important)


16

Customers are the New Intellectual Property

(Keep the promise)

Customer
Intimacy

Decision
Management

Product Operational
Leadership Excellence
(Make the promise) (Deliver the promise)

17

We are seeing unprecedented upheaval in the
consumer buying process

In the past….there was a funnel

• Many Brands - Consumers start
buying process with a large
number of brands in mind
• Fewer Brands: These choices are
narrowed down to a few
• Final Choice: A decision is made
between the few
• Buy: A purchase is made…
• Post Purchase: Consumers’
relationship with the brand is
focused on the use of the product
or service

Today’s consumer buying process is far more dynamic and interactive…..

* David C. Edelman, McKinsey, Dec 2010
18

Increasingly, customer acquisition is more nuanced.
Generating loyalty is the new marketing imperative

Social Analytics is the key to success in
Gain insights and increase positive
this new environment sentiment in social conversations

Accelerate re-purchase
through propensity models
Strengthen brand
preference
through advocacy


* David C. Edelman, McKinsey, Dec 2010
19

Looking ahead – The future must be intelligent
marketing that understands the interrelations of all
channels and media

e

web site, microsites,
Owned blog, Facebook page,
media etc

display ads, PPC, Google
sponsored content,
etc.
PR
Paid Customer Earned
Ads media media

Google
what your customers share and say
about you on twitter, Facebook
blogs and 20 | © 2012 IBM Corporation
the internet
20

A Social Analytics Application: IBM Cognos Consumer Insight

Create Relationships. Build Advocacy. Improve Loyalty.

Grow Your
Business

Enhance Your
Reputation

Improve Your
customer experience


21

Competitive analysis – Financial Services

Drilldowns quickly uncovered a very different sponsorship investment strategy between

Company sponsors many local event
throughout the year, while competitor
focuses one or two high visibility events


Product brand analysis – Consumer Products
Sophisticated analytics revealed which beverage attributes are being leveraged by the competition


Agenda



■ Customer analytics – 360 profile and lead generation (SMARC)
■ Spatio-temporal analytics for demand prediction (Microcosm)
■ Social Medical Discovery (SMD)
■ Voice of the Employee (SaND)



SMARC

Social-media Micro-segmentation and Real-time Correlation
Continuously analyze social media data from a wide range of sources, to construct
360-degree profiles of entities and leverage them in timely decision-making

Value Proposition
─ Construct a comprehensive view of entities of
interest (e.g., people, companies, products)
─ Identify actionable leads in real-time

From
─ 10-100’s of TBs of social media data from sources
such as Twitter, blogs, and forums

Using
─ Scalable “Data-at-Rest” and “Data-in-Motion”
analytics platform
─ Advanced analytics technologies (unstructured
data analytics, real-time, and predictive analytics)


SMARC

Sample Application – Real Time Lead Generation
Go for the Buying a Buying
best, DP- DSLR Thrza gr8 deal DSLR
2000 today ! on ZX-550 @
today!
the mall

Prior Social
Business Entity Extraction,
Transactions Fact Discovery,
Data
Intent & Sentiment
Influencers Intent
250M tweets/day Millions of tweets yield one
company-specific fact Customer ready to buy a
DSLR camera today,
Michael’s online friends offer lots of advice
possibly at a nearby mall

Text Analytics used to extract intent from Social
Media Married, Male, Spouse
Wifey’s birthday tomorrow, looking for a killer dslr Birthdate, Gift Type, Intent
to Purchase, Timeframe
Sarcasm, Maybe I should buy her that purple
Wishful Thinking Intent to Purchase,
roadster, while I’m at it. ;-) lol Gift Type?

Potential In NYC area this w/e, any good malls
Locations and Region & City Location,
nearby? Timeframe, Intent to Shop
Activity
 Resultant fact base contains billions of facts, and is incrementally updated
 Fact segmentation or clustering is rapid enough to drive a business decision 26 | © 2012 IBM Corporation

26

SMARC

Lead Generation Dashboard

Real-time product intents
enriched with consumer
attributes

Micro-segmentation of
product intents by
occupation Real-time tracking by
micro-segmentation

Micro-segmentation of
consumers by hobbies


SMARC

How Do We Create a User Profile?


SMARC

User Profiling Framework- Setting

logging targeting

Big Data Platform


SMARC

Going from Terms to Concepts

Important Relevant Wikipedia Chosen
terms Wikipedia titles/categories concepts
articles
1. Circuit
2. Radio
3. Electron
4. Detector Circuits Integrated circuits Electronics
5. Voltage Electronics
6. Line
Electronic music
7. Chip
Electronics
8. Capacitor
9. Input
10. Signal

Extract titles/Categories
from Wikipedia pages

Retrieve the most
relevant pages Choose the most
appropriate concepts

Microcosm

Spatio-temporal Analytics for Demand Prediction
■ What if you could find out immediately what’s happening in
specific geographies or communities?

■ Updated information ‘from the field’ can support decisions like:
─ Where should we send shipments?
─ What kind of promotions are needed? And where?
─ Which promotions were successful, which were not, and why?

■ Although input is available for analysis from internal data sources
like CRM, ERP, and more – it often involves delay

■ How can you better understand what’s going on now?


Microcosm
Examples
Recommended
Location specific tweets
Actions
Upbeat Charity event 09/08/11 in Redwood
city. Dance and donate to local charities Local Events Annual Charity Event
picking up very fast this
SylvieS Yes – I’m celebrating with dance year in Redwood city.
and donate. Join us 09.08.11 in Redwood
Ship more beverages to
BuyTheWaySuperMarket Sponsors for the the local supermarket
street party in Redwood City. Beer and
pizza 4 all. 09.08.11.

Local Promotion Cookies promotion very
GoodHousekeeping Get $1 off Nestle cookies
and milk with this coupon buy.x33/123/y8 popular in Sarasota.
Redirect shipment from
Care4Kids $1 off Nestle cookies when you St Petersburg to there.
buy milk. HURRY buy.x33/123/y8

Carl Nestle’s giving $1 off milk and cookies!
Get the coupon now buy.x33/123/y8

RestAssured I just wasted an evening having
tasteless Thai food – no spice or flavor @LAfoodies
Local Sentiment Negative sentiment about
a Thai restaurant in LA.
Zoe This restaurant is pathetic. Do not eat here
Propose new spices
** This place looks good but the food is terrible. I assortment.
ordered the chef’s special and was disappointed. 32 | © 2012 IBM Corporation

Social Medical

Social Medical Discovery
■ Social medical discovery
─ Analyzes medical and social relationships in the space of medical data
─ Searches over structured and unstructured information
– Textual search
– Faceted search, by age, medication name, genetic variation Patient

─ Ensures fast results, navigation, and exploration
Patient
Physician
■ Similar patients Patient
Patient
─ Discovers similar patients that share similar medical conditions
─ Creates social communities of similar patients

■ Evidence-based medical recommendations
─ Recommends medication for symptoms

─ Recommends alternative treatments 33 | © 2012 IBM Corporation

Social Medical

Example Use Case - Hemophilia

Discover Lineage

Find communities

Has Genetic Has genetic
symptom variation
variation
Hematuria
Treated by
Hemophilia
Has
Treated by disorder
“Hemophila”

Has Consumes
disorder Drug
Find physicians Consumes interaction

Find adverse drugs
Find Related Consumes
patients
Find medications


SaND

Voice of the Employee
■ 9 out of every 10 businesses using Web 2.0 technology are seeing
measurable business benefits from its use (McKinsey).
■ 41 percent of respondents indicated that they have already
implemented an enterprise social software solution (IDC)

■ IBM as a leading example ■ Use Cases
─ Over 400K employee profiles ─ Recommending relevant content
─ Over 1M bookmarks with and people
over 3M tags ─ Locating experts, influencers, and
─ Over 250K members in over central individuals
30K communities ─ Tracking trends and sentiment
─ Over 100K shared files and ─ Revealing information flow with
100K blog posts customers and partners
─ New event every 5 seconds
in the activity stream
McKinsey Quarterly, "How companies are benefiting from Web 2.0: McKinsey Global Survey Results" 2009

. IDC White Paper Sponsored by IBM, Becoming a Social Business: The IBM Story, Doc.#226706, January 2011. 35 | © 2012 IBM Corporation

SaND

Example Use Case: Social Analytics for the Sales force
■ Deliver accurate and highly relevant recommendations to help
the sales organization most effectively close an opportunity:
─ Find experts – who is top seller, who knows key people from customer
─ Identify similar opportunities – sales opportunities, previous
engagements with customer
─ Locating valuable assets that will maximize their chances of success
─ Business Intelligence - Trends regarding a given industry, competitive
products
─ Example:
Top 25 people
related to large
car manufacturer


SaND

SaND Streams – Sales Force Examples


Agenda



■ Social Analytics innovation activities in IBM Research



IBM’s Big Data Platform
Marketing

IBM Big Data Client and Partner IBM Unica
Solutions Solutions
Content
Big Data Accelerators Analytics
ECM
Text Statistic Financial Geospatial Acoustic
s Business
Image/Video Mining Times Mathematic Analytics
Series al
Cognos & SPSS
Connectors Applications Blueprints

InforSphere Information Server
Warehouse
Appliance
Big Data Enterprise Engines IBM Netezza

Master Data
InfoSphere InfoSphere Management
Streams BigInsights InfoSphere MDM

Data Warehouse
Productivity Tools and Optimization InfoSphere
Warehouse
Workload Management Consumability and
and Optimization Management Tools Database

DB2

Open Source Foundation Components Data Growth
Management
Eclipse Oozie Hadoop HBase Pig Lucene Jaql InfoSphere Optim

39

IBM Cognos Consumer Insight
Business Drivers
Competitive Analysis Corporate Reputation Customer Care

Campaign Effectiveness Product Insight

Product Capabilities
Source Areas
COMPREHENSIVE SENTIMENT
FACEBOOK ANALYSIS
 Keyword Search  Dimensional Analysis
BLOGS  Dimensional  Filtering
Navigation  Voice
 Drill Through to
Content
DISCUSSION FORUMS

AFFINITY ANALYTICS EVOLVING TOPICS
TWITTER

 Relationship Tables  Relevant Topics
NEWSGROUPS  Relationship Matrix  Associated Themes
 Relationship Graph  Ranking and Volume

MULTILINGUAL


IBM Connections
Profiles Home page
Find the people you need See what's happening across your
social network
Communities
Work with people who share
common roles and expertise Social Analytics
Discover who and what you don’t know
Files via recommendations
Post, share, and discover documents,
presentations, images, and more
Micro-blogging
Wikis Reach out for help your social network
Create web content together

Activities Bookmarks
Organize your work and tap your Save, share, and discover bookmarks
professional network

Forums Blogs
Exchange ideas with, and benefit from Present your own ideas, and learn
the expertise of others from others

Questions?

?
Aya Soffer
Email: AYAS@il.ibm.com
Twitter: @asoffer

?
LinkedIn: Aya Soffer

Mark Heid

? Email:
Twitter:
mheid@us.ibm.com
@mheid
LinkedIn: Mark Heid


Additional Information

Cognos Consumer Insight
http://www-01.ibm.com/software/analytics/cognos/analytic-applications/consumer-insight/

Social Analytics – Overview Interview on YouTube
http://www.youtube.com/watch?v=hjlwcXJaCWI



44

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