1. IBM Social Media Analytics 1.2
A Big Data Application
Presenter Dillip Kumar Majhi –Bigdata And Social Analytics Solution Architect

2. Agenda
 The scope of social media analytics
 Demo
 IBM Social Media Analytics: Architecture and Framework
 Filtering the noise: configuring relevant social media analytics
 A deeper look at some of SMA‘s built-in analytics capabilities
2
 A deeper look at some of SMA‘s built-in analytics capabilities
 No silos: Integrating Social into a 360 degree customer view
 Our successful journey to „Application as a Service“

3. “Social Business” – more than just a facebook page
Uses for social business1
Respond to
customer questions
Capture
customer data
78%
60%
79%
55%
3
33 3
Source: Institute for Business Value; Business of Social Business Study, 1 Based on responses from individuals having personal experience with customer-related social business
activities (n = 599)
Solicit customer
reviews and opinions
customer data
Identify and manage
key influencers
Today Next two years
79%
71%
44%
69%
37%
Cognos Consumer Insight 1.1
IBM Social Media Analytics 1.2
Cognos Consumer Insight 1.1
IBM Social Media Analytics 1.2

4. Organizations are moving beyond promotion towards driving
sales and support
Promote events/
marketing campaigns
Generate sales leads
and revenue
83%
71%
74%
51%
4
4
Provide product and
services support
Sell products directly
to customers
Today Next two years
69%
46%
61%
35%
Source: Institute for Business Value; Business of Social Business Study, 1 Based on responses from individuals having personal experience with customer-related social business
activities (n = 599)
Cognos Consumer Insight 1.1
IBM Social Media Analytics 1.2

5. IBM Social Media Analytics (SMA) targets many Business Issues -
driving actions, not just listening
What are your
How can I identify sales
leads ?
Marketing
SalesAre my suppliers
getting a bad
reputation?
Supply ChainSupply Chain
5
What are your
questions?
How do
consumers feel
about our new
messages / ads?
What are emerging
customer questions to
prime our call center
agents with?
Customer Service
5
What features are our
customers asking for?
Product Development

6. A Social Media Analytics application requires more than
Analytics
Deliver results
to more than
one employee
Provide meaningful
Social Media Metrics
Take IT
out of the picture
for daily operation
6
Text Analytics
- Detect Brands, Products
- Sentiment
- Author Geo, Demographics,
Behavior Collection Analysis
- Detect emerging topics
in Social Media
Statistics
- Automatically discover
relationships& affinities
Influencer
Identification

7. Agenda
 The scope of social media analytics
 Demo
 IBM Social Media Analytics: Architecture and Framework
 Filtering the noise: configuring relevant social media analytics
 A deeper look at some of SMA‘s built-in analytics capabilities
7
 A deeper look at some of SMA‘s built-in analytics capabilities
 No silos: Integrating Social into a 360 degree customer view
 Our successful journey to „Application as a Service“

8. Demo Scenario: Addressing new customer segments for a grocery store
 Business problem: Imagine you‘re Wegmans...
 ...and you want to enhance your market positioning
around „healthy foods“
 Approach: Analyze competitors, as well as some key aspects of shopping experience in
8
 Approach: Analyze competitors, as well as some key aspects of shopping experience in
social media

9. Start: SMA Welcome Page
All your analysis
projects in one place
9
Save and share
configurations across
projectsLaunch the
relevant UI

10. SMA Reporting Application Dynamically select
analysis criteria
1
Guided
Navigation
according to
Social Media
Framework Individual KPIs

11. Share of Voice – Check the overall „Brand Health“
I (Wegmans) „lag“
behind my peers
in this space
1
Less positive
sentiment, compared
to peers
Certainly room for
improvement

12. Reach – what are the Top 10 sites where people talk?
Twitter? No surprise –
What‘s tripadvisor
doing here – and why
am I missing?
1
Twitter? No surprise –
let‘s focus on other
sources....

13. Proximity to a „Healthy Food“ store is seen as a plus:
The underlying data is always only
one click away
1
Start co-marketing activities with certain hotels to pull
„healthy food“ shoppers to nearby Wegmans locationsAction

14. Sanity check – are there certain aspects of the shopping
experience we should improve?
Narrow down to a
certain aspect
Positive/Negative
1
Positive/Negative
sentiment ratio
significantly worse
Product
recall
Store
Layout

15. Shaping my message: who‘s talking – and about what ?
1
More females talking
around „healthy food“
stores, but sizeable
number of men as well
Overall themes the
same, but with different
priority

16. Understanding what aspects actual shoppers talk about
Trader Joe‘s shoppers
significantly different
See „actual shoppers“
for further engagement
1

17. Evolving Topics – identify & react to the unexpected
1
Topics in social media
over time, automatically
identified by SMA
Action
Check supply chain to pro-actively
avoid this problem

18. Agenda
 The scope of social media analytics
 Demo
 IBM Social Media Analytics: Architecture and Framework
 Filtering the noise: configuring relevant social media analytics
 A deeper look at some of SMA‘s built-in analytics capabilities
1
 A deeper look at some of SMA‘s built-in analytics capabilities
 No silos: Integrating Social into a 360 degree customer view
 Our successful journey to „Application as a Service“

19. ReportingAdministration Analysis
Welcome Page
Project
Project
Project
Project
Security
Multi-
tenancy
SSO
1
19
Analytics Platform
Message boards
Blogs
News
Cognos 10.1.1Text Analytics
IBM BigInsights 1.3
Search
Index
RDBMS g DB
Twitter
Evolving Topics
Facebook
Reviews
Video
Project
Project
Security
E2E Orchestration
Influencer
Identification

20. SMA Analytics Pipeline – deeper dive
Fetched
Data
(Json)
Document Analysis
 Identify Concept mentions
 Detect Sentiment
 Extract Author Location,
Demographics, Behavior
Evolving Topics
 Topic detection
 Assignment of
Mentions to Topics
Analysis
Results
(CSV +
Json)
BigInsights Orchestrator Job definition
SMA Flowmanager Job definition
2
 Document Analysis & Evolving Topics are running in BigInsights
 Document Analysis: Jaql scripts for document preprocessing + BigInsights
text
analysis rule engine (actual text analysis rules are part of SMA)
 Evolving Topics: Jaql scripts for document pre/postprocessing +
Java algorithm for topic detection
 Processing phases triggered through a 2-level workflow:
BigInsights Orchestrator for steps within Hadoop, SMA „FlowManager“ for
E2E orchestration (e.g., including „data in + data out“ steps)
SMA Flowmanager Job definition

21. Whatever we do – our users must not need to care
2
Hadoop, DB2, Cognos,...
totally transparent to analysts
- they just work with
SMA Administration

22. Results delivered at the right time
 CCI 1.1 provided the capability to update social media content once per day
 Some use cases call for a higher update frequency:
– Identifying sales leads
– Monitoring of an ongoing campaign or event
– Identifying 1:1 customer engagement opportunities
 SMA 1.2 provides additional update frequencies
– every 20 minutes
– every 2 hours
2
– every 2 hours
 All trend reports support a breakdown on „hour“ level
 Create Cognos alerts for „author with Klout score > 80 expresses negative sentiment about
us“

23. Agenda
 The scope of social media analytics
 Demo
 IBM Social Media Analytics: Architecture and Framework
 Filtering the noise: configuring relevant social media analytics
 A deeper look at some of SMA‘s built-in analytics capabilities
2
 A deeper look at some of SMA‘s built-in analytics capabilities
 No silos: Integrating Social into a 360 degree customer view
 Our successful journey to „Application as a Service“

24. The challenge in Social Media....
OBI in the German DIY world OBI in the rest of the world
2
OBI in the German DIY world OBI in the rest of the world
Persil for Germans
Persil for the French

25. All Social
Media
Data
fetcher
Keyword QueriesConfigure
1
Our approach: a multi-level „relevance funnel“
Relevant Blog ,
Board , Video
2
Analysis
 Flexible Type/Concept
hierarchy
 Text Analysis Patterns
Analyze
2
Board , Video
entries…
Product X
Product y
Product Z

26. Configuration Experience
Word lists and
regular
expressions define
a particular
concept
2
„Types“ and „Concepts“ define the
scope of the analysis – anything from
brands to products to services to
events to customer touchpoints to...
Include terms „make up“
the concept
Exclude terms „rule out “
irrelevant meanings
Context terms describe
relevant contexts

27. Agenda
 The scope of social media analytics
 Demo
 IBM Social Media Analytics: Architecture and Framework
 Filtering the noise: configuring relevant social media analytics
 A deeper look at some of SMA‘s built-in analytics capabilities
2
 A deeper look at some of SMA‘s built-in analytics capabilities
 No silos: Integrating Social into a 360 degree customer view
 Our successful journey to „Application as a Service“

28. Approach: Multi-lingual, rule-based, deep natural language
processing
 All our analysis capabilities are provided for multiple languages and multiple data
sources
– There‘s value beyond English tweets
 SMA uses the BigInsights text analysis engine for base text processing, and runs
SMA‘s text analysis rule resources in this engine for „our“ capabilities
My Nikon D5000 doesn‘t work well in fuzzy light conditions. Text
[My] [Nikon] [D5000] [does] [n‘t] [work] [well] [in] [fuzzy] [light] [conditions] Tokens
Part-of-SpeechPP NP NP VAUX NEG VB ADV PREP ADJ NN NN
[My Nikon D5000] [doesn‘t work well] [in fuzzy light conditions]. Syntax Analysis
[My Nikon D5000] doesn‘t work well in fuzzy light conditions. Behavior
[My Nikon D5000 doesn‘t work well] in fuzzy light conditions. Sentiment
BigInsights
SMA

29. Identifying author behavior in English, German, Spanish, French
 Users of a certain product or service
– What product features are relevant for them?
 Recommenders
– E.g., authors mentioning „you should use X“
 Detractors
– e.g. authors mentioning „stay away from X“
2
e.g. authors mentioning „stay away from X“
 Prospective users
– Potential sales leads for 1:1 engagement
– Identify sites where prospective users congregate

30. SMA as a service
 Hosted on SmartCloud Enterprise+
 Every customer has their own SMA deployment
 SLA: maximum of 2 days between „custom places order“ and „customer
receives URL to their SMA welcome page“
 Pricing according to the number of social media documents a customer
3
Pricing according to the number of social media documents a customer
retrieves per month
 Besides the user interfaces, customers can also access the SMA Social
Warehouse to integrate SMA data into their local business processes
– Through ODBC over SSL

31. Summary
 IBM Social Media Analytics targets multiple use cases in marketing, sales, PR,
customer service and product development
– Our Social Media Framework helps to map the right KPIs to a particular use case
 IBM Social Media Analytics is an integrated analytic application, harnessing „best
of breed“ IBM products
– Using the IBM Big Data platform for content processing
– Easy access to insights through Social Media Warehouse and Cognos BI
– Optimized data access for predictive analytics
3
– Optimized data access for predictive analytics
– Sentiment detection in English, French, German, Spanish, Dutch and Chinese
(Simplified and Traditional)
– Extracting Geographic, Demographic and Behavioral data for Social Media Authors in
English, French, German and Spanish
 „Becoming SaaS“ did not only change the way we do installation: it changed our
mindset on things like „performance“, „ease of maintenance“, „migration to new
versions“,... (and will continue to do so)

32. To find out more...
 External:
http://www-01.ibm.com/software/analytics/solutions/customer-analytics/social-media-analytics/
 Product videos (tech, not marketing) – also external
http://ibmtvdemo.edgesuite.net/software/analytics/cognos/videos/HTVs/sma-1-2/index.html
 „Sales Kit“ with Demos, Resources,...
3
 „Sales Kit“ with Demos, Resources,...
https://w3-03.sso.ibm.com/software/xl/portal/content?synKey=Q420240R36382M68#overview
 Integrating SMA data with BI and Predictive Analytics
http://www-01.ibm.com/support/docview.wss?uid=swg27038638

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