Insights into business applications of social analytics.

1. When size matters:
is social media data really that BIG?
Olha Bondarenko
Social Media Architect | Philips IT | March 2013

2. Olha Bondarenko, Social Media Architect
@Philips IT
Olha Bondarenko | Social Media architect | Philips IT | March 2013

3. Today
Social media & big data: what makes
it big and why using it?
Social media types of data and
applications for business
Measuring social: the good,
the bad and the ugly
Olha Bondarenko | Social Media architect | Philips IT | March 2013 3

4. Your takeaways
Understand what kind of data is available in social
media space and how it can be used
Think of relevant applications of data from social media
space for reaching your business objectives
Image: office.microsoft.com
Olha Bondarenko | Social Media architect | Philips IT | March 2013 4

5. Social
media
& big
data
Image: office.microsoft.com
Olha Bondarenko | Social Media architect | Philips IT | March 2013 5

6. These impressive
numbers have to
be translated into
business
opportunities &
revenues
Source: Big data: The next frontier for
innovation, competition, and
productivity
McKinsey Global Institute, May 2011
Olha Bondarenko | Social Media architect | Philips IT | March 2013 6

7. What makes data BIG: IBM view
Source: Analytics: The real-world use of big data, IBM Institute for Business Value, 2012
Olha Bondarenko | Social Media architect | Philips IT | March 2013 7

8. Does social media data qualify as a big data
source?
Respondents with active big data efforts were asked which platform
components are currently either in pilot or integrated into the
architecture. Each data point was collected independently. Total
respondents for each data point range from 297 to 351.
Source: Analytics: The real-world use of big data, IBM Institute for Business Value, 2012
Olha Bondarenko | Social Media architect | Philips IT | March 2013 8

9. What makes social media data big?
Social media data
Huge, but scalable in Needs effort to structure & Requires the business
relevant areas standardize model to adapt
Very high, but offers great
business opportunities
Based on:: Analytics: The real-world use of big data, IBM Institute for Business Value, 2012
Olha Bondarenko | Social Media architect | Philips IT | March 2013 9

10. Social media data for business use: some
examples
Social media data + Other data sources
Competitive intelligence
Innovation & co-creation
Influencers engagement
Issue prevention
Campaign evaluation
Product development
Crisis prevention
Customer journeys
Brand management
MI metrics
Olha Bondarenko | Social Media architect | Philips IT | March 2013 10

11. Example: social media data use @Dell
http://www.slideshare.net/dellsocialmedia/idc-sadler-feb2012
Dell converted an early 2005 social media crisis into a holistic strategy
Olha Bondarenko | Social Media architect | Philips IT | March 2013 11

12. Social
data
types &
their
applications
Image: office.microsoft.com
Olha Bondarenko | Social Media architect | Philips IT | March 2013

13. Three types of data available from social media
1. Linkage* 2. Profile 3. Message*
The linkage behavior of the Information about the Content published on various
network, important nodes, participants of the network, platforms, from 140-charater-
communities, links, evolving either provided by them or cryptic tweets to lengthy
regions* deduced opinion blogs
*Social Network Data Analytics. Charu C. Aggarwal, Ed. Springer Science+Business Media, LLC 2011 Chapter 1. An Introduction to Social Network Data Analytics, pp. 5, Images: office.microsoft.com
Olha Bondarenko | Social Media architect | Philips IT | March 2013 13

14. 1. Linkage data: the secrets of the net
1. Linkage* 2. Profile 3. Message*
The linkage behavior of the
network, important nodes,
communities, links, evolving
regions*
*Social Network Data Analytics. Charu C. Aggarwal, Ed. Springer Science+Business Media, LLC 2011 Chapter 1. An Introduction to Social Network Data Analytics, pp. 5, Images: office.microsoft.com
Olha Bondarenko | Social Media architect | Philips IT | March 2013 14

15. Police uses linkage data to understand the
structure of a gang & identify missing members
“ […] the social network analysis also
identified "six other vital players of which
Image: office.microsoft.com the police were unaware."
Sources: http://www.core77.com/blog/technology/visualizing_criminal_networks_to_help_police_solve_crime_22462.asp ,
http://www.zdnet.com/ten-examples-of-extracting-value-from-social-media-using-big-data-7000007192/#photo
Olha Bondarenko | Social Media architect | Philips IT | March 2013 15

16. Less exciting world of daily business, two
(anonymous) Forrester examples for linkage data
Increased chances to
cross-sell/upsell: A telco
taps into the Facebook
social groups to market
friends-and-family plans.
Image: office.microsoft.com
Preventing “chain” cancellations:
A credit card company retains
customers by understanding Image: office.microsoft.com
social relationships. Source: The Big Deal About Big Data For Customer Engagement
by Sanchit Gogia, Forrester, June 1, 2012 16
Olha Bondarenko | Social Media architect | Philips IT | March 2013

17. 2. Profile data: valuable, sensitive & uncertain
1. Linkage* 2. Profile 3. Message*
Information about the
participants of the network,
either provided by them or
deduced
*Social Network Data Analytics. Charu C. Aggarwal, Ed. Springer Science+Business Media, LLC 2011 Chapter 1. An Introduction to Social Network Data Analytics, pp. 5, Images: office.microsoft.com
Olha Bondarenko | Social Media architect | Philips IT | March 2013 17

18. GE uses social media (geolocation) as one of the
data sources to detect & locate power disruptions
Source: GE Grid IQ brosuer
http://www.zdnet.com/ten-examples-of-extracting-value-from-social-media-using-big-data-7000007192/#photo
Olha Bondarenko | Social Media architect | Philips IT | March 2013 18

19. Dutch railway organization Prorail uses Twitter
& geolocation to detect the snowfalls
Images: office.microsoft.com
http://blog.prorail.nl/twitcident-inzicht-in-sneeuwval-via-innovatieve-social-media-scan
Olha Bondarenko | Social Media architect | Philips IT | March 2013 19

20. 3. Message data: the needle in a haystack
1. Linkage* 2. Profile 3. Message*
Content published on various
platforms, from 140-charater-
cryptic tweets to lengthy
opinion blogs
*Social Network Data Analytics. Charu C. Aggarwal, Ed. Springer Science+Business Media, LLC 2011 Chapter 1. An Introduction to Social Network Data Analytics, pp. 5, Images: office.microsoft.com
Olha Bondarenko | Social Media architect | Philips IT | March 2013 20

21. A machine can’t
fully understand
human talk… yet
Image: office.microsoft.com
Olha Bondarenko | Social Media architect | Philips IT | March 2013 21

22. Example: text analysis of Amazon reviews by
Attensity
Source: Making Social Insights Actionable, An Attensity eBook
Olha Bondarenko | Social Media architect | Philips IT | March 2013 22

23. Respecting privacy and obeying to
legislations is of the outmost
importance for Philips
Olha Bondarenko | Social Media architect | Philips IT | March 2013 23
Image: office.microsoft.com

24. Measuring
social:
the good,
the bad
& the ugly Olha Bondarenko | Social Media architect | Philips IT | March 2013
Image: office.microsoft.com

25. The information value chain: making sense of chaos
Image: office.microsoft.com
Olha Bondarenko | Social Media architect | Philips IT | March 2013 25

26. Simple (numerical) metrics: measure the
conversation
“Share of voice” per competitor
Mentions per media type
Trend over time per media type
Source: http://www.salesforcemarketingcloud.com/products/social-listening
Olha Bondarenko | Social Media architect | Philips IT | March 2013 26

27. Example: Listen to the whispers - a simple
analysis leading to a great business outcome
Source: Philips OneVoice Connect for GM&C, 2013
Hackers start their conversation 24 hrs before the bad news hit mainstream
Olha Bondarenko | Social Media architect | Philips IT | March 2013 27

28. Understanding the
sentiment of
a conversation is
important but
may appear more
difficult and less
meaningful
than one hopes
neutral
Image: office.microsoft.com
Olha Bondarenko | Social Media architect | Philips IT | March 2013 28

29. Certain topics, such as elections, render high
volume of emotional conversation
Source: Image courtesy of Clive Roach, through Hootsuite
Other “speculative” metrics examples: recommendation, purchase intent
Olha Bondarenko | Social Media architect | Philips IT | March 2013 29

30. Influencers: having a focused impactful
conversation, especially in the B2B space
Common as well as
proprietary influence
scores exist
Identify the most
influential participants
of a conversation
Not as simple as just
counting followers or
friends
Subject- and time-
dependent
Screenshot from: http://twittercounter.com/pages/100
Olha Bondarenko | Social Media architect | Philips IT | March 2013 30

31. Complex combinatory metrics: Synthesio Social
Reputation Score
Source: Synthesio
Olha Bondarenko | Social Media architect | Philips IT | March 2013 31

32. Seeing the future through social: predicting flu
spread, movie tickets sales & stock market
4.4 million tweets
from 630,000 users
analyzed.
Claimed to predict
when healthy
people will fall sick
with 90% accuracy
up to eight days in
advance.
Source: http://www.newscientist.com/blogs/onepercent/2012/07/ai-predicts-when-youre-about-t.html
Olha Bondarenko | Social Media architect | Philips IT | March 2013 32

33. Your takeaways
Image: office.microsoft.com
• Understand what kind of data is available in social media
space and how it can be used
• Is social media data big? It may be!
• Three data types and a range of metrics exist
• The business value is indisputable; applications vary
• Think of relevant applications of data from social media
space for reaching your business objectives
• Use today’s examples for your inspiration
• Start exploring & connect to the team!
Olha Bondarenko | Social Media architect | Philips IT | March 2013 33

34. Olha Bondarenko | Social Media architect | Philips IT | March 2013 34