When size matters Is social media data really that BIG

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Insights into business applications of social analytics.

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When size matters Is social media data really that BIG

  1. 1. When size matters:is social media data really that BIG?Olha BondarenkoSocial Media Architect | Philips IT | March 2013
  2. 2. Olha Bondarenko, Social Media Architect@Philips IT Olha Bondarenko | Social Media architect | Philips IT | March 2013
  3. 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. 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 objectivesImage: office.microsoft.com Olha Bondarenko | Social Media architect | Philips IT | March 2013 4
  5. 5. Socialmedia& bigdataImage: office.microsoft.com Olha Bondarenko | Social Media architect | Philips IT | March 2013 5
  6. 6. These impressivenumbers have tobe translated intobusinessopportunities &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. 7. What makes data BIG: IBM viewSource: 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. 8. Does social media data qualify as a big datasource? 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. 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 opportunitiesBased 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. 10. Social media data for business use: someexamples 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. 11. Example: social media data use @Dell http://www.slideshare.net/dellsocialmedia/idc-sadler-feb2012Dell converted an early 2005 social media crisis into a holistic strategy Olha Bondarenko | Social Media architect | Philips IT | March 2013 11
  12. 12. Socialdatatypes &theirapplicationsImage: office.microsoft.com Olha Bondarenko | Social Media architect | Philips IT | March 2013
  13. 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. 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. 15. Police uses linkage data to understand thestructure 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. 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.comPreventing “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. 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. 18. GE uses social media (geolocation) as one of thedata 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. 19. Dutch railway organization Prorail uses Twitter& geolocation to detect the snowfalls Images: office.microsoft.comhttp://blog.prorail.nl/twitcident-inzicht-in-sneeuwval-via-innovatieve-social-media-scan Olha Bondarenko | Social Media architect | Philips IT | March 2013 19
  20. 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. 21. A machine can’t fully understand human talk… yetImage: office.microsoft.com Olha Bondarenko | Social Media architect | Philips IT | March 2013 21
  22. 22. Example: text analysis of Amazon reviews byAttensity Source: Making Social Insights Actionable, An Attensity eBook Olha Bondarenko | Social Media architect | Philips IT | March 2013 22
  23. 23. Respecting privacy and obeying to legislations is of the outmost importance for Philips Olha Bondarenko | Social Media architect | Philips IT | March 2013 23Image: office.microsoft.com
  24. 24. Measuringsocial:the good,the bad& the ugly Olha Bondarenko | Social Media architect | Philips IT | March 2013Image: office.microsoft.com
  25. 25. The information value chain: making sense of chaos Image: office.microsoft.com Olha Bondarenko | Social Media architect | Philips IT | March 2013 25
  26. 26. Simple (numerical) metrics: measure the conversation “Share of voice” per competitor Mentions per media type Trend over time per media typeSource: http://www.salesforcemarketingcloud.com/products/social-listening Olha Bondarenko | Social Media architect | Philips IT | March 2013 26
  27. 27. Example: Listen to the whispers - a simpleanalysis leading to a great business outcome Source: Philips OneVoice Connect for GM&C, 2013Hackers start their conversation 24 hrs before the bad news hit mainstream Olha Bondarenko | Social Media architect | Philips IT | March 2013 27
  28. 28. Understanding the sentiment of a conversation is important but may appear more difficult and less meaningful than one hopes neutralImage: office.microsoft.com Olha Bondarenko | Social Media architect | Philips IT | March 2013 28
  29. 29. Certain topics, such as elections, render highvolume of emotional conversationSource: Image courtesy of Clive Roach, through HootsuiteOther “speculative” metrics examples: recommendation, purchase intent Olha Bondarenko | Social Media architect | Philips IT | March 2013 29
  30. 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- dependentScreenshot from: http://twittercounter.com/pages/100 Olha Bondarenko | Social Media architect | Philips IT | March 2013 30
  31. 31. Complex combinatory metrics: Synthesio SocialReputation Score Source: Synthesio Olha Bondarenko | Social Media architect | Philips IT | March 2013 31
  32. 32. Seeing the future through social: predicting fluspread, 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. 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. 34. Olha Bondarenko | Social Media architect | Philips IT | March 2013 34

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