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The Future of Social Intelligence - Extracting the Gold from Social Media #smm2011 Toronto


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Companies are just beginning to grasp the true power of social data. The ability to collect feedback without the need for costly market research studies, surveys, and focus groups is a relatively new prospect. But as brands have started measuring, many sense that they could (and should) be doing much more with the abundant data at their finger tips. Simply collecting data is not enough. To remain competitive, marketers must fully realize the breadth and depth of knowledge and insights they can gain from online conversations.

Scott Briggs discusses the state of social media intelligence today and where we are headed in the future. He outlines the advanced techniques that forward-thinking brands are using to move from simply collecting data to truly analyzing and drawing insights that are fueling smart business decisions.

The future of social intelligence is predictive, strategic, and unlike social measurement as you know it today. Are you ready?

Published in: Business, Technology
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The Future of Social Intelligence - Extracting the Gold from Social Media #smm2011 Toronto

  1. 1. The Future ofSocial Intelligence
  2. 2. About Me
  3. 3. SocialIntelligence is Today’s “Moneyball”Opportunity for Businesses
  4. 4. What is Social Intelligence? “The management and analysis of customerdata from social sources, used to activate and recalibrate marketing programs.” – Zach Hofer-Shall “Defining Social Intelligence”
  5. 5. My DefinitionThe Process of Using SocialMedia Data to Solve Business Problems
  6. 6. 
  7. 7. The Changing Consumer
  8. 8. Why use Social Media Data?
  9. 9. 9Reasons
  10. 10. Don’t be yesterday’s news.
  11. 11. Know when an activity occurred.
  12. 12. Get ALL of the answers.
  13. 13. Hear from more people, more often.
  14. 14. See the forest AND the trees.
  15. 15. Get the complete picture.
  16. 16. The more the merrier.
  17. 17. $avings
  18. 18. It’s the future.
  19. 19. The Current State
  20. 20. Typical Social Media Questions How is our brand How does sentiment in social link to my connecting to customer sat/ NPS score? customers’ lives? Which How can we be Who’s influencingexperiences more our brand? matter to innovative? customers (and which How can we be more What’s the ROI of our don’t)? responsive when things marketing activities? go wrong? What should we How do we drive reach stop doing? value & volume? How good are we at launching products & how What are our How should we can we get better? competitors engage? doing in social? 3 2
  21. 21. Social Media Drives many Business Functions
  22. 22. Everyone wants to talk about Measurement
  23. 23. Anything can be measured……Measuring and Analyzing aren’t the same thing
  24. 24. Metrics and Measurement Still Evolving“What do I do with all this data and what does it mean?”
  25. 25. We Need to Get Better at Solving SpecificProblems for Business Decision Makers
  26. 26. The Future of Social Intelligence
  27. 27. Cross – Discipline Nobody “owns” social it’s a businessactivity that solves a specific business problem.
  28. 28. Data IntegrationOrganizations will begin to integrate Social data with other data sources.
  29. 29. PredictiveSocial Media will be forward looking
  30. 30. Focused on OutcomesThe results will drive tangible business result, not just Social results.
  31. 31. Actionable Measuring Social Media will provide acompetitive advantage for organizations.
  32. 32. Tied to Corporate ResultsSocial Media metrics will be measured on the corporate KPI scorecard.
  33. 33. Two ExamplesSocial Intelligence Providing a Competitive Advantage
  34. 34. Multi-National CPG Needs to better Target Content for a Website
  35. 35. • Creating a non-branded website aimed at mothers with school age children• Goal is to identify the top family-minded female social media users in the UK• Facilitate sharing of product information• Want to drive trust of key brands• Want to engage for trials of new brands• Want to always provide the most relevant, targeted content
  36. 36. The Social Media Research Methodology Content Social data set Report development Refresh social Report Content data set developmentVirtual Social Media Data Analytics: Refresh social Contentethnography: Measurement: Identifying and data set Report developmentDiscovery & Theme extracting alearning validation to target data set ‘define’ target demographic On-going tracking cycle
  37. 37. Virtual EthnographyIdentify how mothersinteract on-line
  38. 38. Mothers Play Many Roles Confidant Nurse Event Friend plannerTechnology user & Activist adviser Mothers with Financial school age Wife manager children Employer Cleaner Family Teacher archivist Adviser Cook
  39. 39. Social Data Analysis Identify • Collect Social Media conversations for the themes created in the research phase • Create a “conversation matrix” to segment your data set by categories and themes • Examine and quantify what is important and relevant to the target audience • Analyze data by conversation, domain,Data Analytics:Identifying and and author within each categoryextracting a • Determined by your goals and objectivestarget data set
  40. 40. Analytics and MeasurementAuthor Influence – Relevant Influence Index (RII)• We created a unique measure of influence specific to mothers. We have called it the Relevant Influence Index (RII)• A score of 100 = average influence compared to all the other authors in the data set• If someone scores 200, they are twice as influential as the average author in our dataset, so if someone has a score of 5,000, they are extremely influential to your target audience and 50 times more influential than the average• The index is based on three things: 1. Volume of posts containing relevant content (i.e. from the conversation matrix) 2. Relevance of content (number of family taxonomy words contained in posts) – we call this NET FAMILY SCORE 3. Reach within the community – number of followers or responses to / comments on forum posts or blog entries
  41. 41. Analytics and MeasurementTheme Relevance Index (TRI)• We created a unique measure to track changes in themes over time, we it call it the Theme Relevance Index (TRI).• Using the theme categories developed in the conversation matrix we can track changes in theme volume and sentiment over time. We can see changing moods on a weekly/monthly basis based on the index score of each category.• A score of 100 = average compared to all categories in the data set. A score of 200 indicates that theme is twice as relevant as the average theme in our dataset.• The index is based on three main elements: 1. Volume of posts containing relevant content for each category (i.e. from the conversation matrix) 2. Sentiment of the each category 3. Reach of conversation within the theme• This data is then tracked weekly and monthly to measure change in attitudes and themes of our target audience
  42. 42. Measurement Framework ActSocial data set Benchmark Report Visualize • Determine the business outcome up front • From the data, develop standard measures andRefresh social Visualize metrics that explain yourdata set Report business outcome • If comparing or tracking over time we frequently will create a measurementRefresh social index Visualizedata set Report • Determine the best way to visualize and present this data for your audience • Automate the process of updating the On-going tracking cycle measurements
  43. 43. Experience Index
  44. 44. Enterprise Technology Company Needs to Understand how Consumers Experience New Products
  45. 45. • Goal was to drive greater uptake of new products to Enterprise Clients• Did not have a clear picture of how users experienced new product releases• Current models work well to predict purchase, but are costly and time consuming• Need more “in the moment” data for decisions during a release cycle
  46. 46. Research to understand the customer journey Identified 30+ Customer Experience Stages
  47. 47. Using the Customer Experience Methodology we created 3 Data Sets Traditional Survey Social Media Conversations of Participants Broad Social Media Search
  48. 48. Modeled the Data Sets
  49. 49. Results indicate the Social Data Model performed similar to the Survey Data Model
  50. 50. The Metric Calculation:
  51. 51. 
  52. 52. Scott BriggsSr. Director, Social Strategy and InsightsAlterian, 312 884