Social monitoring bootcamp Bogota, Colobmia


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I gave a workshop at #congressosm in Bogota on October 31st, 2013 covering ways to access monitoring technologies and approaches.

Published in: Social Media, Business, Technology
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Social monitoring bootcamp Bogota, Colobmia

  1. 1. Monitoring Bootcamp Bogota 10/31/13 Marshall Sponder WebMetricsGuru Inc.
  2. 2. Monitoring Boot camp Bogota 10/31/13 Marshall Sponder WebMetricsGuru Inc.
  3. 3. WebMetricsGuru INC.
  4. 4. Some of the companies I have worked with IT/Unix SEO /Web Analytics CORPORATE MKG /PR ANAL
  5. 5. Social Media has several use cases Care of Gary Angel – E&Y
  6. 6. Different tools are needed for different situations Operational Metrics Listening & Influence Categorization Advanced NLP Analysis Customer Support Product & Customer Research Public Relations Uses of Social Social CRM Customer Data Integration Campaigns Communities Listening & Web Analytics Engagement & Attrition Care of Gary Angel – E&Y
  7. 7. Matching platforms to meet the need • • • • • • • • • NM Incite Radian6 Brandwatch Sysomos MAP/Heartbeat Clarabridge SAS In-Community Tools Recorded Future Momentfeed (Geo-location) [Customer Integration] [Listening and Influence] [Listening and Influence] [Listening and Influence] [Advanced NLP] [Advanced NLP] [Engagement & Attention] [Advanced NLP] [Customer Integration]
  8. 8. Understanding the situation makes choices of platform tools much easier Consumer Research PR Monitoring & Support Social Campaigns Listening for Insights Listening and Engagement Automating of the engagement Social Media Coverage Traditional Media Coverage Workflow NLP (machine learning) Influencer Identification Operational Metrics Rich Categorization Topic Categorization Low-Latency Care of Gary Angel – E&Y
  9. 9. Identify right use cases for your situation Consumer Sentiment • How do our customers perceive us? • What are our brand strengths? • What drives consumer choice? PR Effectiveness • What Key Influencers Think • Have we shaped their Message • Can we talk to them directly Social Campaign Effectiveness • Are our customers engaged • Have we sold product • Did we drive PII and Site Traffic
  10. 10. Avoid Redundancy Care of Gary Angel – Full Service Care of Gary Angel – E&Y
  11. 11. Identify Internal Stakeholders and Platforms
  12. 12. 4 Types of Platforms
  13. 13. Platform Definitions • Self serve – etc. Brandwatch, Radian6, Sysomos, • Full service – Synthesio • Hybrid – Additional Reporting included with Self Serve. • Internal – Some companies build their own listening and analytics platforms for internal/private use.
  14. 14. Social Intelligence – Making sense of Social Media Messages
  15. 15. Social Scoring – Analyze social profiles and organize them in your own unique way, hopefully to be actionable.
  16. 16. Social Marketing Management – Build your Brand through customer interactions
  17. 17. Analytics – Campaign performance and Industry benchmarking
  18. 18. Mix of different platform types and service models in the social marketing space
  19. 19. At least Four Levels of Social Media Maturity
  20. 20. First Level: Monitoring Radian6 / Sysomos good examples of “monitoring Function” in SMM.
  21. 21. Example of monitoring – River of News Manual, labor intensive, subjective, not scalable, mostly a “news feed”.
  22. 22. Second Level: Online Research
  23. 23. Example of Market Research 1 Speed Style Hardware 0.5 Screen Res. Form Factor Media Integration Gameplay Use Apps OS 0 0 500 1,000 Connect 1,500 Screen Size -0.5 Price Reliability -1 Care of Gary Angel – E&Y 2,000
  24. 24. Third Level: Social Targeting
  25. 25. Example of Social Targeting Care of The New York Times
  26. 26. Fourth LevelCollaboration
  27. 27. Example of Collaboration / Social CRM
  28. 28. Mature Organizations get most from their Social Investments
  29. 29. Aside from Social Platforms to analyze Social Media, media channels are monetized in different ways.
  30. 30. Capturing Social Data is easier to do for some industry verticals than others
  31. 31. Platform Challenges
  32. 32. Inadequate query length size limits
  33. 33. Geo-location is often not specified or too broad to be helpful
  34. 34. Limited options to sub segment data
  35. 35. Boolean Queries impose limitations on monitoring accuracy
  36. 36. Language Support Issues
  37. 37. Interoperability issues
  38. 38. Immature Frameworks
  39. 39. Aggregators supplying most social data introduce data quality/latency issues
  40. 40. Becoming Strategic
  41. 41. Need a Plan
  42. 42. Example Plan
  43. 43. Typical Business Goals (Business Objectives) Business Goal Target 1. Increase Market Share by X% (this/next Y/Q) 2. Increase Business Income/Profit by X% (this/next Y/Q) 3. Save X% of our (monthly/quarterly) spent (this/next Y/Q) 4. Improve Productivity by X% (this/next Y/Q) 5. Improve Services provided by X% (this/next Y/Q) 6. Increase Company Profit by X% (this/next Y/Q) 7. Improve Team Productivity by X% (this/next Y/Q) 8. Improve/increase worker productivity by X% (this/next Y/Q) 9. Open New Offices (#) (this/next Y/Q) 10.Find/Create New Business Opportunities (#) (this/next Y/Q) 11.Increase Sales Bookings by (#) (this/next Y/Q) 12.What are the sales drivers & Incentives (this/next Y/Q) 13.What are your sales drivers & Incentives? (this/next Y/Q) 14.How and where to do we generate leads (#/%)? (this/next Y/Q)
  44. 44. Set Realistic measures and thresholds (DSS) • What Measures do you want to track? • What Decisions would you make differently if the one of the measures was surprisingly high or low? • What is the threshold of the measure? In other words, at what point if the value was exceeded or dipped would an alternative action take place? Source: Douglas Hubbard - The Pulse
  45. 45. Frameworks are need to create context in social data – often this has to be assigned by humans though machine learning is improving
  46. 46. Business Metrics are much more useful than channel and program metrics (micro conversions) but are harder to formulate and customize
  47. 47. Previous Business Investment/ Size Time Spent – Data Cleaning Customization Required Determining Platform Investment
  48. 48. Big Data is causing profound changes Structured 1950’s 1960’s 1970’s Unstructured 1980’s 1990’s 2000-2010 2011-2020
  49. 49. We need to learn ways to organize information in a useful way Offline WOM Search Social Data Hybrid email Survey Web Intelligence POS CRM UV Data Unified Information
  50. 50. Media Channels often need their own Analytics to best understand the impact of media efforts
  51. 51. Clouds are still maturing and may not suit all businesses or use cases
  52. 52. Salesforce, Oracle, Adobe and Microsoft have all wagered that marketing, sales and social clouds could solve many of the tougher marketing analytics issues organizations have
  53. 53. Unstructured Data is Growing much faster than structured data 1950’s 1960’s 1970’s 1980’s 1990’s 2000-2010 2011-2020
  54. 54. Twitter explains how Chris Hadfield went viral
  55. 55. Understanding how social media spreads has become a major interest as well as the subject of a new course @Rutgers Facegroup » Twitter Video Virality - Chris Hadfield
  56. 56. Rutgers University & Unruly partnering to create a course about the details around Creating Viral Media (using Big Data) Launching late 2013
  57. 57. Workshop Exercises 1. Analyzing CongresoSM using Social Media Analytics – pick 3 metrics to track Metric 1 Metric 2 Metric 3 Based on the Metrics you choose – what do you think your measurement goal is? What platforms are best to use to track the conference based on the goal (s) expressed? Any special considerations that need to be taken into account with this situation? How long would you track the conference (days/weeks months before/after)?
  58. 58. Workshop Exercises 2. What would be a business metric for Exposure? Engagement? ? ?
  59. 59. Workshop Exercises 3. How do you determine content has gone viral? Viral Metric 1 Viral Metric 2 Viral Metric 3
  60. 60. Thank You!
  61. 61. ¡Gracias!