Web Analytics Value Proposition For Executives

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Web Analytics Value Proposition For Executives

  1. 1. WEB ANALYTICS VALUE PROPOSITION FOR EXECUTIVES The case for data driven website decision making Monday, June 1, 2009
  2. 2. Gut or Data? Monday, June 1, 2009
  3. 3. Gut or Data?  How does your organization make website decisions? Monday, June 1, 2009
  4. 4. Gut or Data?  How does your organization make website decisions?  Gut or Data? Monday, June 1, 2009
  5. 5. Gut or Data?  How does your organization make website decisions? Non-data based  Gut or Data? No good data decisions to be available made Insufficient Lack of analytical skills analytical talent in employees Multiple versions of the “truth” Monday, June 1, 2009
  6. 6. Research says… Source: Quantitative Acenture Online Survey, July 2008 https://www.accenture.com/Global/Technology/Information_Mgmt/Information_Mgmt_Services/R_and_I/SurveyAchieved.htm Monday, June 1, 2009
  7. 7. Research says…  Accenture surveyed more than 250 executives in July 2008 about their companies' use of and investment in business analytics to remain competitive. Source: Quantitative Acenture Online Survey, July 2008 https://www.accenture.com/Global/Technology/Information_Mgmt/Information_Mgmt_Services/R_and_I/SurveyAchieved.htm Monday, June 1, 2009
  8. 8. Research says…  Accenture surveyed more than 250 executives in July 2008 about their companies' use of and investment in business analytics to remain competitive. Source: Quantitative Acenture Online Survey, July 2008 https://www.accenture.com/Global/Technology/Information_Mgmt/Information_Mgmt_Services/R_and_I/SurveyAchieved.htm Monday, June 1, 2009
  9. 9. Research says…  Accenture surveyed more than 250 executives in July 2008 about their companies' use of and investment in business analytics to remain competitive. Source: Quantitative Acenture Online Survey, July 2008 https://www.accenture.com/Global/Technology/Information_Mgmt/Information_Mgmt_Services/R_and_I/SurveyAchieved.htm Monday, June 1, 2009
  10. 10. Research says…  Accenture surveyed more than 250 executives in July 2008 about their companies' use of and investment in business analytics to remain competitive.  Nearly half of major corporate decisions are based on the good 'ole gut. (And that’s only what they say) Source: Quantitative Acenture Online Survey, July 2008 https://www.accenture.com/Global/Technology/Information_Mgmt/Information_Mgmt_Services/R_and_I/SurveyAchieved.htm Monday, June 1, 2009
  11. 11. Why? Monday, June 1, 2009
  12. 12. Why?  61% - No good data available Monday, June 1, 2009
  13. 13. Why?  61% - No good data available  55% - Qualitative (emotional) factors Monday, June 1, 2009
  14. 14. Why?  61% - No good data available  55% - Qualitative (emotional) factors  23% - Insufficient quantitative skills in employees Monday, June 1, 2009
  15. 15. Why?  61% - No good data available  55% - Qualitative (emotional) factors  23% - Insufficient quantitative skills in employees  36% - Shortage of analytical talent Monday, June 1, 2009
  16. 16. Why?  61% - No good data No good data Non-data based decisions to be available available made  55% - Qualitative Insufficient (emotional) factors Lack of analytical talent analytical skills in employees  23% - Insufficient quantitative skills in employees  36% - Shortage of analytical talent Monday, June 1, 2009
  17. 17. Why?  61% - No good data No good data Non-data based decisions to be available available made  55% - Qualitative Insufficient (emotional) factors Lack of analytical talent analytical skills in employees  23% - Insufficient quantitative skills in Multiple employees versions of the “truth”  36% - Shortage of analytical talent Monday, June 1, 2009
  18. 18. Why?  61% - No good data No good data Non-data based decisions to be available available made  55% - Qualitative Insufficient (emotional) factors Lack of analytical talent analytical skills in employees  23% - Insufficient quantitative skills in Multiple It’s the way employees versions of the “truth” we’ve always done it  36% - Shortage of analytical talent Monday, June 1, 2009
  19. 19. So what? Monday, June 1, 2009
  20. 20. So what?  Nearly three-quarters (72 percent) of respondents say they are striving to increase their organization's analytics use. Two-thirds surveyed recognize their decision- making failings and want to reduce their dependency on their gut. Monday, June 1, 2009
  21. 21. So what?  Nearly three-quarters (72 percent) of respondents say they are striving to increase their organization's analytics use. Two-thirds surveyed recognize their decision- making failings and want to reduce their dependency on their gut.  Some key quotes from the research: Monday, June 1, 2009
  22. 22. So what?  Nearly three-quarters (72 percent) of respondents say they are striving to increase their organization's analytics use. Two-thirds surveyed recognize their decision- making failings and want to reduce their dependency on their gut.  Some key quotes from the research:  “There’s a strong concern over the future lack of analytical skilled resources.” Monday, June 1, 2009
  23. 23. So what?  Nearly three-quarters (72 percent) of respondents say they are striving to increase their organization's analytics use. Two-thirds surveyed recognize their decision- making failings and want to reduce their dependency on their gut.  Some key quotes from the research:  “There’s a strong concern over the future lack of analytical skilled resources.”  quot;We need to move from a mass-market approach to a more segmented, targeted approach which requires significantly more analysis.” Monday, June 1, 2009
  24. 24. So what?  Nearly three-quarters (72 percent) of respondents say they are striving to increase their organization's analytics use. Two-thirds surveyed recognize their decision- making failings and want to reduce their dependency on their gut.  Some key quotes from the research:  “There’s a strong concern over the future lack of analytical skilled resources.”  quot;We need to move from a mass-market approach to a more segmented, targeted approach which requires significantly more analysis.”  quot;Companies can become mired in the past, i.e., ‘that’s the way we’ve always done business.’ Today’s marketplace and available technology requires the ability to revamp marketing and customer service strategies.” Monday, June 1, 2009
  25. 25. So why give up on your gut? Monday, June 1, 2009
  26. 26. So why give up on your gut?  To quickly react to changes in customer demand Monday, June 1, 2009
  27. 27. So why give up on your gut?  To quickly react to changes in customer demand  Increase sales Monday, June 1, 2009
  28. 28. So why give up on your gut?  To quickly react to changes in customer demand  Increase sales  Increase profit margin Monday, June 1, 2009
  29. 29. So why give up on your gut?  To quickly react to changes in customer demand  Increase sales  Increase profit margin  Increase customer loyalty and retention Monday, June 1, 2009
  30. 30. So why give up on your gut?  To quickly react to changes in customer demand  Increase sales  Increase profit margin  Increase customer loyalty and retention  Improve EBITDA Monday, June 1, 2009
  31. 31. So why give up on your gut?  To quickly react to changes in customer demand  Increase sales  Increase profit margin  Increase customer loyalty and retention  Improve EBITDA Measurement Monday, June 1, 2009
  32. 32. So why give up on your gut?  To quickly react to changes in customer demand  Increase sales  Increase profit margin  Increase customer loyalty and retention  Improve EBITDA Measurement Accountability Monday, June 1, 2009
  33. 33. So why give up on your gut?  To quickly react to changes in customer demand  Increase sales  Increase profit margin  Increase customer loyalty and retention  Improve EBITDA Measurement Accountability ROI Monday, June 1, 2009
  34. 34. Example Monday, June 1, 2009
  35. 35. Example  A January 2008 report from Aberdeen Group on retailers using “best in class” analytics tools and techniques increased Monday, June 1, 2009
  36. 36. Example  A January 2008 report from Aberdeen Group on retailers using “best in class” analytics tools and techniques increased  Average year-over-year same-store sales by 11.7 percent Monday, June 1, 2009
  37. 37. Example  A January 2008 report from Aberdeen Group on retailers using “best in class” analytics tools and techniques increased  Average year-over-year same-store sales by 11.7 percent  Average profit-margin by 9.3 percent Monday, June 1, 2009
  38. 38. Example  A January 2008 report from Aberdeen Group on retailers using “best in class” analytics tools and techniques increased  Average year-over-year same-store sales by 11.7 percent  Average profit-margin by 9.3 percent  Customer retention by 12.2 percent Monday, June 1, 2009
  39. 39. In short… Monday, June 1, 2009
  40. 40. In short…  Using analytics can help you Monday, June 1, 2009
  41. 41. In short…  Using analytics can help you  Understand your customers Monday, June 1, 2009
  42. 42. In short…  Using analytics can help you  Understand your customers  Quantify and improve marketing results Monday, June 1, 2009
  43. 43. In short…  Using analytics can help you  Understand your customers  Quantify and improve marketing results  Make better decisions Monday, June 1, 2009
  44. 44. In short…  Using analytics can help you  Understand your customers  Quantify and improve marketing results  Make better decisions  Increase EBITDA Monday, June 1, 2009
  45. 45. On Web Analytics Monday, June 1, 2009
  46. 46. On Web Analytics  In the April 2007 report quot;Web Analytics: The Crystal Ball of Customer Behavior,quot; Aberdeen found that 89% of Best-in-Class companies used, or planned to use, web analytics solutions as a method to measure corporate goals, such as improving the customer experience. Monday, June 1, 2009
  47. 47. On Web Analytics  In the April 2007 report quot;Web Analytics: The Crystal Ball of Customer Behavior,quot; Aberdeen found that 89% of Best-in-Class companies used, or planned to use, web analytics solutions as a method to measure corporate goals, such as improving the customer experience.  Of these top performing companies, 28% admitted that the data delivered by a web analytics solution was difficult to interpret. Monday, June 1, 2009
  48. 48. What about “subjective” stuff? Monday, June 1, 2009
  49. 49. What about “subjective” stuff? Monday, June 1, 2009
  50. 50. What about “subjective” stuff? Everything online is Monday, June 1, 2009
  51. 51. What about “subjective” stuff? Everything online is MEASURABLE Monday, June 1, 2009
  52. 52. Everything is Measurable Monday, June 1, 2009
  53. 53. Everything is Measurable  Example – Should I authorize my CMO to spend ½ million dollars on a 6 month branding campaign? Monday, June 1, 2009
  54. 54. Everything is Measurable  Example – Should I authorize my CMO to spend ½ million dollars on a 6 month branding campaign?  Traditional – Do campaign (or not) and then do a focus group before and after to see if your brand appeal increased Monday, June 1, 2009
  55. 55. Everything is Measurable  Example – Should I authorize my CMO to spend ½ million dollars on a 6 month branding campaign?  Traditional – Do campaign (or not) and then do a focus group before and after to see if your brand appeal increased  Answer – Yes, people are liking our brand more, or ooops, not. Monday, June 1, 2009
  56. 56. Everything is Measurable  Example – Should I authorize my CMO to spend ½ million dollars on a 6 month branding campaign?  Traditional – Do campaign (or not) and then do a focus group before and after to see if your brand appeal increased  Answer – Yes, people are liking our brand more, or ooops, not.  Problem – You don’t know until it’s over Monday, June 1, 2009
  57. 57. Everything is Measurable  Example – Should I authorize my CMO to spend ½ million dollars on a 6 month branding campaign?  Traditional – Do campaign (or not) and then do a focus group before and after to see if your brand appeal increased  Answer – Yes, people are liking our brand more, or ooops, not.  Problem – You don’t know until it’s over  The Web Analytics Way – Ongoing measurement of brand keywords typed in search engines and direct/bookmarks for people who arrive at your site. Monday, June 1, 2009
  58. 58. Everything is Measurable  Example – Should I authorize my CMO to spend ½ million dollars on a 6 month branding campaign?  Traditional – Do campaign (or not) and then do a focus group before and after to see if your brand appeal increased  Answer – Yes, people are liking our brand more, or ooops, not.  Problem – You don’t know until it’s over  The Web Analytics Way – Ongoing measurement of brand keywords typed in search engines and direct/bookmarks for people who arrive at your site.  Answer – Authorize two months, test and optimize the campaign, then when your “brand” index is increasing X% monthly, keep the spend going! Monday, June 1, 2009
  59. 59. Everything is Measurable  Example – Should I authorize my CMO to spend ½ million dollars on a 6 month branding campaign?  Traditional – Do campaign (or not) and then do a focus group before and after to see if your brand appeal increased  Answer – Yes, people are liking our brand more, or ooops, not.  Problem – You don’t know until it’s over  The Web Analytics Way – Ongoing measurement of brand keywords typed in search engines and direct/bookmarks for people who arrive at your site.  Answer – Authorize two months, test and optimize the campaign, then when your “brand” index is increasing X% monthly, keep the spend going!  You know while it’s going on and can adjust Monday, June 1, 2009
  60. 60. Ready to lose your gut? Monday, June 1, 2009
  61. 61. Ready to lose your gut?  Here’s how to get started Monday, June 1, 2009
  62. 62. Ready to lose your gut?  Here’s how to get started  Hire an experienced web analyst, or a geeky marketer with some analytics experience, or choose an interested geek internally and send them for training. Monday, June 1, 2009
  63. 63. Ready to lose your gut?  Here’s how to get started  Hire an experienced web analyst, or a geeky marketer with some analytics experience, or choose an interested geek internally and send them for training.  Invite said geek to every decision making meeting and ask for his/her applicable data. Monday, June 1, 2009
  64. 64. Ready to lose your gut?  Here’s how to get started  Hire an experienced web analyst, or a geeky marketer with some analytics experience, or choose an interested geek internally and send them for training.  Invite said geek to every decision making meeting and ask for his/her applicable data.  Listen to their data. Monday, June 1, 2009
  65. 65. Ready to lose your gut?  Here’s how to get started  Hire an experienced web analyst, or a geeky marketer with some analytics experience, or choose an interested geek internally and send them for training.  Invite said geek to every decision making meeting and ask for his/her applicable data.  Listen to their data.  Whenever you feel that tingle in you gut, ask your analytics person to prove it. Monday, June 1, 2009
  66. 66. Ready to lose your gut?  Here’s how to get started  Hire an experienced web analyst, or a geeky marketer with some analytics experience, or choose an interested geek internally and send them for training.  Invite said geek to every decision making meeting and ask for his/her applicable data.  Listen to their data.  Whenever you feel that tingle in you gut, ask your analytics person to prove it.  Enjoy your improved EBITDA Monday, June 1, 2009
  67. 67. Why a Web Analyst? Monday, June 1, 2009
  68. 68. Why a Web Analyst?  Aberdeen’s “Crystal Ball” report also identified the number one issue for organizations who are evaluating web analytics solutions: Monday, June 1, 2009
  69. 69. Why a Web Analyst?  Aberdeen’s “Crystal Ball” report also identified the number one issue for organizations who are evaluating web analytics solutions: “There is little direction from vendors on how to maximize the use of the data for better business decisions” Monday, June 1, 2009
  70. 70. Why a Web Analyst?  Aberdeen’s “Crystal Ball” report also identified the number one issue for organizations who are evaluating web analytics solutions: “There is little direction from vendors on how to maximize the use of the data for better business decisions” Monday, June 1, 2009
  71. 71. Why a Web Analyst?  Aberdeen’s “Crystal Ball” report also identified the number one issue for organizations who are evaluating web analytics solutions: “There is little direction from vendors on how to maximize the use of the data for better business decisions” Monday, June 1, 2009
  72. 72. Why a Web Analyst?  Aberdeen’s “Crystal Ball” report also identified the number one issue for organizations who are evaluating web analytics solutions: “There is little direction from vendors on how to maximize the use of the data for better business decisions” Monday, June 1, 2009
  73. 73. Why a Web Analyst? Monday, June 1, 2009
  74. 74. Why a Web Analyst? Monday, June 1, 2009
  75. 75. Why a Web Analyst? Monday, June 1, 2009
  76. 76. Why a Web Analyst? Monday, June 1, 2009
  77. 77. Why a Web Analyst? Monday, June 1, 2009
  78. 78. Why a Web Analyst? Monday, June 1, 2009
  79. 79. What you and your analyst should be doing… Monday, June 1, 2009
  80. 80. What you and your analyst should be doing…  Define Objectives Monday, June 1, 2009
  81. 81. What you and your analyst should be doing…  Define Objectives  Map Objectives to Site Monday, June 1, 2009
  82. 82. What you and your analyst should be doing…  Define Objectives  Map Objectives to Site  Look for Opportunities Monday, June 1, 2009
  83. 83. What you and your analyst should be doing…  Define Objectives  Map Objectives to Site  Look for Opportunities  Set Targets and Segment Audience Monday, June 1, 2009
  84. 84. What you and your analyst should be doing…  Define Objectives  Map Objectives to Site  Look for Opportunities  Set Targets and Segment Audience  Test the Change! Monday, June 1, 2009
  85. 85. What you and your analyst should be doing…  Define Objectives  Map Objectives to Site  Look for Opportunities  Set Targets and Segment Audience  Test the Change!  Measure Results & Optimize Monday, June 1, 2009
  86. 86. What you and your analyst should be doing…  Define Objectives  Map Objectives to Site  Look for Opportunities  Set Targets and Segment Audience  Test the Change! Repeat  Measure Results & Optimize Monday, June 1, 2009
  87. 87. What you and your analyst should be doing…  Define Objectives  Map Objectives to Site  Look for Opportunities Repeat  Set Targets and Segment Audience  Test the Change! Repeat  Measure Results & Optimize Monday, June 1, 2009
  88. 88. Thanks for your time! dan@webanalyticsbuzz.com, danlinton@gmail.com Monday, June 1, 2009
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