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HOW TO USE COHORTS OF GOOGLE ANALYTICS

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Understanding the behavior of your users is a necessary element in any marketing effort. The means to this is being critical to the sets or even subsets of your audience. The reaction of a certain group of audience with respect to a particular ad is not the same with that of others. This is to this point that cohort is necessary. A cohort is defined as a group of users who share common characteristics.

A cohort analysis application of Google Analytics is a very powerful tool that lets you isolate and analyze cohort behavior. With this, you can understand the behavior of component groups of users apart from that of the total population in general. With the use of this application, you can see the consistence, improvement or deterioration across cohorts. Of course, having cohort analysis report, you will be able to retain, engage and/or acquire users. Also, you will be able to know the response to your short-term marketing efforts. This is so exciting especially in cases where you are running campaigns as a holiday approaches.

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HOW TO USE COHORTS OF GOOGLE ANALYTICS

  1. 1. How to use COHORTS of Google Analytics
  2. 2. Do you want to understand the behavior of your audience?
  3. 3. Then, you need to understand COHORTS.
  4. 4. You must use COHORTS in your business.
  5. 5. You need to keep track with user’s behavior.
  6. 6. Why do you need to do this?
  7. 7. It can make or break your strategy.
  8. 8. It widens your imagination to be more creative.
  9. 9. So, what is all about COHORT then?
  10. 10. A COHORT is a group of users.
  11. 11. These users share a common characteristic.
  12. 12. For better understanding, here is an example.
  13. 13. The same cohorts are users with the same acquisition date.
  14. 14. Cohort Analysis report lets you isolate cohort behavior.
  15. 15. It also lets you analyze cohort behavior.
  16. 16. Cohort Analysis report is available for properties using Universal Analytics.
  17. 17. No changes to the tracking code are necessary.
  18. 18. To see cohort data, you must do these steps:
  19. 19. Sign in to Google Analytics
  20. 20. Type your email ad, and then, click NEXT.
  21. 21. Use one account for all Google transactions.
  22. 22. To facilitate all your activities very easily
  23. 23. To save your time for other meaningful outputs
  24. 24. Type your password and click SIGN IN.
  25. 25. Your password must be easy to remember.
  26. 26. Combination of letters, numbers, and symbols is encouraged.
  27. 27. You are then navigated to your view.
  28. 28. You can see HOME, REPORTING, CUSTOMIZATION and ADMIN.
  29. 29. This time, select the reporting tab.
  30. 30. Select and click it.
  31. 31. This time, you select the audience tab.
  32. 32. Select and click it.
  33. 33. Select COHORT ANALYSIS from the report navigation.
  34. 34. Select and click it.
  35. 35. Cohort data can be used in so many ways.
  36. 36. First, you can examine individual cohorts.
  37. 37. To gauge response to short-term marketing efforts.
  38. 38. You can see data of each day.
  39. 39. You can see the changes in users’ behavior and performance.
  40. 40. It can be day to day data.
  41. 41. It can be week to week data.
  42. 42. It can be month to month data.
  43. 43. Scroll it down and choose the range.
  44. 44. Organize users into groups based on shared characteristics.
  45. 45. An example of shared characteristics is acquisition date.
  46. 46. Click and see who interacts with your content.
  47. 47. Then, you can examine the behavior of groups.
  48. 48. Metrics like User Retention can be used.
  49. 49. Scroll down, and choose what metrics you want to evaluate.
  50. 50. How should we be able to interpret the data?
  51. 51. For better understanding, a report configured is given.
  52. 52. Acquisition Date Cohorts by the User Retention metric
  53. 53. Let us talk about charts first.
  54. 54. It shows the cumulative metric values for all cohorts.
  55. 55. This can be done by default.
  56. 56. Use N selected menu to select a cumulative chart line/s.
  57. 57. You can use this to compare individual cohorts.
  58. 58. N selected menu means the metrics you want to evaluate.
  59. 59. Choose from these metrics what data you want to evaluate.
  60. 60. Let’s go to how columns and rows are used.
  61. 61. This is a row. This is a column.
  62. 62. The first column identifies the cohorts.
  63. 63. It also identifies the number of users in each cohort.
  64. 64. The rest of the columns reflect the time increments.
  65. 65. This depends on the COHORT SIZE chosen.
  66. 66. For better understanding, here is an example.
  67. 67. The dimension that characterizes the cohorts is Acquisition date.
  68. 68. This column lists the acquisition date for each cohort.
  69. 69. The number of users acquired during that time frame is also shown.
  70. 70. The first row shows the total metric value.
  71. 71. These values are for all cohorts for each column.
  72. 72. The other rows shows the values for the individual cohorts.
  73. 73. For better understanding, here is an example.
  74. 74. The metric is Pageviews and the columns are daily data.
  75. 75. The first row shows the total pageviews for the day.
  76. 76. What is the importance of a cell?
  77. 77. This is a cell.
  78. 78. You could see cells for time increments.
  79. 79. It holds 0 to 12 relevant metric values.
  80. 80. Think that you are using the Pageviews metric.
  81. 81. Each cell contains the number of pageviews.
  82. 82. Pageviews are per cohort per time element.
  83. 83. What will happen if you apply other segments?
  84. 84. Data for each segment is displayed in a separate table.
  85. 85. Scroll it down, and see the list.
  86. 86. Choose to a maximum of 4 segments.
  87. 87. Report is user-based if the segment is session-based.
  88. 88. You can really get unexpected results.
  89. 89. Results do not include 100% of users on day o.
  90. 90. Here is the fact in knowing micro trends.
  91. 91. It gives you a more realistic picture of your business.
  92. 92. The benefits in comparing the values in a single column?
  93. 93. You’ll know if there’s a consistent behavior among your cohorts
  94. 94. You can see whether performance improves or deteriorates.
  95. 95. What is the point of knowing users’ disengagement behavior?
  96. 96. Common points of attrition can be easily remedied.
  97. 97. Devise new strategy to compensate for unavoidable attrition.
  98. 98. Thank you for watching!

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