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.

1. How to use
COHORTS of
Google Analytics

2. Do you want to
understand the
behavior of your
audience?

3. Then, you need to
understand
COHORTS.

4. You must use
COHORTS in your
business.

5. You need to keep
track with user’s
behavior.

6. Why do you need to
do this?

7. It can make or break
your strategy.

8. It widens your
imagination to be
more creative.

9. So, what is all about
COHORT then?

10. A COHORT is a group
of users.

11. These users share a
common
characteristic.

12. For better
understanding, here
is an example.

13. The same cohorts are
users with the same
acquisition date.

14. Cohort Analysis
report lets you
isolate cohort
behavior.

15. It also lets you
analyze cohort
behavior.

16. Cohort Analysis
report is available for
properties using
Universal Analytics.

17. No changes to the
tracking code are
necessary.

18. To see cohort data,
you must do these
steps:

19. Sign in to Google
Analytics

20. Type your
email ad,
and then,
click NEXT.

21. Use one account for
all Google
transactions.

22. To facilitate all
your activities
very easily

23. To save your time
for other meaningful
outputs

24. Type
your
password
and click
SIGN IN.

25. Your password must
be easy to remember.

26. Combination of
letters, numbers, and
symbols is
encouraged.

27. You are then
navigated to your
view.

29. You can see HOME,
REPORTING,
CUSTOMIZATION
and ADMIN.

31. This time, select the
reporting tab.

32. Select and
click it.

33. This time, you
select the audience
tab.

34. Select and click it.

35. Select COHORT
ANALYSIS from the
report navigation.

36. Select and
click it.

37. Cohort data can be
used in so many
ways.

38. First, you can
examine individual
cohorts.

39. To gauge response
to short-term
marketing efforts.

40. You can see data of each day.

41. You can see the
changes in users’
behavior and
performance.

42. It can be day to day
data.

43. It can be week to
week data.

44. It can be month to
month data.

45. Scroll it down and
choose the range.

46. Organize users into
groups based on
shared characteristics.

47. An example of shared
characteristics is
acquisition date.

48. Click and see who
interacts with your
content.

49. Then, you can
examine the
behavior of groups.

50. Metrics like User
Retention can be
used.

51. Scroll down, and
choose what
metrics you
want to
evaluate.

52. How should we be
able to interpret
the data?

53. For better
understanding, a
report configured is
given.

54. Acquisition Date
Cohorts by the User
Retention metric

56. Let us talk about
charts first.

57. It shows the
cumulative metric
values for all cohorts.

58. This can be done by
default.

59. Use N selected menu
to select a
cumulative chart
line/s.

60. You can use this to
compare individual
cohorts.

61. N selected menu
means the metrics
you want to
evaluate.

62. Choose
from these
metrics
what data
you want to
evaluate.

63. Let’s go to how
columns and rows
are used.

64. This is a row.
This is a column.

65. The first column
identifies the
cohorts.

66. It also identifies the
number of users in
each cohort.

67. The rest of the
columns reflect the
time increments.

68. This depends on the
COHORT SIZE
chosen.

69. For better
understanding, here is
an example.

70. The dimension that
characterizes the
cohorts is Acquisition
date.

71. This column lists the
acquisition date for
each cohort.

72. The number of users
acquired during that
time frame is also
shown.

73. The first row
shows the total
metric value.

74. These values are for
all cohorts for each
column.

75. The other rows
shows the values for
the individual
cohorts.

76. For better
understanding, here
is an example.

77. The metric is
Pageviews and the
columns are daily
data.

78. The first row shows
the total pageviews
for the day.

79. What is the
importance of a cell?

80. This is a cell.

81. You could see cells
for time
increments.

82. It holds 0 to 12
relevant metric
values.

83. Think that you are
using the Pageviews
metric.

84. Each cell contains
the number of
pageviews.

85. Pageviews are per
cohort per time
element.

86. What will happen if
you apply other
segments?

87. Data for each
segment is displayed
in a separate table.

88. Scroll it down, and
see the list.

89. Choose to a
maximum of
4 segments.

91. Report is user-based
if the segment is
session-based.

92. You can really get
unexpected
results.

93. Results do not
include 100% of
users on day o.

94. Here is the fact in
knowing micro
trends.

95. It gives you a more
realistic picture of
your business.

96. The benefits in
comparing the values
in a single column?

97. You’ll know if there’s a
consistent behavior
among your cohorts

98. You can see whether
performance
improves or
deteriorates.

99. What is the point of
knowing users’
disengagement
behavior?

100. Common points of
attrition can be
easily remedied.

101. Devise new strategy
to compensate for
unavoidable
attrition.

102. Thank you for
watching!