Top
Login
Contents x
Create a Cohort
  • 24 Feb 2025
  • 7 Minutes To Read
  • Print
  • Dark
    Light
  • PDF
Contents

Create a Cohort

  • Updated On 24 Feb 2025
  • 7 Minutes To Read
  • Print
  • Dark
    Light
  • PDF
Article summary

Whatfix enables you to group users based on their behavior or engagement using Cohorts.

Cohorts enable:

  • Creating a group of users based on specific criteria
  • Creating a group based on User lists
  • Filtering data and analyzing end-user behavior
  • Displaying content or making further decisions

Use the following steps to create a Cohort:

  1. On the Whatfix Analytics dashboard, click Audience.
    ia_left%20nav_audience

  2. Click Cohorts.
    Click_coharts

  1. Click Create cohort.
    analytics_create_cohort

  2. Click the Edit icon to name your Cohort.
    analytics_cohort_name

Info:

Provide a description that explains the purpose of the Cohort.

  1. To add conditions to build your Cohort, click Add rule.
    2022-09-27_12-54-01
Info:

A Cohort requires at least one rule.

  1. Select one of the following conditions from the dropdown.
    cohort_conditions.png
Rule - Performed

Performed: This groups users based on the Whatfix events (both Default and Custom events) they engage with.

Info:

The Default and Custom events appear in the dropdown only if you have performed the events at least once.

For more information on Whatfix events, see List of Whatfix related Events.

Use the following steps to group users who have engaged with any Whatfix event (Default or Custom) over a specific period:

cohorts_performed

a) Select the Event that the end user has engaged with that you want to track.
Example: Group users who completed a Flow.
b) Select the comparison operators (Equal to, Does not equal to, Greater than, Less than, Greater than or equal to, Less than or equal to) to compare the number of times the event occurs.
Example: Group users who completed a Flow more than a specified number of times.
c) Enter the count of occurrences of the Event.
Example: Group users who completed a Flow more than once.
d) Select the time window (During or Since).
e) Select the default or custom date filters.
Example: Group users who completed a Flow more than once during the last 7 days.

Info:

  • The following default and custom date filters are available for the During time window:

    • Last 7 days
    • Last 30 days
    • Last 90 days
    • Last X days
    • Custom date
      cohort_date_filter_new

  • Whatfix enables you to add up to 400 days as Last X days.
    cohorts_date_filter_last x days

  • The Since time window enables you to add only a custom date.
    date_filter_since

  • The date filters align with the timezone that you've set. For more information, see How can I visualize Analytics data in my timezone?

f) Click the Filter icon to select the Event or User attributes associated with that Event to drill down on the users based on event or user properties.
cohort_event_filter

Example: Group users who completed the Access Self Help Flow more than once in the last 7 days.
performed_flow_completed

Info:

  • The During time window includes default and custom date filters, and the Since time window enables you to set a custom date since the time the event has been performed or engaged with.

    For example, if you select the During time window on November 21, 2022 for the Last 7 Days, the filter is applied from November 14, 2022, 00:00:00 hours until November 20, 2022, 23:59:59 hours.

  • Add Event or User attributes associated with that Event to drill down on users based on event or user properties, respectively.
    cohort_event_user_attribute

  • Whatfix enables you to add more than one Event or User attribute for a rule.

Rule - Did not perform

Did not perform: This groups users based on the Whatfix events (both Default and Custom events) they have not engaged with.

Info:

The Default and Custom events appear in the dropdown only if you have performed the events at least once.

For more information on Whatfix events, see List of Whatfix related Events.

Use the following steps to group users who have not engaged with any Whatfix event (Default or Custom) over a specific period:
cohorts_did_not_perform

a) Select the Event that your end user has not engaged with that you want to track.
Example: Group users who have not opened a Link.
b) Select the time window (During or Since) for which you want to track the Event.

Info:

For example, if you select the During time window on November 21, 2022 for the Last 7 Days, the filter is applied from November 14, 2022, 00:00:00 hours until November 20, 2022, 23:59:59 hours.

c) Select the default or custom date filters.
Example: Group users who have not opened a Link since a specific date.

Info:

  • The following default and custom date filters are available for the During time window:

    • Last 7 days
    • Last 30 days
    • Last 90 days
    • Last X days
    • Custom date
      cohort_date_filter_new

  • Whatfix enables you to add up to 400 days as Last X days.
    cohorts_date_filter_last x days

  • The Since time window enables you to add only a custom date.
    date_filter_since

  • The date filters align with the timezone that you've set. For more information, see How can I visualize Analytics data in my timezone?


d) Click the Filter icon to select the Event or User attributes associated with that Event to drill down on the users based on event or user properties.
cohort_filter_did_not_perform

Example: Group users who have not opened the link called Testing since a particular date.

Example: Grouping users who have not opened the link called Testing since September 9, 2022.
did_not_perform_event

Rule - Has Attribute

Has Attribute: This groups users based on user attributes, such as city, browser, country, and OS.
For more information on User attributes, see User Filters and Breakdown in Insights.

Use the following steps to group users based on certain user attributes:

cohorts_has_attributes

a) Select the user Attribute that you want to track.
Example: Group users based on the browser that they use.
b) Select the comparison operators (Equal, Does not equal, Contains, Does not contain, Starts with, Ends with) to compare the Attribute.
c) Select the value of the Attribute.
Example: Group users who use the Chrome browser.
d) Select the frequency
Example: Group users who use the Chrome browser at any time.
e) Select the time window (During or Since).

Info:

For example, if you select the During time window on November 21, 2022 for the Last 7 Days, the filter is applied from November 14, 2022, 00:00:00 hours until November 20, 2022, 23:59:59 hours.

f) Select the default or custom date filters.
Example: Group users who used the Chrome browser at any time during the last 7 days.

Info:

  • The following default and custom date filters are available for the During time window:

    • Last 7 days
    • Last 30 days
    • Last 90 days
    • Last X days
    • Custom date
      cohort_date_filter_new

  • Whatfix enables you to add up to 400 days as Last X days.
    cohorts_date_filter_last x days

  • The Since time window enables you to add only a custom date.
    date_filter_since

  • The date filters align with the timezone that you've set. For more information, see How can I visualize Analytics data in my timezone?

Info:

Event filters are not applicable for the Has attribute rule.

Example: Group users who have used the Chrome browser anytime during the last 7 days.

cohorts_has_attribute

Rule - Belong to user list

Belong to user list: This groups users based on whether they're part of the User list or not. Whatfix enables you to upload a list of User IDs called User list (Static Cohort) and create a Cohort. For example, upload a User list containing the User IDs of all Sales team members to create a Cohort that targets Whatfix content to this specific team.

Info:

For more information on User lists, see What are Static Cohorts (User lists)? and Create a Static Cohort (User list)

Use the following steps to group users based on User lists:

Example: Create a Cohort from the User list containing Sales team members.

cohort_user_list_example.png

a) Select the condition as Belongs to or Does not belong to.

Condition Description
Belongs to Users who are part of the User list.
Does not belong to Users who are not part of the User list.

b) Select the User list.

Info:

Whatfix enables you to add other rules, such as Performed, Did not perform, or Has Attribute along with the Belong to User list rule to analyze the behavior of the users part of the User list.
Examples:

  • Identify Sales team members engaged with a new feature.
    user_list_cohort_example_performed.png

  • Identify new users who did not complete the onboarding Task List.
    user_list_cohort_example_did_not_perform.png

Info:
  • All the rules are grouped using an Or operator, which means that if any one of the conditions is true, you get results.
  • Whatfix enables you to add rules and group them using an And operator, which means that all the conditions have to be satisfied to get results.
    Scroll down to the And also meet the below conditions section and then click Add a group to add more rules.
    and_cohorts
  1. After adding the rules, scroll down to the Users in this cohort section, and then click Refresh to view the number of users included in the Cohort.
    cohort_refresh
Info:

  • The following image shows the number of users part of the Cohort.
    users_in_the_cohort

  • Every time you add a rule, you need to refresh the Cohort to see the updated data.

  1. Click Save cohort.
    save_cohort
Was this article helpful?
Related Articles
What's Next
Privacy Policy | Whatfix Glossary | Whatfix Platform Status
Copyright © 2024 WHATFIX TM. All rights reserved.
Change password!
Changing your password will log you out immediately. Use the new password to log back in.
Change profile
Success!
First name must have atleast 2 characters. Numbers and special characters are not allowed.
Last name must have atleast 1 characters. Numbers and special characters are not allowed.
Enter a valid email
Enter a valid password
Your profile has been successfully updated.
Logout