Top
Login
Contents x
Create a Cohort
  • 07 Nov 2023
  • 6 Minutes To Read
  • Print
  • Dark
    Light
  • PDF
Contents

Create a Cohort

  • Updated On 07 Nov 2023
  • 6 Minutes To Read
  • Print
  • Dark
    Light
  • PDF
Article Summary

After creating Insights, you have to analyze the Insight, and compare and contrast the user behavior to make decisions. With Cohorts, you can do the following:

  • Create a group of users based on certain criteria
  • Analyze this Cohort to compare user behavior
  • Show content or take actions on the specific Cohort

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

your title goes here

You can also provide a description for your Cohort.

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

Your Cohort needs to have at least one rule.

  1. Select any one of the following conditions using the dropdown.
    cohorts_
Rule - Performed

Performed: To group users based on the Whatfix events (both Default and Custom events) they've engaged with.

your title goes here

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 Create Trend Insights and List of Whatfix related Events.

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

cohorts_performed

a) Select the Event that the end user has engaged with that you want to track.
Example: group users who have 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 has occurred or has been engaged with.
Example: group users who have completed a Flow more than a certain number of times
c) Enter the count of occurrence of the Event.
Example: group users who have 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 have completed a Flow more than once during the last 7 days.

your title goes here

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

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

    date_filters_during

  • 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 filters associated with that Event to drill down on the users based on certain Event properties, if required.
cohort_event_filter

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

your title goes here

  • The During time window has 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/engaged with.
    Date filter

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

  • You can add Event filters to drill down on the users based on certain Event properties.


  • You can add more than one Event filter for a rule.

Rule - Did not perform

Did not perform: To group users based on the Whatfix events (both Default and Custom events) they've not engaged with.

your title goes here

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 Create a Trend Insight and 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 particular period of time:

cohorts_did_not_perform

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

your title goes here

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

c) Select the default or custom date filters.
Example: group users who have not viewed a Link since a particular date.

your title goes here

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

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

    date_filters_during

  • 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) Select the Event filters associated with that Event to drill down on the users based on certain Event properties, if required.
Example: group users who have not viewed the link called Testing since a particular date.

Example: Grouping users who have not viewed the link called Testing from a widget since September 9th, 2022.
did_not_perform_event

Rule - Has Attribute

Has Attribute: To group users based on user attributes (User Filters and Breakdown) like city, browser, country, OS, etc.
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 given time.
e) Select the time window (During or Since).

your title goes here

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

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

your title goes here

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

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

    date_filters_during

  • 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?

your title goes here

Event filters are not applicable for the Has attribute rule.

Example: Group users who have used the Chrome browser anytime during the last 30 days.

cohorts_has_attribute

your title goes here

  • All the rules are grouped using an Or operator, which means that if any one of the conditions is true, you get results.

  • You can also add rules and group them using an And operator, which means that all the conditions have to be satisfied to get the 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 see the number of users part of the Cohort that you have built.
    cohort_refresh
your title goes here

  • 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?
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