Targeting users

The Targeting tab lets you determine which users will see each variation of an element.

Prerequisites

Prerequisites allow you to control element dependencies in CustomFit.ai. To enable an element you can add a list of elements and their expected values as prerequisites. To delete a prerequisite click on the delete button of the respective prerequisite.

For example, in the below figure you can see that the users who belong to the United States are served with a sign-up button with variation v2 color only if the signed up element is serving false to the user(The user has not signed up).

Adding a prerequisites

To meet a prerequisite, the prerequisite element status must be turned on.

Deleting elements which have prerequisites

You cannot delete an element that other elements are dependent on. You must first remove the dependency before the element can be deleted.

Cyclic Dependencies

CustomFit.ai avoids creating cyclic dependencies between prerequisites. For example, if element A is prerequisites of element B. Then element B cannot be prerequisites for element A.

Target individual users

This section allows you to add individual users to a particular variation. To assign a single user to a variation, add the user to the corresponding variation. If your users are already identified by CustomFit.ai then you will be able to search the users with their user_customer_id or user_id. To remove a particular user from the variation just click on the "X" mark on the user name and click on the Save button at the top of the targeting page. Target individual users feature comes into handy if you want to see how the individual variation appears to different users.

Note: Same user cannot be added in two different variations.

Targeting users based on user persona

CustomFit.ai allows you to target users based on the user persona by writing different rules. For example, a rule serving variation V1 for all the users whose age isLESS_THAN 25. For different types of user properties and operation types supported by CustomFit.ai please visit the User Persona section.

A single rule can also have multiple conditions. To add the second condition click on the "+" icon beside the first condition. And to satisfy this rule the user must satisfy all the conditions. For example, a rule serving variation V1 for all the users with their Gender IS_ONE_OF Female and age is LESS_THAN 25.

Similarly we can have "n" number of conditions in a single rule. To delete a condition click on the delete icon of the respective condition.

Once the conditions have been added then we can decide whether the user will be served with one variation or percentage rollout with several variations.

Targeting users based on user tags

CustomFit.ai allows you to target users based on user tags on which the rules will be executed and the variation will be returned. For example, a rule serving variation V1 for all the users who are tagged with Marketing tag.

For user tags CustomFit.ai has defined two predefined attribute types:

Attribute type

Description

User having Tags

Checks if the given tag is attached to the user

User not having Tags

Checks if the given tag is not attached to the user

For both the tag attributes CustomFit.ai supports one operation type:

Operation Type

Description

TAG_MATCH

Exact match of tag

Targeting users based on user behavior

CustomFit.ai allows you to target users based on user events, based on which the rules will be executed and the variation will be returned. For example, the rule serving variation V1 for all the users who has executed event "/" at least once in the last 15 days. For different types of event operation types and conditions please visit the User Behavior section.

Targeting users based on firmographic attributes

CustomFit.ai allows you to target users based on different firmographic attributes, based on which the rules will be executed and the variation will be returned. For example, the rule serving variation V1 for all the users whose industry belongs to Internet Software and services as well as the number of employees of the company is between 1-10 and the company is in the United States. For different types of firmographic attributes available please refer Firmographic section

Targeting users based on UTM parameters

CustomFit.ai allows you to target users based on different UTM parameters based on which the rules will be executed and the the variation will be returned. For example, the rule serving variation V1 for all the users whose utm_source is from twitter, utm_medium is social and utm_campaign is twitter-camapgin1. For different type of operation types supported by CustomFit.ai please refer UTM parameters section.

Targeting users based on user segment

CustomFit.ai allows you to target users based on custom user segments based on which the rules will be executed and the variation will be returned. For example, if we have a user segment for all the users whose age is LESS_THAN 25, and country IS_ONE_OF USA and gender IS_ONE_OF Female then we can use the segment in rules for targeting users. The same segment can be used for multiple elements.

For user segments CustomFit.ai has defined two predefined attribute types:

Attribute type

Description

User is in Segment

Checks if the given user falls under the given segment

User not in Segment

Checks if the given user does not fall under the given segment

For both the tag attributes CustomFit.ai supports one operation type:

Operation Type

Description

SEGMENT_MATCH

Exact match of SEGMENT

Targeting users based on timestamp

CustomFit.ai allows you to target users based on current time stamp, based on which the rules will be executed and the variation will be returned. For example, a default greeting message will be displayed if the user visits between 12/11/2019 12:00 AM to 12/20/2019 05:28 PM.

Percentage Rollouts

Once you've finished setting up the conditions for your rule, you can decide whether the users will receive just one variation of the element or percentage rollout across several variations.

If you want to serve a percentage rollout for a rule then select it from the dropdown and allocate the users accordingly. For example, from the below figure we can say that if the country IS_ONE_OF USA then 10% of the users will see the website color in AUTUMN color and the remaining 90% of users will see the website in the same default color.

Rule with percentage rollout

In percentage rollouts, we can bucket users based on user properties/user tags. To bucket the users by a particular field, click on the Advanced option in percentage rollout and select the required field from the dropdown. For example, if we select Bucket_By as COUNTRY then users will be bucketed by the value of their COUNTRY field.

Percentage rollout with bucket by

If Bucket by has not been selected in an advanced option then by default the users will be bucketed by user_id.

Default rule

If a user does not fall under any of the above section then the default rule variation will be served. A default rule can serve one variation or multiple variations through percentage rollout.

Default rule with percentage rollout

Off variation

When the element is turned off then the off variation will be served to the users. If the element is of a Boolean type then by default false will be set to off variation and for other types by default the last variation(at the time of the creation of element) will be set as off variation. We can also customize the off variation based on the needs.

Off variation

Priority

The targeting tab of the element evaluates the rule in the top-down approach. If a user matches multiple rules, then the first matching rule applies to the user. The priorities in the targeting tab are as follows:

Priority

‚Äč

1

Prerequisites

2

Target individual user

3

Rule1

4

Rule2

5

Default rule

6

Off variation

For example, in the below figure you can see two rules. The first rule is email ENDS_WITH gmail.com and the second rule is country IS_ONE_OF INDIA. If the user matches both the rules then the first rule will take higher priority.

If none of the rules matches and the element is turned on then Default will take higher priority. And if none of the rules matches and the element is turned off then off variation will take higher priority