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Unlike custom groups, which are manually created and maintained, smart groups are managed by rules that govern membership and its qualifications. When these rules are in effect, users are automatically sorted into groups according to rule criteria. For example, you might create a rule to group users by job title or business unit, or you can stack rules to create complex conditions that combine several criteria.

Rules follow this syntax: rule type + operator + value. Rule type refers to a particular user attribute; value refers to information recorded in that attribute; and operators define the relationship between attributes and their values. In combination, these three elements create a logical string or expression that tells Seismic Learning how to sort users into groups, or whether users should be sorted at all.

For example, suppose you create the following rule:

All users with a job title (rule type) that contains (operator) the word manager (value) will be added to the smart group. Thereafter, any new users who meet these conditions will also be added to the group.

Navigate to the People page, and then select New Smart Group from the command menu.

Alternatively, select the ➕ icon in the left-hand menu.

Doing so will launch the smart group rule builder. This is where you'll establish the criteria by which users are automatically sorted into groups. Read on to learn about the different rules you can set.

There are three types of rules: user, group, and custom field rules. Each rule type contains several attributes such as job title and hire date. These attributes are combined with operators (e.g., equal to, contains) to create logical expressions.

User rules comprise several characteristics drawn from user profiles: name, email address, role, job title, business unit, department, location, manager name, hire date, and the date on which the user was created.

Group rules depend on the existence of custom groups. Use these rules to sort people by their membership in other groups or whether they manage other groups. For example, you could create a new enablement smart group that includes all members of the sales and marketing custom groups, or you could create a smart group that brings together all group managers in your tenant.

Custom field rules act on the values in custom fields you've created. If you haven't created any custom fields you won't see this option in the rule type menu.

There are two kinds of operators in the rule builder: those which act on criteria within a rule and those which determine how rules interact with one another.

Criteria operators, or value operators, are part of a rule's syntax; they define the relationship between attributes and their values. These operators vary according to the fields in user profiles. More precisely, they vary according to the number of values a field can have. Free-text fields, such as name, email address, and job title, are unbounded; they admit an unlimited number of possibilities. Therefore, such fields have operators that help rule builders account for these many possibilities. Such operators include:

Some user fields have a defined or discrete number of possible values, however. Because Learning only has four user roles, for example, the Role field has only four possible values: admin, manager, creator, or learner.

The other fields with defined values include Locale and the Manager and Membership properties of custom group rule types.

Once you've created a rule, you can determine how it interacts with other rules by setting rule operators. These operators, OR and AND, are sometimes called Boolean operators. Using them will help you create complex rulesets that group users according to multiple criteria.

When two rules are joined by an OR operator, Learning will include all users who meet the criteria in the first or second rules. In other words, using the OR operator will expand the number of users in a smart group.

For example, suppose you've created two rules: one applies to all users in the Go to Market business unit; the other applies to all users in the Customer Success department. When these rules are joined with an OR operator, the resulting smart group will contain all members of the GTM business unit or the Customer Support department.

We can visualize this as a Venn diagram.

You can also join rules with an AND operator. This will instruct Learning to create a smart group that includes all users who meet both criteria. The AND operator narrows the number of qualified users.

If we apply the AND operator to the example above, the resulting smart group will contain only users who belong to the Go to Market business unit and the Customer Success department.

Unlike the first example, the one using an OR operator, the overlap here is significant. Only users who fall within the overlapping region of the diagram are included in the smart group.

Using criteria operators with ruleset operators can help you create multivariate filters in order to group users together.

Smart group rulesets can be edited at any time. Before making updates, however, look for live assignment triggers associated with the group. If a smart group is updated, and new users are added when a trigger is live, the trigger will fire, assigning content to new group members, and possibly restarting the progress of learners who already completed the assignment. To prevent this from happening, read this guidance on deactivating triggers.

Each smart group in a Learning tenant must have a unique name. This applies even to smart groups that have been archived. If you see the error message "Name has already been taken" when attempting to save a new smart group, it means such a group already exists, either in your group roster or in the archives.

To free up the name of an archived smart group, restore the group to your account, change its name, and then return it to the archives. This process is similar to registering users when their email addresses have been taken.

Membership is automatically recalculated when the following events occur:

You can also force recalculation of a smart group's members by selecting the Recalculate button from the group overview page. Smart group membership is automatically recalculated when users are created or updated, but there are occasions when it's helpful to manually recalculate membership, such as checking your work when building complicated groups, or when restoring archived users and their membership in a smart group.

The group details page gives you the nitty-gritty on a particular group's progress and performance.

Let's put it all together! This 5-minute tutorial covers the fundamentals of smart group creation and the interaction of several different rules. Select the image below to launch the tutorial in a new tab.

The rule builder is not predictive, nor does it account for abbreviations or inflected forms of a word. Criteria operators will act strictly upon the values you enter.

For example, suppose your company uses AM as shorthand for account managers. A rule that groups users according to job titles that contain "AM" will include everyone who has that string in their job title, both AMs (account managers) and people with unrelated job titles, such as "Team Lead". Similarly, a rule intended to group all account managers will not function correctly if account manager is misspelled or if the plural form is used when the singular form is preferred.

In other words, ensure a one-to-one parity between the value in a rule and the information in its corresponding user field.

Seismic Learning looks for an exact match between rules and the user fields they act upon. Even errant spaces, sometimes called whitespaces, can leave users unaffected by rules that are meant to group them with their teammates.

In the example below, all users named Eddie Van Loon will be sorted into a smart group called Test Smart Group. Note the extra space between "Van" and "Loon", however. This is enough to create a mismatch between fields, breaking the rule's intended functionality.

A. When attempting to archive smart groups that contain more than 730 users, Learning will throw a 504 gateway timeout error. We're working on a permanent solution to this issue. In the meantime, please contact support@lessonly.com. We'll fix it for you ASAP!

A. Each day is 24 hours long beginning at the time of a smart group's creation. The example pictured below contains two rules, the combined effect of which will be to group only those users who were created three days previous. The second rule, "created within the last 3 days", applies to all users created within the last 72 hours. If you were to save this smart group at 9:15 am UTC on Oct 7th it would apply to all users created since Oct 4th 9:15 am UTC.

A. When a user is created in Learning, the created date is stored as a string in UTC. For example, if a user is created at 10:33 am EDT on 04/08/2021 we store the created date as 2:33 pm UTC on 04/08/2021.

When creating a smart group with a rule to identify users "created on a specific date," the results will include everyone created between 12:00 am UTC and 11:59 pm UTC on the selected date.

Depending on the time of day a user was created, the created date could be saved as the following day. For example, if a user is created at 10:00 pm EDT on 04/08/2021 we store the created date as 2:00 am UTC on 04/09/2021. If you encounter this scenario, edit the rule to use the "between" operator, then set the date range accordingly.

A. User hire dates are stored in the following format: MM/DD/YYYY. A rule that groups all users hired between two dates will include everyone hired between 12:00am UTC on the start date and 11:59 pm UTC on the end date.