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A bot behavior automatically makes decisions and performs actions in response to events.

A behavior is described by a decision tree made up of nodes – a collection of relatively simple building blocks that can be chained together to do complex things.

There are five types of nodes:

Decisions and Outcomes

A decision represents a point where a bot behavior needs to choose the best outcome from any number of possible outcomes.

The first outcome to satisfy all of its conditions is chosen. For this reason, the order of outcomes within a decision is very important.

Conditions are criteria like the time of day, day of week, or the comparison of any record field against some value using an operator (e.g. is, is not, greater/less than, between, contains, matches, starts with).

Here’s a simple binary (two outcome) decision:

  • Is it Friday?
    • Yes
    • No

The “Yes” outcome has a single condition that the current day is “Friday”.

The “No” outcome, being last, doesn’t need any conditions because it would be selected on any day other than Friday. We call this a default (or “catch-all”) outcome.

This is comparable to an if...else conditional statement in computer programming.

A slightly more complex variation is:

  • Day of week:
    • Monday
    • Tuesday
    • Wednesday
    • Thursday
    • Friday
    • Saturday
    • Sunday

Similar to the “Yes” example above, each outcome would compare the current day against a specific target day, and the behavior would continue down the path (branch) of the outcome that matched the current day.

This is comparable to a switch statement in computer programming.

While the above examples have a single condition for each outcome out of simplicity, an outcome can have any number conditions, optionally grouped into sets with an any or all constraint.

As you would expect, a set of any conditions need only satisfy one of them. A set of all conditions must satisfy all of them.

Decisions can also be nested within other decisions. Consider the following:

  • Schedule:
    • Holiday
    • Weekend
    • Weekday
      • What time of day is it?
        • Before office hours
        • During office hours
        • After office hours

The above decision tree describes five final outcomes within two decisions. It doesn’t repeat the conditions to check if the current day is a weekday. The same approach can be used to create very complex decisions that are still easy to follow.


When activated by a bot behavior reaching it, an action node performs one or more operations in response. There are actions to allow bots to do almost anything that a normal worker can do. The available actions depend on the specific event that triggered the behavior.

Cerb comes with many built-in actions: setting a variable, sending an email, closing a ticket, creating a task, making an HTTP request, commenting on a record, loading filtered records from a worklist, notifying a worker, triggering another behavior to run, etc.

Plugins can also add new actions to behaviors: sending an SMS via Twilio, posting to Twitter or Facebook, retrieving customer information from Salesforce or LinkedIn, uploading a file to Amazon S3, and much more.


A loop node repeats every node inside of it for a certain number of iterations.

For instance, assume that you just loaded a list of tweets that @mention your company’s Twitter account using an action node. You now need to scan through each tweet to see if the username matches a contact record in your address book (stored in a custom field). You can use a loop node to iterate through each tweet and run decisions, outcomes, and actions against them.

You can do the same thing with records loaded from a worklist by an action.

It’s also possible to just loop a specific number of times without being based on anything.

In conversational bot behaviors, loops are a simple way to validate user input and prompt them to make corrections when necessary.

See also


Subroutine nodes allow you to create reusable sub-behaviors that can be used any number of times by any action node in the behavior. A subroutine will never run on its own.

For instance, consider again the above example of our “Schedule:” decision. Perhaps in every outcome other than “During office hours”, and among other actions that justify splitting the outcomes, we want to send the same “out of office” auto-response to contacts who write in when we’re not there. A single subroutine would contain the action node for sending the email message, and the four outcomes would each use it. Any changes to that auto-response action would only need to be made in a single place.

Subroutine nodes can also use other subroutine nodes.