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Introduction to Sitecore Personalize
Managing accounts and system settings
Identifying guests
Introduction to experiments
Introduction to experiences
Decisioning
View dashboards
Developer Center
Connecting to an external system
Using client-side JavaScript
Using server-side JavaScript
AI in Personalize
Glossary
  • Sitecore Personalize
  • Introduction to decisioning in Sitecore Personalize
  • Managing decision models in Sitecore Personalize
  • Using decision model components in Sitecore Personalize

Using decision model components in Sitecore Personalize

After you create a decision model, the next step is to create a decision model variant. A decision model variant is made up of components that help you define the business logic behind a decision model.

To build the variant, you need to select a component, drag it onto the decision canvas, and then establish a connection between it and another dependent component. This could be a decision table, a programmable, a connection, or any other relevant component in the decision model canvas palette.

The components available in the decision model canvas palette.

Input Data

These components represent different data entities that can be used as inputs to a decision model to derive an output. They visually represent guest, order, or session data entities, but they don't have any functional roles. You're not required to add them to the decision canvas explicitly, but doing so makes it easier to understand the input data feeding into other decision model components.

Component

Description

Guest

Enables you to use guest data as an input to the decision model, for example, guest email or first name.

Order

Enables you to use order data as an input to the decision model, for example, payment type or order status.

Sessions

Enables you to use real-time session data, including event data, as an input to the decision model. For example, cart type or value.

Decisions

These components are designed to process inputs by running specific selection or computational tasks. Based on the input data, these components evaluate the most appropriate output, such as returning an optimal offer or recommending the next strategic action.

Component

Description

Decision Table

Enables you to write business rules in a tabular format to determine the next best offer or action based on input and output conditions and rules.

Programmable

Enables you to use JavaScript in a decision model, often to use nested data that is required by a decision table to determine the next best offer or action.

When you add a programmable, you need to assign it an output reference so that it returns a JavaScript object to the decision model.

Decision Template

Enables you to add a reusable JavaScript or programmable template into a decision model, without having to edit code or write it from scratch.

Decision templates often display a form.

Knowledge Sources

This component refers to a repository for slow-changing, static data such as your organization's offer catalog. This can be added to a decision model to return relevant offers.

Component

Description

Offers

Enables you to return offers in a decision table. This is currently the only type of knowledge source component that Sitecore Personalize supports.

External Systems

These components include both internal or external systems that play a role in the decision-making process. They let you retrieve data, perform calculations, and use the latest machine learning technologies. The results from these operations are often used as input in a decision table or a programmable component.

Component

Description

Data Systems

Enables you to retrieve dynamic data from an external system and use it as an input into other decision model components. For example, using a guest's location and sending this to an external weather service to retrieve real-time weather data, and then using the information to determine the most relevant offers.

Analytical Model

Enables you to use the latest machine learning technologies to pass parameters to an analytical model, retrieve data, or perform a calculation, and then use the result as an input into other decision model components.

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