System tools for Optimizely Data Platform (ODP)

  • Updated

System tools are built-in features that help Optimizely Opal take action. Each tool performs a specific task, such as creating a campaign, uploading files, or generating images. Think of tools like attachments on a Swiss Army knife. Each one has a distinct purpose that helps you get work done.

In addition to the system tools available in Opal, Optimizely Data Platform (ODP) includes a set of system tools designed to support getting campaign information.

Ask Opal what tools it has at any time. For example, enter "Please list the tools you have with a brief description of what they do and the parameters" into Opal Chat.

Click a tool's name to expand it and learn when to use it, its required and optional parameters, and example prompts for calling the tool. If you do not provide a required parameter, Opal prompts you for it.

create_odp_audience – Creates a new audience (segment) in ODP, supporting both standard and realtime types.
  • When to use
    • Create a new realtime audience in ODP with a custom definition and ID.
    • Create a new standard audience segment in ODP with a display name and definition.
    • Build a new audience segment from a JSON definition to target specific customer behaviors.
    • Set up a new ODP segment as part of a personalization or targeting strategy.
  • Parameters
    • type – Type of audience: standard or realtime.
    • definition – Definition of the audience in JSON format.
    • (Optional) id – ID of the realtime audience to be created (required for realtime).
    • (Optional) display_name – Display name of the audience (required for standard).
  • Example prompts
    • Create a realtime ODP audience with id "high_value_customers" and a definition that targets customers with lifetime value over 500.
    • I need a new standard audience in ODP called "Newsletter Subscribers" with a definition filtering by email opt-in status.
    • Can you create a realtime ODP segment with id "recent_purchasers" and display name "Recent Purchasers" that includes customers who purchased in the last 30 days?
create_odp_audiences – Creates a new real-time segment in ODP based on a natural language description.
  • When to use
    • Quickly create a real-time ODP audience from a plain-language description without writing JSON.
    • Generate one real-time segment at a time using a conversational prompt.
    • Build a targeted audience segment when you know the criteria but do not want to manually construct the definition.
  • Parameters
    • user_query – A natural language query of a segment or audience to create in ODP. Use the exact query that the user wrote without rewriting it. The query will be normalized (lowercased, punctuation removed, and extra spaces cleaned).
  • Example prompts
    • Create an ODP segment for customers who abandoned their cart in the last 7 days.
    • Build me an ODP audience of users who have made more than 3 purchases in the past month.
    • I need a real-time ODP segment for customers located in the United States who opened an email in the last 14 days.
fetch_schema – Retrieves the complete ODP data model schema for the connected account.
  • When to use
    • Understand what customer data is available in ODP, such as email, loyalty tier, or purchase history.
    • Explore which event types are being tracked or inspect the event schema structure.
    • Identify available fields before building audience segments or queries.
    • Understand data relationships, for example how customers relate to orders or events.
    • Answer questions like "what data do we have," "what fields are available," "show me the schema," or "what customer attributes exist."
  • Parameters
    • (Optional) dimensions – Optional comma-separated list of specific dimension or object names to retrieve (for example, customers,events,products). Dimension names must be in lowercase, snake_case, and plural form (for example, customers not Customer). When provided, Opal only returns schema information for the specified dimensions. When omitted or empty, Opal returns the complete schema for all dimensions in the account.
  • Example prompts
    • Show me the full ODP data model schema.
    • What customer attributes are available in ODP?
    • Fetch the ODP schema for customers and events only.
    • What fields are available in the orders dimension in ODP?
get_odp_audience_by_id – Retrieves details for a specific ODP segment (audience) by its ID.
  • When to use
    • Look up a specific ODP audience or segment by its unique identifier.
    • Inspect the definition, configuration, or metadata of an existing segment.
    • Verify the details of a realtime or standard audience before updating or referencing it.
  • Parameters
    • id – ID of segment to be returned.
    • type – Type of segment: standard or realtime.
  • Example prompts
    • Show me the details of the ODP realtime segment with id "high_value_customers".
    • Get the definition of standard ODP audience "12345".
    • Look up the ODP segment "recent_purchasers" — it's a realtime audience.
get_odp_audience_list – Retrieves a list of all segments (audiences) in ODP by type.
  • When to use
    • List all available realtime or standard segments in ODP.
    • Get an overview of existing ODP audiences and their descriptions.
    • Discover which segments are configured before creating or updating one.
  • Parameters
    • type – Type of segment: standard or realtime.
  • Example prompts
    • Show me all realtime ODP segments.
    • List all standard audiences in ODP.
    • What ODP realtime audiences do we have configured?
odp_query_event_logs – Queries event log data from ODP and returns matching records.
  • When to use
    • Retrieve recent event activity for a specific customer or set of customers in ODP.
    • Investigate what events were tracked for a particular user, such as purchases, page views, or email interactions.
    • Query ODP event logs to troubleshoot or validate that events are being recorded correctly.
    • Analyze customer behavior patterns by querying event data with filters.
  • Parameters
    • queries – The natural language query describing what event log data to retrieve from ODP.
  • Example prompts
    • Show me the last 10 events for the customer with email "jane@example.com" in ODP.
    • Query ODP event logs for all purchase events in the last 24 hours.
    • What events have been tracked for customer ID "abc123" in ODP?
suggest_odp_audiences – Suggests three real-time ODP audience segments based on a natural language description. 
  • When to use
    • Get audience segment suggestions from ODP before committing to a specific definition.
    • Explore possible audience configurations when you have a general targeting idea but want recommendations.
    • Generate multiple audience segment options to compare before creating one.
  • Parameters
    • None.
  • Example prompts
    • Suggest ODP audiences for targeting high-value customers who have purchased more than three times.
    • What ODP audience segments would you recommend for re-engaging users who have not visited in 30 days?
    • Suggest some ODP segments for customers interested in electronics based on their browsing behavior.
update_odp_audience – Updates an existing audience (segment) in ODP.
  • When to use
    • Modify the definition of an existing ODP audience segment.
    • Change the display name of a standard audience in ODP.
    • Update the targeting criteria for a realtime or standard segment that already exists.
  • Parameters
    • id – Id of the audience to be updated.
    • type – Type of audience: standard or realtime.
    • definition – The segment definition in JSON format.
    • (Optional) description – Description for the segment (required for realtime).
    • (Optional) display_name –Display name of the audience (required for standard).
  • Example prompts
    • Update the ODP realtime segment "high_value_customers" to include customers with lifetime value over 1000 instead of 500.
    • Change the display name of standard ODP audience "12345" to "VIP Customers".
    • Update the definition of the ODP realtime audience "recent_purchasers" to target purchases in the last 14 days instead of 30.
validate_odp_audience – Validates an ODP audience definition without creating or updating it.
  • When to use
    • Check whether an audience definition is valid before creating or updating a segment in ODP.
    • Troubleshoot errors in an ODP audience definition by validating its structure.
    • Confirm that a JSON audience definition conforms to ODP requirements before applying it.
  • Parameters
    • definition – Definition of the audience in JSON format to validate.
    • type – Type of audience: 'standard' or 'realtime'.
  • Example prompts
    • Validate this ODP audience definition before I create the segment: {"filter": [{"field": "lifetime_value", "operator": "gt", "value": 500}]}.
    • Check if this realtime ODP audience definition is valid: {"event": "purchase", "days": 30}.
    • Can you validate my standard ODP audience definition to make sure it has no errors?

If you use Opti ID, administrators can turn off generative AI in the Opti ID Admin Center. See Turn generative AI off across Optimizely applications.