System tools for Optimizely Analytics

  • 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.

Optimizely Analytics provides system tools to help you with Analytics-related tasks, in addition to the system tools already available in Opal. 

You can 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 to calling the tool. If you do not provide a required parameter, Opal prompts you for it.

Exploration creation tools

oa_analyze_explore – Lets you get insights and data from a specific exploration in Optimizely Analytics. You can use it for explorations you have just created or ones you have previously saved.
  • When to use

    • You want to see the data and analysis for an exploration you just created.

    • You have found an existing exploration and now want to understand its results.

    • You need to gain insights from a specific report.

  • Parameters

    • A natural language question of what exploration you would like to analyze. 

  • Example prompts

    • Analyze the 'signup funnel' exploration for me.

    • Show me the results of this new exploration. (After you have just created one.)

    • What insights can you provide from exploration ID. 

oa_create_explore – Constructs and saves a Funnel, Retention, or Event Segmentation exploration in Optimizely Analytics.
  • When to use
    • After you have identified the necessary events using oa_find_events.
    • After you have identified any entities for grouping using oa_find_entities.
    • When you are ready to finalize and save an exploration.
  • Parameters
    • appid – The application ID for context. You can find this in the URL (for example, ?app=YOUR_APP_ID).
    • explore_type – Specifies the type of exploration to create. Available values are FUNNEL_BLOQ, RETENTION, or EVENT_SEGMENT.
    • events – A list of event groups that define the exploration.
      • For Funnels, the order of events in this list defines the stage order.
      • For Retention, this list must contain exactly two event groups: the first is the 'initial' event group, and the second is the 'return' event group.
      • For Event Segmentation, this list must contain exactly one event group.
      • Each event group must contain JoinableEvent objects obtained from the oa_find_events tool.
    • (Optional) name – A concise, descriptive name for your exploration. Opal intelligently generates this, but if there is a duplicate name, Opal asks you for a new one.
    • (Optional) description – A brief, one-sentence description of what the exploration shows. Opal intelligently generates one, if you do not provide one.
    • (Optional) group_by  – The id from a JoinableEntity object (returned by the oa_find_entities tool) to group the results. Used when you explicitly request to 'group by' or 'break down by' a specific attribute.
    • (Required for EVENT_SEGMENT) measure – The metric to measure for Event Segmentation. Available values are EVENT_COUNT, UNIQUE_ACTOR_COUNT, or AVG_EVENT_BY_ACTOR.
  • Example prompts
    • Create a funnel exploration for users who viewed a product page and then added an item to their cart.
    • Show me the retention of users who signed up and then returned to make a purchase.
    • Create an event segmentation report for all 'click' events, grouped by device type.
    • I want a funnel that tracks 'page_view' of the homepage, followed by 'add_to_cart', and then 'purchase'.
    • Generate a retention report for users who 'signed_up' and then 'logged_in'.
oa_find_entities – Searches for analytics entities (also known as properties or attributes) based on a natural language query within Optimizely Analytics.
  • When to use
    • Find specific properties that you want to use for analysis.
    • Identify properties to "group by," "break down by," or analyze "for each" when creating an exploration.
    • Discover properties related to a specific event that you have already identified using oa_find_events.
  • Parameters
    • appid – The application ID for context.
    • query – A natural language description of the property you are searching for (for example, "country" or "device type").
    • (Optional) event – A JoinableEvent object (returned from the oa_find_events tool) to restrict the search to entities related to that specific event. 
  • Example prompts
    • Find entities related to "country" or "device type."
    • What properties can I use to group my 'purchase' events?
    • Show me the entities associated with the 'user signed up' event.
    • I want to break down my funnel by "browser type." 
oa_find_events – Searches for and returns a list of analytics events based on a natural language query.
  • When to use
    • When you need to identify specific user actions, such as 'user signed up' or 'product added to cart'.
    • As the initial step in building an analytics exploration, as its output is required by the oa_create_explore tool.
    • To find events that Opal can use to discover related properties with the oa_find_entities tool.
    • Find the correct event objects to use as stages in a funnel, initial or return events in a retention report, or events to segment in an event segmentation report.
  • Parameters 
    • appid – The ID of your Optimizely Analytics application for context. Opal uses the appid from your system context if available, or explicitly asks you for this value. You can often find it in the URL of your Optimizely Analytics project (signified by ?app=).
    • query – A natural language description of the event you are searching for (for example, "user signed up").
  • Example prompts
    • Find the event for "user signed up."
    • What are the events related to "product added to cart"?
    • Show me the event for when a user "completed checkout."
    • I need to find events for "page view" and "button click."
oa_find_explores – Helps you find existing saved explorations in Optimizely Analytics by using AI to understand your request and find relevant explorations even if your wording is slightly different from the saved name.
  • When to use

    • You want to locate a previously saved analysis, like a "signup funnel" or "user retention" report.

    • You are looking for an existing exploration to analyze further.

  • Parameters

    • A natural language description of the exploration you're looking for (for example, "signup funnel", "user retention", or "conversion analysis").

  • Example prompts

    • Find my 'signup funnel' exploration.

    • Are there any saved explorations about user retention?

    • Show me explorations related to conversion analysis.

    • Can you find the 'Q4 marketing campaign' exploration?

Data retrieval

oa_find_datasets – Searches and lists available datasets in Optimizely Analytics. It uses fuzzy matching on dataset names and semantic search on descriptions to find relevant datasets.
  • When to use
    • To locate specific datasets by name or keyword within Optimizely Analytics.
    • To discover available datasets related to a particular topic or area of interest.
    • To get a comprehensive list of all accessible datasets.
    • To identify relevant datasets for further analysis or reporting.
  • Parameters
    • query – A natural language search query to filter datasets by name or description. For example, 'mobile users', 'premium customers', or 'active subscribers'.
  • Example prompts
    • Find datasets related to 'user behavior'.
    • Show me all datasets.
    • What datasets can I use for my analysis?
    • Are there any datasets about 'e-commerce sales'?
    • Search for datasets containing 'product'.
oa_find_metrics – Searches and finds existing metrics from Optimizely Analytics. Uses fuzzy matching on metric names and semantic search on descriptions to find relevant metrics.
  • When to use
    • You want to locate a previously saved metric, like "revenue" or "conversion rate".
    • You are looking for an existing metric to analyze or use in an exploration.
  • Parameters
    • metric_name – The specific metric to retrieve. For example, 'conversions', 'revenue', 'page_views', or 'bounce_rate'.
    • (Optional) project_id – The ID of the Optimizely project to filter metrics by.
    • (Optional) experiment_id – The ID of a specific experiment to retrieve metrics for.
    • (Optional) campaign_id – The ID of a specific campaign to retrieve metrics for.
    • (Optional) start_date – The start date for the metric data in 'YYYY-MM-DD' format.
    • (Optional) end_date – The end date for the metric data in 'YYYY-MM-DD' format.
    • (Optional) interval – The aggregation interval for the data. For example, 'daily', 'weekly', 'monthly', or 'total'.
  • Example prompts

    • Are there any saved metrics for conversion rate?

    • Show me metrics related to average order value.

    • Can you find the 'daily active users' metric?

oa_get_metric_data – Retrieves and executes a specific saved metric in Optimizely Analytics, returning its calculated table data.
  • When to use
    • You want to see the actual data values for a metric you previously found using the oa_find_metrics tool. 
    • To analyze the trends or patterns for a specific metric over a defined period or granularity.
    • You want to understand the performance of a key business indicator. 
  • Parameters
    • app_id – The ID of the Optimizely application for which to retrieve metric data.
    • metric_id – The ID of the specific metric to retrieve from the oa_find_metrics tool.
    • (Optional) start_date – The start date for the data retrieval in 'YYYY-MM-DD' format. 
    • (Optional) end_date – The end date for the data retrieval in 'YYYY-MM-DD' format.
  • Example prompts
    • Get metric data for app 123 and metric conversion_rate.
    • Retrieve the page_views metric for application 456 from 2025-01-01 to 2025-01-31.
    • What is the bounce_rate for app 789?
    • Show me the revenue metric for app 101 for the last week.
oa_list_apps – Lists all available applications in Optimizely Analytics.
  • When to use
    • To see all applications you have access to within Analytics.
    • To find the ID of a specific application when you need to perform actions on it.
    • To get an overview of your Optimizely Analytics application landscape and available projects.
  • Parameters
    • None
  • Example prompts
    • List all Optimizely applications.
    • What applications are available in Optimizely Analytics?
    • Show me a list of all apps I have access to.

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.