Intent Discovery

  • Release version: Yokohama
  • Updated January 30, 2025
  • 6 minutes to read
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    Summary of Intent Discovery

    The Intent Discovery application in ServiceNow helps identify opportunities for incident deflection by analyzing historic incident or task data to uncover useful intents for Natural Language Understanding (NLU). It assists customers in understanding which prebuilt or custom intents to activate, such as for Virtual Agent and AI Search, enhancing automation and user experience.

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    Intent Discovery is a standalone application available on the ServiceNow Store and appears under All > NLU Workbench > NLU Advanced Features after installation, but it is not part of the NLU Workbench - Advanced Features installation.

    Key Features

    • Intent Analysis: Runs on historic data like incidents, analyzing key text fields (e.g., short description) to identify intents and classify records.
    • Taxonomy Support: Allows running analysis against predefined intent taxonomies (e.g., ITSM domain) to match records to known intents and identify unmatched utterances.
    • Clustering: Groups unmatched records into clusters by keywords, enabling manual review and creation or expansion of intents.
    • Intent Importing: Recommended intents from the analysis can be reviewed and added directly to existing or new custom NLU models within the same application scope.
    • Manual Utterance Addition: Users can add clustered utterances to intents and models with the ability to edit or delete utterances, supporting continuous improvement of NLU models.
    • Report Management: Users can run, rerun, delete, and manage multiple versions of analysis reports to keep intent data current.

    How It Works

    To create an Intent Discovery report, an admin selects a data source (e.g., Incident table), filters records, specifies a field to analyze (like short description), selects a taxonomy, and optionally enables clustering for unmatched utterances. The system then processes the data, generating a report showing matched intents, unmatched records, and clusters.

    Users can then:

    • Review recommended intents and add them to NLU models to enhance automated handling of similar future incidents.
    • Examine clusters of unmatched utterances to create or expand intents by adding relevant utterances manually.
    • Run repeated analyses to refine intent coverage over time.

    Benefits for ServiceNow Customers

    • Improves Virtual Agent and AI Search accuracy by identifying relevant intents from historical data.
    • Enables proactive incident deflection by surfacing common intents that can be automated.
    • Supports continuous enhancement of NLU models with data-driven intent and utterance recommendations.
    • Facilitates efficient management of intent models within the ServiceNow platform's application scopes.

    Getting Started

    • Install Intent Discovery from the ServiceNow Store with admin privileges.
    • Access it under NLU Advanced Features and run your first analysis on incident or task data.
    • Review and import recommended intents into your NLU models or create new intents from clustered utterances.
    • Iterate analyses regularly to maintain and improve intent coverage and incident deflection effectiveness.

    Use the Intent Discovery application to help identify opportunities for incident deflection. For example, you can use it to identify which Virtual Agent conversations to activate next.

    Summary usage

    For applications that consume NLU, such as Virtual Agent and AI Search, Intent Discovery helps you to better understand which prebuilt intents you can benefit from, and which custom intents would be useful to create.

    Intent Discovery provides an analysis that you run on historic incident data or other task data. You can also group the run’s remaining records into different clusters so you can manually add utterances to NLU intents. In addition, you can use specific clusters to create new intents in a model.

    In this example scenario, you're using Intent Discovery to identify the top intents in your instance, and how much coverage they can provide across your historic incident records.

    Installation

    Intent Discovery is available from the ServiceNow Store. For more information, see Install Intent Discovery.

    After Intent Discovery is installed and activated, it appears under All > NLU Workbench > NLU Advanced Features.
    Note:
    Although organized under NLU Advanced Features in the navigation pane, Intent Discovery is a separate application that is not included when installing NLU Workbench - Advanced Features.

    Intent Discovery report details

    • When Taxonomy is selected, the generated report contains intent recommendations against the selected taxonomy. A taxonomy is a prebuilt library of intents in a specific domain. While you don't have access to the underlying intents, when you run Intent Discovery against a specific taxonomy, data that maps to any intent in the taxonomy will be identified.
    • Unmatched records are the utterances which couldn't match to any intent in the taxonomy.
    • Recommended intents are the intents which are found from utterances that data was run on.
    • The percentage of Unmatched records (clustered) are the records that aren't classified (records that don't belong to any of the recommended intents).
    • The percentage of unmatched records and the number of recommended intents don't need to match. It's a coincidence if they match.

    Creating an Intent Discovery report

    1. Using the admin or nlu_admin role, navigate to All > NLU Workbench > NLU Advanced Features > Intent Discovery.

    2. Select either Run analysis or Find recommendations.
    Figure 1. Intent Discovery landing page
    On the Intent Discovery landing page, buttons for Run analysis and Find recommendations are highlighted.

    Running an analysis on the report

    1. For this example report, you configure the following fields on the Intent Discovery > Create new screen.
    • Data Source: Select the Incident (incident) table.
    • Filter by: [Created] [on] [This quarter]
    • Field to analyze: Short description (short_description). You choose Short description because it's a highly used string field that references words that can help the system identify an intent.
    • Taxonomy: Select ITSM. This field tells the system to run classification processing on your ITSM incident records. It has 3 options: Classification, ITSM, or blank, which defaults as Classification.
    • Cluster unmapped utterances by keywords... : Select the check box. When you check this box, the system groups your incident records that weren't classified into clusters.
    • Report name: The field automatically defaults to Incident <month/day/year>. You can edit the name if you prefer. In this example scenario, you enter Incident 12/16/2020 - SF Test.

    2. Select Run analysis.

    Figure 2. Selecting data sources in Intent Discovery for a run analysis
    The Intent Discovery > Create New screen and the fields you need to configure before you select Run Analysis

    Result: Your report appears on the Intent Discovery screen, showing its status as the analysis begins. The subsequent status values appear in the following order during the analysis: Preparing to run, Work in progress, Clustering, and Done. This can take from 5 minutes to 30 minutes to complete. The fewer the records you have in a cluster, the less time it takes. Turning clustering off can also speed up the process.

    Figure 3. An ongoing run analysis
    Your report appears on the Intent Discovery screen where the analysis shows its ongoing status as its job begins and ends
    When the analysis is complete, the column values on the screen appear, with the Status column value set to Done, as shown in the image below.
    Note:
    If you want to delete the report and start over, point to the right of the Status column to invoke the Delete report icon.

    3. Select the Name of your report.

    Figure 4. A completed run analysis
    The report column values have appeared, as the analysis is complete and its status value is set to Done

    Result: The screen refreshes, showing the analyzed incident records and the remaining incident records that were not classified.

    Importing recommended intents to new or existing custom models

    Before importing intents to an NLU model, ensure that you are in the same application scope as the model. For more information, see Select an application from the application picker.

    1. On the Records covered by recommendations section of the screen, select the caret icon on a recommended intent you want to add to a custom model.

    Figure 5. Reviewing a recommended intent
    Instructions to click the caret button which opens to reveal the details of the recommended intent

    Result: The details of the recommended intent appear so you can review them, as shown in the image below.

    2. Select Add to Model.

    Figure 6. Adding a recommended intent to a model
    The recommended intent details are shown with an instruction to add them to a model
    3. On the Select a destination model screen that appears, choose a model you want to add the recommended intent to. If you can't find an appropriate model, create a new one, return to the report, and add the new model.
    Note:
    The model you choose must have the same application scope as your current scope.

    4. Select Save.

    Figure 7. Saving a recommended intent to a model
    The model you choose to associate to the recommended intent is followed by an instruction to select the Save button

    Result: A banner appears on the screen, confirming the intent is added to the target model.

    Figure 8. Confirmation of adding a recommended intent to a target model
    A banner that confirms the recommended intent you chose has been successfully added to the target model

    The recommended intent also appears on the Model screen of the target model, as shown in the image below.

    Figure 9. View a recommended intent in the target model
    The recommended intent is now visible in the Model screen of the target model

    Adding clustered utterances to an intent and its model

    1. On the Remaining records section of the intent discovery records screen, select and open a cluster of utterance and short description data that you want to add to an intent and its associated model.

    As you continue to build out new intents from these clusters, you can click the Ignore icon to remove any unwanted intents from the report.

    There's also a Show Additional filter you can use to show or hide the added intents, and the ignored intents as well.

    2. Select Add to intent.

    Figure 10. Adding a cluster to an intent
    The cluster you chose to add to an intent. Select the Add to Intent button or choose the Ignore button if you want to remove the cluster from the report

    3. In the Add this cluster to an intent and model screen, select an intent and model pair you want to associate to this cluster.

    Figure 11. Adding a cluster to an intent and model
    How to add an a cluster to an intent and its model

    4. Enter a few utterance examples into the open text field. Select Add each time you complete your entry to save it in the system. Use the pencil icon or the trash can icon respectively to edit or delete your entry.

    5. Select Save.

    Figure 12. Adding paraphrased utterances to an intent
    Instruction to add and save paraphrased utterances to an intent

    Result: The records screen appears, showing a banner confirming you added two new utterances to the target intent and its associated model. The model and intent pair appears in the Added To column, as shown in the image below.

    Figure 13. Confirmation of adding paraphrased utterances to an intent
    A banner that confirms the utterances you added to the intent are successfully added

    Use the Show Additional filter if you want to show or hide the clusters that have added intents, and the clusters that are ignored.

    Figure 14. Viewing or hiding clusters and ignored clusters
    How to show or hide clusters that have added intents, and those that you have marked as ignored

    Running another analysis on your Intent Discovery report

    1. Select Run Again.

    Figure 15. Selecting the version of the analysis to run
    Instruction to choose the version of the analysis you want to run

    Result: The new run begins. When it's in progress, the option to cancel the run appears, as shown in the image below.

    Figure 16. The Cancel Run option
    An image that shows the Cancel Run option is available during the first few minutes of the In Progress phase of the run

    When the run is complete, a new banner appears that states you have a new version of the report.

    2. Select the new version, then select Run Again.

    Figure 17. Selecting the new version of the report
    How to select the new version of the report.

    Result: The time stamp you selected for the most recent run appears in the Run date column of the Intent Discovery screen.

    Figure 18. View the new time stamp of the Intent Discovery report
    The new time stamp of the Intent Discovery report