Funnels tab

  • Release version: Washingtondc
  • Updated February 1, 2024
  • 3 minutes to read
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    Summary of Funnels tab Extend ServiceNow AI Platform capabilities

    The Funnels feature in ServiceNow allows users to filter and analyze conversation flows within the Virtual Agent. By creating up to 10 filtering steps, users can gain insights into the performance of chat interactions, helping to identify effective conversation paths and areas for improvement.

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    Key Features

    • Cumulative Filtering: Each step in a funnel refines results based on the previous step, allowing for detailed analysis of user interactions.
    • Performance Metrics: Metrics displayed include user engagement at each step, drop-off rates, and completion rates, which assist in evaluating conversation flow efficiency.
    • Customizable Steps: Users can define fields, operators, and values to create tailored filtering steps for specific analysis needs.
    • Comparative Analysis: Users can compare current funnel performance with historical data over the same date range to track changes in user engagement.

    Key Outcomes

    By utilizing Funnels, ServiceNow customers can:

    • Identify where users drop off during interactions with the Virtual Agent, enabling targeted improvements.
    • Gather actionable metrics to enhance conversation flows and overall user experience.
    • Manage and edit funnels for ongoing optimization of Virtual Agent performance.

    Overall, the Funnels feature equips ServiceNow customers with the tools necessary to analyze and enhance their conversational interfaces effectively.

    Funnels provide cumulative filtering of conversation flows. Using funnels, you can identify whether your conversation flows are performing effectively when users chat with Virtual Agent.

    Figure 1. Funnels page
    Select the Funnels option on the menu to view the Funnels page.

    Video link to Funnels demo. Funnels demo Watch this video for an overview of Funnels.

    Overview of funnels

    Funnels filter conversation flows using steps that are defined when a user creates the funnel.

    A funnel can contain up to 10 filtering steps for a conversation flow. Each subsequent step further refines the results from the previous step. This type of cumulative filtering helps you to easily narrow down on the data of interest at each step of the conversation flow.

    When you run a funnel for a particular date range, the system displays the following metrics that show the number of users at each step:
    • The percentage and number of users who have used the specified conversation flow.
    • The percentage and number of users who proceeded to the next conversation step specified in the funnel.
    • The percentage of users who dropped off at a particular conversation step.
    • The percentage and number of users who completed all specified conversation steps in the flow.
    • The biggest drop-off point or step where users left the conversation flow.
    Each step in a funnel consists of the following:
    • Field: The item on which the step is evaluated.
    • Operator: A list of operators that is contextually generated based on the selected field.
    • Value: A text entry field or a list that is contextually generated based on the selected field.

    For more information about filtering options in steps, see Filter options in funnels.

    Use case for funnels

    Consider an example scenario where an admin has to get insights about how Virtual Agent is handling user queries in a conversation flow. To review the efficiency of the conversation flow, the admin might look for information such as the following:
    • What percentage or number of users have interacted with Virtual Agent.
    • Out of the users who interacted with Virtual Agent, what percentage or number of users have followed a specific node in the topic during the conversation.
    • Out of the users who used the specific node, what number of users requested for a transfer to a live agent.
    For example, see the following funnel for fetching metrics on a conversational flow that provides software access.
    Figure 2. Funnel
    The filter specifies the Software Access standard topic in which the Drive Flow Executed topic node has run and the user requested a transfer to a live agent.
    Here, the funnel has three filtering steps:
    • Step 1 fetches users who have followed the Software Access topic while interacting with the Virtual Agent.
    • Out of the retrieved users from step 1, step 2 fetches users who requested for a drive access in the Drive Flow Executed node.
    • Out of the retrieved users from step 2, step 3 fetches users who requested transferring to a live agent.

    Metrics for funnels

    Using Funnels, you can easily filter conversation flows and get information as metrics. Metrics indicate what percentage or number of users are active at each step of the conversation flow.

    You can improve the conversation flows based on the performance metrics derived from using funnels. The metrics help identify opportunities for improving conversation flows so that Virtual Agent can handle your user queries better.

    Using the previous example, that funnel displays the following metrics:
    Figure 3. Metrics for funnels
    The metrics show the percentage and number of users who made it through the steps and the step that experienced the biggest drop-off point for users.
    Here, the metrics indicate the following for the selected date range:
    1. 134 users followed the Software Access topic.
    2. Out of these 134 users, 85 users requested for a drive access.
    3. Out of these 85 users, 23 users requested for transferring to a live agent.

    These example metrics indicate an opportunity for improvement because 23 users requested for a transfer to a live agent.

    Other benefits of using funnels

    Users can create funnels to get insights on their conversation flows. Additionally, they can edit and delete existing funnels created by other users. For more information, see Create and manage funnels.

    You can compare the performance of previous and current conversation flows. Funnels show metrics for the specified date range. Additionally, it shows the comparison for the same number of days in the date range prior to the specified start date. You can know the increase or decrease in users who have made through all the steps.
    Figure 4. Previous metrics
    The change from previous metrics displays at the bottom of the card. For example, the percentage of users may display as a 25% increase from the previous 8 days.