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Back to Analytics Overview This page walks through creating a custom dashboard using a Banking AI Agent as an example to analyze performance metrics and identify trends.

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Problem Statement

As a Banking AI Agent client, you want to track the following metrics:
  • Dollar Value Breakup
  • Customer Type Summary
  • Task Fulfillment Trend
  • Top Failure Tasks
  • Channel Volume Trend
  • Filter the Messages using the Having clause
Once the dashboard is configured for all scenarios, it looks like the following: Configured Custom Dashboard

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Pre-requisites

  • AI Agent building knowledge.
  • Custom Meta Tags usage. See Custom Meta Tags for more information.
  • A Banking AI Agent with the following dialog tasks:
Transfer Funds: A dialog task that walks the user through the transfer steps. Transfer Funds This dialog includes a Script node to add the Custom Meta Tag TransferValue based on the amount transferred: 
if(context.entities.TransferAmount[0].amount > 50000){
   tags.addSessionLevelTag("TransferValue", "HighValue");
}

if(context.entities.TransferAmount[0].amount > 10000)
tags.addSessionLevelTag("TransferValue","MediumValue");

if(context.entities.TransferAmount[0].amount > 0)
tags.addSessionLevelTag("TransferValue","LowValue");
Transfer Funds Add Scripts Manage Payee: A dialog task for the user to manage their payee list. Manage Payee This dialog includes a Script that assigns a value to the CustomerType meta tag: 
if(context.custType == 3){
   tags.addUserLevelTag("CustomerType","Premium");
}
if(context.custType == 2){
   tags.addUserLevelTag("CustomerType","Gold");
};
if(context.custType == 1){
   tags.addUserLevelTag("CustomerType","Regular");
};

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Implementation

  1. From the left navigation panel, under Dashboard, click Custom Dashboard.
  2. Click Create a New Dashboard. Create New Dashboard
  3. Use the Add Widget button to add widgets for each scenario. You can add up to 4 widgets per row and organize them by moving within or across rows. Widgets can also be manually resized.
The following sections explain the configuration for each widget.

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Dollar Value Breakup

  1. Click Add Widget.
  2. Query setup:
    • Dataset: Analytics
    • Select: sessionTag.TransferValue as TransferValue, count(taskName)
    • Group By: sessionTag.TransferValue
    • Click Run to see the results.
  3. Widget setup:
    • Chart type: Pie chart
    • Dimension: TransferValue
    • Metrics: count(taskName)
    Dollar Value Breakup Query
  4. Click Preview, then click Update to Dashboard. Dollar Value Breakup Preview

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Customer Type Summary

This query provides usage statistics based on customer type.
  1. Click Add Widget.
  2. Query setup:
    • Dataset: Analytics
    • Select: userTag.CustomerType as CustomerCategory, count(taskName)
    • Group By: userTag.CustomerType
    • Click Run to see the results.
  3. Widget setup:
    • Chart type: Bar chart
    • Dimension: CustomerCategory
    • Metrics: count(taskName)
    Customer Type Summary
  4. Click Preview, then click Update to Dashboard.

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Task Fulfillment Trend

This query provides day-wise task success vs. failure trends.
  1. Click Add Widget.
  2. Query setup:
    • Dataset: Analytics
    • Select: date, metricType, count(metricType) as TotalTasks
    • Filter By: metricType = 'successtasks' or metricType = 'failedtasks'
    • Group By: date, metricType
    • Click Run to see the results.
  3. Widget setup:
    • Chart type: Bar chart
    • Dimension: date
    • Metrics: TotalTasks
    • Overlay: metricType
    Task Fulfillment Trend
  4. Click Preview, then click Update to Dashboard.

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Top Failure Tasks

This query shows the top tasks that are failing.
  1. Click Add Widget.
  2. Query setup:
    • Dataset: Analytics
    • Select: taskName as TaskName, count(taskName) as Failures
    • Filter By: metricType = 'failedtasks'
    • Group By: taskName
    • Click Run to see the results.
  3. Widget setup:
    • Chart type: Table chart
    • Dimension: TaskName and Failures
    Top Failure Tasks
  4. Click Preview, then click Update to Dashboard.

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Channel Volume Trend

This query provides channel-wise usage details.
  1. Click Add Widget.
  2. Query setup:
    • Dataset: Messages
    • Select: date, channel, count(messageId)
    • Group By: date, channel
    • Click Run to see the results.
  3. Widget setup:
    • Chart type: Line chart
    • Dimension: date
    • Metrics: count(messageId)
    • Overlay: channel
    Channel Volume Trend
  4. Click Preview, then click Update to Dashboard.
Your custom dashboard is ready. Set the Date Range to view the required metrics for each scenario.

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Filter the Messages using the Having Clause

This query uses a Having clause to display the number of messages per userId where the user has interacted with the AI Agent more than 12 times.
  1. Click Add Widget.
  2. Query setup:
    • Dataset: Messages
    • Select: count(messageId), userId
    • Group By: userId
    • Having: count(messageId) > 12
    • Click Run to see the results.
  3. Widget setup:
    • Chart type: Table chart
    • Dimension: count(messageId), userId
  4. The following shows results when retrieving the count of all messages grouped by userId (without the Having clause): Filter Messages Having Clause 1
  5. The following shows results when using the Having clause (only users with more than 12 messages): Filter Messages Having Clause 2
  6. Click Preview, then click Add to Dashboard. Filter Messages Having Clause Preview
  7. The Having clause widget is added to the dashboard: Filter Messages Having Clause Dashboard