GETTING STARTED
Kore.ai XO Platform
Virtual Assistants Overview
Natural Language Processing (NLP)
Concepts and Terminology
Quick Start Guide
Accessing the Platform
Working with the Builder
Building a Virtual Assistant
Using Workspaces
Release Notes
Current Version
Previous Versions
Deprecations

CONCEPTS
Design
Storyboard
Dialog Tasks
Overview
Dialog Builder
Node Types
Intent Node
Dialog Node
Entity Node
Form Node
Confirmation Node
Message Nodes
Logic Node
Bot Action Node
Service Node
Webhook Node
Script Node
Group Node
Agent Transfer
User Prompts
Voice Call Properties
Dialog Task Management
Connections & Transitions
Component Transition
Context Object
Event Handlers
Knowledge Graph
Introduction
Knowledge Extraction
Build Knowledge Graph
Add Knowledge Graph to Bot
Create the Graph
Build Knowledge Graph
Add FAQs
Run a Task
Build FAQs from an Existing Source
Traits, Synonyms, and Stop Words
Manage Variable Namespaces
Update
Move Question and Answers Between Nodes
Edit and Delete Terms
Edit Questions and Responses
Knowledge Graph Training
Knowledge Graph Analysis
Knowledge Graph Import and Export
Importing Knowledge Graph
Exporting Knowledge Graph
Creating a Knowledge Graph
From a CSV File
From a JSON file
Auto-Generate Knowledge Graph
Alert Tasks
Small Talk
Digital Skills
Digital Forms
Views
Introduction
Panels
Widgets
Train
Introduction
ML Engine
Introduction
Model Validation
FM Engine
KG Engine
Traits Engine
Ranking and Resolver
NLP Configurations
NLP Guidelines
Intelligence
Introduction
Contextual Memory
Contextual Intents
Interruption Management
Multi-intent Detection
Amending Entities
Default Conversations
Sentinment Management
Tone Analysis
Test & Debug
Talk to Bot
Utterence Testing
Batch Testing
Conversation Testing
Deploy
Channels
Publish
Analyze
Introduction
Conversations Dashboard
Performance Dashboard
Custom Dashboards
Introduction
Meta Tags
Dashboards and Widgets
Conversation Flows
NLP Metrics
Containment Metrics
Usage Metrics
Smart Bots
Universal Bots
Introduction
Universal Bot Definition
Universal Bot Creation
Training a Universal Bot
Universal Bot Customizations
Enabling Languages
Store
Manage Assistant
Plan & Usage
Overview
Usage Plans
Support Plans
Invoices
Authorization
Multilingual Virtual Assistants
Masking PII Details
Variables
IVR Settings
General Settings
Assistant Management
Data Table
Table Views
App Definitions
Sharing Data Tables or Views

HOW TOs
Build a Flight Status Assistant
Design Conversation Skills
Create a Sample Banking Assistant
Create a Transfer Funds Task
Create a Update Balance Task
Create a Knowledge Graph
Set Up a Smart Alert
Design Digital Skills
Configure Digital Forms
Configure Digital Views
Add Data to Data Tables
Update Data in Data Tables
Add Data from Digital Forms
Train the Assistant
Use Traits
Use Patterns for Intents & Entities
Manage Context Switching
Deploy the Assistant
Configure an Agent Transfer
Use Assistant Functions
Use Content Variables
Use Global Variables
Web SDK Tutorial
Widget SDK Tutorial
Analyze the Assistant
Create a Custom Dashboard
Use Custom Meta Tags in Filters

APIs & SDKs
API Reference
API Introduction
API List
API Collection
koreUtil Libraries
SDK Reference
SDK Introduction
SDK Security
SDK Registration
Web Socket Connect and RTM
Using the BotKit SDK

ADMINISTRATION
Introduction
Assistant Admin Console
Administration Dashboard
User Management
Add Users
Manage Groups
Manage Roles
Assistant Management
Enrollment
Invite Users
Send Bulk Invites
Import User Data
Synchronize Users from AD
Security & Compliance
Using Single-Sign On
Security Settings
Cloud Connector
Analytics
Billing
  1. Home
  2. Docs
  3. Virtual Assistants
  4. Analyzing Your Bot
  5. Performance Dashboard

Performance Dashboard

Once a virtual assistant (VA) is published then, there will be n-number of users who will be interacting with it. In such scenarios it becomes essential to monitor the performance of the dashboard so that it could be improved over a period of time. 

To understand the performance of a virtual assistant, a VA designer needs insights of how many intents were identified, how many tasks were successfully completed using the virtual assistant, how many services or scripts failed during the interactions etc. You can use the Performance dashboard to get all the insights related to performance of a virtual assistant. These insights will help a VA designer to improve the performance of the virtual assistant by making necessary changes to it. 

Note

  • Performance Dashboard is only available post 9.2 release, i.e post-April 09, 2022.
  • Usage Metrics and Containment Metrics will be deprecated in future releases. 

To navigate to the Performance Dashboard you need to click on Analyze tab on the top menu and click on Performance Dashboard as shown in the figure below:

Performance Dashboard Metrics

The Performance Dashboard provides insights to understand the virtual assistant’s NLP performance and integration metrics.

The Performance Dashboard is categorized into four categories to identify how a virtual assistant performs. These categories are mentioned below:

Intent Identification Rate

This section of the dashboard provides the information of the number of intents that were classified and unclassified. An intent refers to the goal the customer has in mind when typing in a question or comment. While entity refers to the modifier the customer uses to describe an issue, intent is “What they really mean”. To know more about intents refer here 

Below are the widgets that are used to provide insights:

Metric Description
Intent Identification Rate A scorecard which displays the percentage and the number of intents that were identified in a duration. It also displays the percentage increase or decrease in identifying intents from the last selected period.
Intent Identification Trend A line chart that displays the total number of intents that were classified by the virtual assistant versus the total number of intents that were unclassified by the virtual assistant over a period of time.
Popular Intents A table that provides the insights to the number of times an intent was successfully identified from the user utterances.
Popular Unidentified Utterances A table that displays the number of utterances that did not identify an intent. The utterances are grouped by their similarity. 

Goal Completion Rate

The goal completion metrics provide insights as to how many tasks were completed in a period of time by a virtual assistant. This metrics shows all types of tasks which includes the completed tasks, abandoned tasks, incomplete tasks and failed tasks.

Listed below are the widgets that could help in providing information about these details:

Metric Description
Goal Completion Rate A scorecard which displays the percentage and the number of task executions that were successfully completed in a duration. It also displays the percentage increase or decrease in completing tasks from the last selected period.
Goal Completion Trend A line chart that plots the successful and failed task executions over a period of time.
Task Performance A table that provides insights of the number of successful and failed task executions per task for a selected duration.
Failure Point Analysis A table that displays the number of times a task has failed at various nodes.

API Execution Rate

This section of the dashboard provides the information of the number of APIs that were successfully executed and failed. While configuring a dialog task often there are needs to use a Service node that is used to make REST or SOAP requests to a third party web-services. To know more about service nodes refer here.

Below are the widgets that are used to provide information about API performance:

Metric Description
API Performance Rate A scorecard which displays the percentage and the number of service calls that were executed successfully. It also displays the percentage increase or decrease of APIs that were executed successfully from the last selected period.
Service Execution Trend A line chart that plots the trend of successful and failed service execution over a period of time.
Service Performance A table that displays the number of times a service node is executed, their status, and the average response time of executing the API.

Script Execution Rate

This section of the dashboard provides the information of the number of Scripts that were successfully executed and failed. A Script allows you to write JavaScript code in a dialog task. To know more about script nodes please refer here.

Below are the widgets that are used to provide information about Script performance.

 

Metric Description
Script Performance Rate A scorecard which displays the percentage and the number of scripts that were executed successfully. It also displays the percentage increase or decrease of Scripts that were executed successfully from the last selected period.
Script Execution Trend A line chart that plots the trend of successful and failed script execution over a period of time.
Script Performance A table that displays the number of times a script node is executed, their status, and the average response time executing the script.

Filter Criteria

You can filter the data based on the following parameters.

  • Date:  Filtering the data based on time period in the date filter will display all the conversation sessions that have started in the selected time period. The dashboard displays the data in the local timezone. By default, the dashboard will display past 24 hours data. . By default it is set to GMT timezone. you can change it by selecting the appropriate zone.  Below are the filter criterias that could be applied as a date filter.
    • 24 Hours – Data aggregated during the immediately preceding 24 hours is displayed. This is the default setting. 
    • 7 Days – Data aggregated over the past seven days is displayed. The start date is from the day when you selected this filter. For example, If today’s Date is May-17-2022  then selecting the past 7 days will display the record between May-11-2022 to May-17-2022.
    • Custom – You can also choose a custom date range to filter the records. You need to choose the start date and end date in the calendar and click on the Select button to filter the records. You can select a maximum of 90 days duration as a filter. 
      Note: The date format is MMM-DD-YYYY
  • Session Type: You can filter based on the Session Type.:
    • Interactive sessions – conversations that include one or more messages from the user
    • Non-interactive sessions – conversations that do not include any message from the user.
      Note: The Developer Interactions are not included in the Session Type filter. Billing session is completely different from the Conversation Session.
  • Session Status: You can also filter by Session Status:
    • Active Sessions: These are the ongoing conversations where the users are interacting with the virtual assistant.
    • Closed Sessions: These  are the conversations that are completed between the virtual assistant and the users.  To know when a session is considered as closed, click learn more.
  • Tag Based: You can filter the dashboard using meta tags added at a message, user, or session level. Multiple tags can be selected under the filter criteria, an ‘and‘ condition will be applied across multiple fields selected for filtering. 

The following table gives the widget-wise applicability of meta tags on the dashboard.

Widget Type Session Tags User Tags Message Tags
Successful Tasks Applicable Applicable Not Applicable
Sessions Applicable Applicable Not Applicable
Messages & Conversation Sessions Applicable Applicable Applicable for Chats
Intent Recognized vs. Failed Applicable Applicable Not Applicable
Top Tasks Applicable Applicable Not Applicable
Top Channels Applicable Applicable Not Applicable
Agent Transfer Applicable Applicable Not Applicable
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