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. Builder
  5. Dialog Task
  6. Custom Meta Tags

Custom Meta Tags

While analyzing your Bot performances, you might want to give preference to or discard a particular scenario. For example, you might want to track how many people are booking tickets to Chicago. Or you might want to track how a specific user, a premium customer, requests are being catered to.

By adding Custom Meta Tags to the conversation flows, you will be able to profile bot user conversations and derive business-critical insights from your bot usage and execution metrics. Tags can be defined as part of the bot definition at any point of interest. When users interact with your bot, the platform will dynamically resolve these tags and adds them to chat transcripts so that you can later filter your conversations, and flows using those tags.

Defining Meta Tags

Kore.ai Bot builder platform allows you to add tags to various nodes in a dialog task like dialog node, entity node, etc.

This option is available from the Instance Properties tab

You can define these tags at three levels:

  • User Level: These tags can be added to the user’s profile information to capture user information. For example, to track conversations with a premium customer you will define a user-level tag with the user name or some qualifier as the value.
  • Message Level: These tags can be added to the message of the current node. If the current node is not associated with a message, then the tag gets added to the immediately previous node that has a message associated with it. From the above example, to track bookings to a specific city Chicago, you would be defining a Message Level tag.
    The platform will roll-up these message level tags to task level. That is if a task ends up as ‘Success/Failed Task’, then all the ‘message level’ tags emitted anywhere during the task execution will be associated with the Success/Failed Task event. You can filter Success Tasks as well as Failed Tasks using the message level tags emitted anywhere during the task execution
  • Session Level: These tags can be added at the current session of the user. These can be used to track the conversation sessions from a specific time frame say holiday season or a geographic domain.

The tag values will be emitted at run time:

  • For service, script, webhook and form nodes tags will be emitted on reaching the nodes;
  • For entity, message, confirmation, and other nodes tags will be emitted on the successful execution of the nodes.

You can also define Tags as key-value pairs from Script written anywhere in the application like Script node, Message, entity, confirmation prompts, error prompts, Knowledge Task responses, BotKit SDK, etc. This would be useful if you want conditional tagging.

Be aware that Script tagging would work only if the prompt where you added the tag script is triggered during the conversation.

Following script can be used for adding meta tags:

  • To add a User level tag:
    tags.addUserLevelTag("tagname","tagvalue")
  • To add a Session level tag:
    tags.addSessionLevelTag("tagname","tagvalue")
  • To add a Message level tag:
    tags.addMessageLevelTag("tagname","tagvalue")

The tagvalue can be a value or a variable name containing the value.

Updating Meta Tag Values

Chances are the Meta Tag values, once assigned, may be modified, for either business or other reasons. In such cases following points need to be noted:

  • The latest value assigned for a key will over-ride the previously assigned value.
  • The updates to the tags follow the following rules:
    • Message-level tags: You may set value for a tag multiple times within the script and the last set value will be assigned against the message. The value cannot be updated after the message is sent to the user
    • Session level tags: Value for a given tag can be set any number of times throughout the session. The last value assigned will be retained and this is the value that you should be using for all analytics purposes. Value cannot be updated after the session is closed.
    • User level tags: Value for a given tag can be set any number of times throughout the session. The last value assigned will be retained and this is the value that you should be using for all analytics purposes. Value can be edited at any time.

Using Meta Tags

Once you have defined the Meta Tags, you can:

  • Use the filter option from Bot Metrics to filter the conversations based upon the Meta Tag values. The export file for the Bot Metrics would include the Meta tag information, too. See here for more.
  • Use the filter option from Bot Builder Dashboard and Admin Console Dashboard to filter the Bot activity details based upon the Meta Tag values.
  • Use to filter the Chat History. Export of Chat History will also include the Meta Tag values. See here for more.
  • Filter the records from Conversation History API and Sessions API by meta tags.
Menu