OVERVIEW
Virtual Assistants
Kore.ai Platform
Key Concepts
Natural Language Processing (NLP)
Accessing Platform
VIRTUAL ASSISTANTS
Virtual Assistant Builder
Virtual Assistant Types
Getting Started
Creating a Simple Bot
SKILLS
Storyboard
Dialog Task
Introduction
Dialog Builder (New)
Dialog Builder (Legacy)
User Intent Node
Dialog Node
Entity Node
Supported Entity Types
Composite Entities
Supported Colors
Supported Company Names
Form Node
Logic Node
Message Nodes
Confirmation Nodes
Bot Action Node
Service Node
Custom Authentication
2-way SSL for Service nodes
Script Node
Agent Transfer Node
WebHook Node
Grouping Nodes
Connections & Transitions
Manage Dialogs
User Prompts
Knowledge Graph
Terminology
Building
Generation
Importing and Exporting
Analysis
Knowledge Extraction
Build
Alert Tasks
Introduction
Ignore Words and Field Memory
How to Schedule a Smart Alert
Small Talk
Digital Views
Overview
Configuring Digital Views
Digital Forms
Overview
How to Configure Digital Forms
NATURAL LANGUAGE
Overview
Machine Learning
Introduction
Model Validation
Fundamental Meaning
Introduction
NLP Guidelines
Knowledge Graph
Traits
Introduction
How to Use Traits
Ranking and Resolver
Advanced NLP Configurations
INTELLIGENCE
Overview
Context Management
Overview
Session and Context Variables
Context Object
How to Manage Context Switching
Manage Interruptions
Dialog Management
Sub-Intents & Follow-up Intents
Amend Entity
Multi-Intent Detection
Sentiment Management
Tone Analysis
Sentiment Management
Event Based Bot Actions
Default Conversations
Default Standard Responses
TEST & DEBUG
Talk to Bot
Utterance Testing
Batch Testing
Conversation Testing
CHANNELS
PUBLISH
ANALYZE
Overview
Dashboard
Custom Dashboard
Overview
How to Create Custom Dashboard
Conversation Flows
NLP Metrics
ADVANCED TOPICS
Universal Bots
Overview
Defining
Creating
Training
Customizing
Enabling Languages
Store
Smart Bots
Defining
koreUtil Libraries
SETTINGS
Authorization
Language Management
PII Settings
Variables
Functions
IVR Integration
General Settings
Management
Import & Export
Delete
Versioning
Collaborative Development
PLAN & USAGE
Overview
Usage Plans
Support Plans
Invoices
API GUIDE
API Overview
API List
API Collection
SDKs
SDK Overview
SDK Security
SDK App Registration
Web SDK Tutorial
Message Formatting and Templates
Mobile SDK Push Notification
Widget SDK Tutorial
Widget SDK – Message Formatting and Templates
Web Socket Connect & RTM
Using the BotKit SDK
Installing
Configuring
Events
Functions
BotKit SDK Tutorial – Agent Transfer
BotKit SDK Tutorial – Flight Search Sample Bot
Using an External NLP Engine
ADMINISTRATION
HOW TOs
Creating a Simple Bot
Creating a Banking Bot
Context Switching
Using Traits
Schedule a Smart Alert
Configure UI Forms
Add Form Data into Data Tables
Configuring Digital Views
Add Data to Data Tables
Update Data in Data Tables
Custom Dashboard
Custom Tags to filter Bot Metrics
Patterns for Intents & Entities
Build Knowledge Graph
Global Variables
Content Variables
Using Bot Functions
Configure Agent Transfer
Update Balance Task
Transfer Funds Task
RELEASE NOTES
  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.
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