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. How Tos
  5. Using Custom Tags to filter Assistant Metrics

Using Custom Tags to filter Assistant Metrics

In this How-To, we will explore a scenario in a Banking Bot, where, various metrics will be used to analyze the bot performance.

For details on what Bot Metrics are and how they are implemented in the Kore.ai Bots platform, refer here.

Problem Statement

A Banking Bot client can track the following metrics:

  • Frequent Intents used by customers;
  • Usage split based on the customer type;

This document gives a detailed step-by-step approach to viewing the above statistics from the Bot Metrics page and apply filters based on Custom Meta Tags.

Pre-requisites

  • Bot building knowledge.
  • Custom Meta Tags usage, refer here for more.
  • A Banking Bot with the dialogs as mentioned below:
    • Transfer Money – Dialog task walking the user through the steps in transferring money.
      In this diaog, we have included a Script node to add Custom Meta Tag, TransferValue, based upon the amount transferred. Following script was used:

      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");

    • Manage Payee – For the user to manage their payee list.

      Here we have a Script assigning customerType meta tags:

      if(context.custType == 3){
         tags.addUserLevelTag("CustomerType","Premium");
      }
      if(context.custType == 2){
         tags.addUserLevelTag("CustomerType","Gold");
      };
      if(context.custType == 1){
         tags.addUserLevelTag("CustomerType","Regular");
      };

Implementation

Let us consider how each of the metrics mentioned in the problem statement can be viewed from the Metrics.

  1. From the left navigation panel, under Analyze click Metrics.
  2. The page will display the Intent found metrics to include successful utterances, intents, userid of the user,  and other details.
  3. These are the successful intents in the past one week as captured by the Bot.
  4. Click the Filter button to customize the report.
  5. Customize the Date periodLanguangesChannel, and the Task/Intent you want to capture.
  6. Since we want to track the Transfer Money intent, we have selected accordingly.
  7. We want the report of all the interactions by the Gold and Premium customers doing High Value money transfers.
  8. For this select the Custom Tags as follows (you can select the tag name and tag value from the type ahead drop down:
    • Customer Type – Gold, Premium
    • Transfer Value – HighValue

  9. On Applying the filter, you will see the updated Metrics page. Note that tags filter is applied only on the published version on the bot.
  10. You can repeat the above steps for all metrics like Intent not foundFailed task, etc..
Menu