GETTING STARTED
Kore.ai XO Platform
Virtual Assistants Overview
Natural Language Processing (NLP)
Concepts and Terminology
Help & Learning Resources
Quick Start Guide
Accessing the Platform
Navigating the Kore.ai XO Platform
Building a Virtual Assistant
Using Workspaces
Release Notes
Current Version
Previous Versions
Deprecations
Request a Feature
CONCEPTS
Design
Storyboard
Overview
FAQs
Conversation Designer
Overview
Dialog Tasks
Mock Scenes
Dialog Tasks
Overview
Navigate Dialog Tasks
Build Dialog Tasks
Nodes & Connections
Overview
Node Types
Intent Node
Dialog Node
Entity Node
Entity Rules
Form Node
Confirmation Node
Message Nodes
Logic Node
Bot Action Node
Service Node
Webhook Node
Script Node
Process Node
Agent Transfer
Node Connections Setup
Sub-Intent Scoping
User Prompts
Voice Call Properties
Dialog Task Management
Supported Entity Types
Supported Company Names
Supported Colors
Knowledge AI
Introduction
Knowledge Graph
Knowledge Extraction
Build Knowledge Graph
Create Node Structure
Build the Graph
Add FAQs
Add FAQs from an Existing Source
Run a Task
Traits, Synonyms, and Stop Words
Manage Variable Namespaces
Update Knowledge Graph
Introduction
Move Question and Answers Between Nodes
Edit and Delete Terms
Edit Questions and Responses
Knowledge Graph Analysis
Knowledge Graph Import and Export
Prepare Data for Import
From a CSV File
From a JSON File
Importing Knowledge Graph
Exporting Knowledge Graph
Auto-Generate Knowledge Graph
Answer from Documents
Alert Tasks
Small Talk
Digital Skills
Overview
Digital Forms
Digital Views
Introduction
Widgets
Panels
Session and Context Variables
Context Object
Intent Discovery
Train
NLP Optimization
ML Engine
Overview
Model Validation
FM Engine
KG Engine
Traits Engine
Ranking and Resolver
Training Validations
NLP Configurations
NLP Guidelines
Intelligence
Introduction
Event Handlers
Contextual Memory
Contextual Intents
Interruption Management
Multi-intent Detection
Amending Entities
Default Conversations
Conversation Driven Dialog Builder
Sentinment Management
Tone Analysis
Default Standard Responses
Ignore Words & Field Memory
Test & Debug
Overview
Talk to Bot
Utterance Testing
Batch Testing
Conversation Testing
Conversation Testing Overview
Create a Test Suite
Test Editor
Test Case Assertion
Test Case Execution Summary
Glossary
Health and Monitoring
NLP Health
Flow Health
Integrations
Actions
HubSpot
Overview
Templates
Salesforce
Overview
Templates
ServiceNow
Overview
Templates
Agents
Custom
Genesys
Intercom
ServiceNow
External NLU Adapters
Overview
Dialogflow Engine
Test and Debug
Deploy
Channels
Publishing
Versioning
Analyze
Introduction
Overview Dashboard
Conversations Dashboard
Users Dashboard
Performance Dashboard
Custom Dashboards
Introduction
Custom Meta Tags
Create Custom Dashboard
Create Custom Dashboard Filters
NLP Insights
Conversations History
Conversation Flows
Conversation Insights
Feedback Analytics
Analytics Dashboard Filters
Usage Metrics
Containment 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
Get Started
Supported Components & Features
Manage Languages
Manage Translation Services
Multiingual Virtual Assistant Behavior
Feedback Survey
Masking PII Details
Variables
Collections
IVR Settings
General Settings
Assistant Management
Manage Namespace
Data
Overview
Data Table
Table Views
App Definitions
Data as Service
Sharing Data Tables or Views
HOW TOs
Build a Travel Planning Assistant
Travel Assistant Overview
Create a Travel Virtual Assistant
Design Conversation Skills
Create an ‘Update Booking’ Task
Create a Change Flight Task
Build a Knowledge Graph
Schedule a Smart Alert
Design Digital Skills
Configure Digital Forms
Configure Digital Views
Train the Assistant
Use Traits
Use Patterns
Manage Context Switching
Deploy the Assistant
Use Bot Functions
Use Content Variables
Use Global Variables
Use Web SDK
Build a Banking 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
Composite Entities
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
Intent Scoping using Group Node
Analyze the Assistant
Create a Custom Dashboard
Use Custom Meta Tags in Filters
Migrate External Bots
Google Dialogflow Bot
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
BotKit SDK Tutorial - Blue Prism
Widget SDK Tutorial
Web SDK Tutorial
ADMINISTRATION
Introduction to Admin Console
Administration Dashboard
User Management
Add Users
Manage Groups
Manage Roles
Data Tables and Views
Assistant Management
Enrollment
Invite Users
Send Bulk Invites
Import User Data
Synchronize Users from AD
Security & Control
Using Single-Sign On (SSO)
Two-Factor Authentication (2FA)
Security Settings
Cloud Connector
Analytics
Billing
  1. Home
  2. Docs
  3. Virtual Assistants
  4. Bot Settings
  5. Feedback Survey

Feedback Survey

The Kore.ai XO Platform allows you to design and create feedback surveys for products, services, and overall experiences using out-of-the-box templates on the web and mobile channels. You can configure a Virtual Assistant to launch these surveys at a certain point in a conversation or at the end of a conversation (when the end of conversation event is triggered). The NPS, CSAT, and Like/Dislike survey types are currently supported.

Key Feature Highlights

  1. The Feedback Module is use-case and channel-agnostic. But by default, it only shows text messages. You can always add additional channel-specific prompts to collect feedback from voice channels.
  2. When a feedback survey is created on the platform, all messages are in text format. The text from the platform gets converted into a voice using the ASR and TTS engines.
  3. You can leverage channel-specific configuration to modify the feedback prompts.
  4. Feedback flows are fully customizable.
  5. The Kore.ai XO Platform lets you configure feedback in two ways:
  • Using the built-in flows to collect the feedback and the new service type called feedback service to submit the feedback to the bots platform.
  • Collecting feedback from other sources that can be pushed to the platform as part of the conversation execution.
  1. Feedback Surveys get created as dialog tasks with a series of entities, service calls, and message notes. You have complete control of modifying the out-of-the-box messages, adding additional messages to specific channels, such as voice channels, and capturing the feedback on voice.
  2. You can use the automatic feedback template that the platform generates or build their flows and submit the feedback to the platform feedback service. Alternatively, it could be a hybrid approach where the feedback flow can emerge from or integrate with another flow.
  3. Once a customer responds to a Feedback Survey, the event displays on the chat transcript slider of the Conversations History Dashboard. Learn more.
  4. Additionally, you can filter and analyze Conversations (with feedback survey enabled) based on the Feedback Type, Response, and Score using prebuilt and custom filters. Learn more.
  5. The feedback response from a customer is captured and pushed to the platform for further analysis in three ways:
  • By creating a Dialog to capture feedback responses/scores and generate the required analytics to derive actionable insights on the Feedback Analysis Dashboard. Learn more.
  • By pushing feedback data to the platform using the Public API. Learn more.
  • By pushing feedback data via the Botkit. Learn more.
  1. In addition to the primary survey question, you can configure a Follow-up Question for negative feedback to gather specific details and better understand any primary survey issues.
  2. Additionally, you can set an Acknowledgement Message to customers after they complete the survey to show appreciation and let them know that it has been received.

Navigating to Feedback Survey

To navigate to the Feedback Survey feature, follow the steps below:

  1. On the Bot Builder, click the Build tab.
  2. Navigate to Configurations > Feedback Survey on the left navigation menu.

Feedback Template Types

The Platform provides the following in-built feedback template types, to create and define a feedback survey:

NPS Scale Categorization

Known as New Promoter Score, this is a standard customer experience metric that measures the experience and loyalty of customers based on their feedback response. For a single-question survey, respondents give a rating between 0 (not at all likely) and 10 (extremely likely), and based on their response, they fall into one of the following NPS score categories:

Customer Category NPS Score Description
Promoters 9 & 10 This score indicates a loyal customer who is satisfied with the conversation and is highly likely to return.
Passives 6,7, & 8 This score represents a satisfied customer who may or may not be willing to continue the conversation and return for a service.
Detractors 0,1,2,3,4, & 5 This score indicates that the customer is unsatisfied with the conversation and has given negative feedback. As a result, the customer will mostly not return to the platform and may detract other customers by sharing their experiences.

CSAT Score Categorization

CSAT or Customer SATisfaction is a customer experience metric that measures or quantifies how happy the customer is with a Virtual Assistant interaction. The customer is asked to rate on a five-point scale, 1 meaning very satisfied and 5 meaning very unsatisfied, for a survey question like “How satisfied were you with the conversation?” The response score is mapped to the relevant category as shown below:

Category Score
Very Satisfied 1
Satisfied 2
Neutral 3
Unsatisfied 4
Very Unsatisfied 5

 

Like/Dislike

The customer is asked to respond to the feedback survey by clicking a Like or Dislike icon. Like or Extremely Likely denotes the customer’s positive experience and is allocated a score of 1 internally. Dislike or Extremely Unlikely indicates a negative customer experience, and is allocated a score of 0 internally.

Feedback Survey Creation and Definition

To create a Feedback Survey on the Bot Builder, follow the steps below:

  1. Navigate to Build > Configurations > Feedback Survey.
  2. If this is your first feedback survey, click Add Feedback Survey on the Feedback Survey screen.
  3. Otherwise, click New Survey.

  4. In the Add Feedback Survey window, define the survey details and design, and launch the survey to be visible to customers.

The Feedback Survey definition and design flow steps are given below:

Step 1: Define the Survey Details

In this section, you can define a survey name and the type you want to use. To define the survey details, follow the steps below:

  1. Enter the Survey Name in the relevant text area.
  2. Select the Survey Type as either NPS, CSAT, or Like/Dislike. Based on your selection, the survey definition changes.
  3. Click Next to move to the next step.

Step 2: Define the Survey Design

You can define how to present the survey in the Survey Design stage which includes the following:

  • Gathering the customer’s feedback using one of the out-of-the-box default templates.
  • Defining the primary question that will be posed to the customer when the system triggers the feedback survey.
  • Setting the follow-up questions based on the feedback conditionally.

To define the survey design, follow the steps below:

  1. Select the relevant option in the Add Feedback Survey window based on how you want to create the survey.
  2. If you want to create a new Feedback Survey along with a Dialog Task (customizable) which will have the flow required to collect the feedback and capture the analytics, select Create a survey with a New Dialog and follow the steps below:
  • Enter the Dialog Name in the text area.
  • Set the default Primary Question to be posed to the customer for the selected survey type when it’s triggered.
  • Alternatively, modify/change the Primary Question in the text area.
  • The Primary Question response options the customer will see are displayed below based on the selected survey type:

NPS

CSAT

Like/Dislike

Note: The default response names provided for CSAT and the Like/Dislike types are editable; however, the scores set in the system cannot be changed for any survey type.

  1. To create your flow, select Create survey without Dialog and click Next
  2. Optional Step: To capture additional details from the customer for a negative feedback, configure the follow-up question with the steps below:
  • Enable the Follow-up Question option (default setting).
  • Define when to post the follow-up question by configuring the IF condition, where you must select the conditional option from the list for User Score.
  • Next, increment or decrement the feedback score counter for the selected condition to set the validation criterion.
  • Either edit the default follow-up question in the text area provided for the THEN clause or keep it unchanged.
  1. Modify the Acknowledgement Message in the text area or retain the default message to acknowledge the customer’s effort in taking the survey.
  2. Click Next to move to survey launch configuration.

Step 3: Define Launch Configuration

After defining the survey, you can choose how and when to launch the survey in one of the following ways with the Launch Configuration:

  1. Associate the survey with the end-of-task (conversation) event.
  2. Add the survey task as a sub-dialog to other primary tasks.

To configure the feedback survey launch, follow the steps below:

  1. Select one of the following options:
  • Launch after End of Task: The dialog task is considered as the ‘End of Task‘ event, and the survey is triggered at the end of every conversation. When selected, End of Task (End of Conversation Event) under Intelligence > Events > End Of Task will be overridden and the feedback survey is launched. Through the survey dialog you’ve created in the previous step.
  • I will decide how to launch the Survey: You can manually initiate the feedback survey at any time by using the associated dialog task in the Kore.ai XO platform. A dialog task will be made available under Build → Conversational Skills. This allows you to control when the survey is launched and gather feedback at your own convenience.
  1. Click Create to launch the feedback survey.

A success confirmation message, as shown below, is displayed with your survey details.

Feedback Survey Dialog Flow

After you’ve created the survey, you can view the built-in survey flow as a dialog task under Build > Conversational Skills > Dialog Tasks on the left menu.

The Task Flow will include a combination of Entity, Message, and Service nodes to represent the survey flow.

You can customize the dialog flow as per your need by changing the dialog flow definition fields.

Important

  • Feedback Service is introduced as the new Service Type option under General Settings. You can use this service to submit feedback on the surveys you may have captured using your custom flows.
  • You can invoke feedback as a sub-dialog from any other point in the conversation where you would like to capture the feedback.
Menu