시작
Kore.ai 대화형 플랫폼
챗봇 개요
자연어 처리(NLP)
봇 개념 및 용어들
빠른 시작 가이드
봇 빌더 접근 방법
사용 고지 사항 (영어)
Kore.ai 봇 빌더로 작업하기
봇 구축 시작하기
릴리스 정보
현재 버전 (영어)
이전 버전 (영어)

개념
디자인
스토리보드
대화 작업
개요
Using the Dialog Builder Tool
노드 유형
사용자 의도 노드
대화 노드
엔티티 노드
양식 노드
확인 노드
서비스 노드
봇 조치 노드
Service Node
WebHook 노드
스크립트 노드
노드 그룹화하기
Agent Transfer Node
사용자 프롬프트
음성 통화 속성
대화 관리
노드 및 전환
구성 요소 전환
컨텍스트 개체
이벤트 기반 봇 조치
지식 그래프
소개
지식 추출
지식 그래프 생성
봇에 지식 그래프 추가
그래프 생성
지식 그래프 작성
FAQ 추가
작업 실행
기존 소스에서 FAQ 구축
특성, 동의어 및 불용어
변수 네임스페이스 관리
수정
용어 편집 및 삭제
용어 편집 및 삭제
질문과 응답 편집
Knowledge Graph Training
지식 그래프 분석
봇 온톨로지 가져오기 및 내보내기
지식 그래프 가져오기
지식 그래프 내보내기
지식 그래프 생성
CSV 파일에서
JSON 파일
지식 그래프 생성
경고 작업
스몰 토크
Digital Skills
디지털 양식
Views
Digital Views
Panels
Widgets
기차
봇 성능 향상 – NLP 최적화
기계 학습
소개
모델 검증
기초 의미
지식 그래프 학습
특성
순위 및 해결
고급 NLP 설정
NLP 설정 및 지침
봇 인텔리전스
소개
컨텍스트 관리
컨텍스트 관리
대화 관리
다중 – 의도 탐지
엔티티 수정
기본 대화
정서 관리
어조 분석
Test & Debug
봇과 대화
발화 테스트
배치 테스트하기
대화 테스트
배포
채널 활성화
봇 게시
분석
봇 분석하기
Conversations Dashboard
Performance Dashboard
사용자 정의 대시보드
소개
맞춤형 메타 태그
사용자 정의 대시보드 생성 방법
Conversation Flows
NLP 지표
Containment Metrics
사용량 지표
스마트 봇
소개
범용 봇
소개
범용 봇 정의
범용 봇 생성
범용 봇 학습
범용 봇 커스터마이징
범용 봇용 추가 언어 활성화
스토어
Manage Assistant
플랜 및 사용량
Overview
Usage Plans
Support Plans
플랜 관리
봇 인증
다국어 봇
개인 식별 정보 삭제하기
봇 변수 사용
IVR 통합
일반 설정
봇 관리

방법
간단한 봇 생성하기
Design Conversation Skills
뱅킹 봇 생성
뱅킹 봇 – 자금 이체
뱅킹 봇 – 잔액 업데이트
Knowledge Graph (KG) 구축
스마트 경고를 예약하는 방법
Design Digital Skills
디지털 양식 설정 방법
디지털 보기 설정 방법
데이터 테이블에 데이터를 추가하는 방법
데이터 테이블 내 데이터 업데이트 방법
UI 양식에서 데이터 테이블에 데이터를 추가하는 방법
Train the Assistant
특성 사용 방법
의도와 엔티티에 대한 패턴 사용 방법
컨텍스트 전환 관리 방법
Deploy the Assistant
상담사 전환을 설정하는 방법
봇 기능 사용 방법
콘텐츠 변수 사용 방법
전역 변수 사용 방법
Kore.ai 웹 SDK 튜토리얼
Kore.ai 위젯 SDK 튜토리얼
Analyze the Assistant
사용자 정의 대시보드 생성 방법
사용자 지정 태그를 사용하여 봇 메트릭을 필터링하는 방법

API 및 SDK
API 참조
Kore.ai API 사용
API 목록
API 컬렉션
koreUtil Libraries
SDK 참조
상담사 전환을 설정하는 방법
봇 기능 사용 방법
콘텐츠 변수 사용 방법
전역 변수 사용 방법
소개
Kore.ai 웹 SDK 튜토리얼
Kore.ai 위젯 SDK 튜토리얼

관리
소개
봇 관리자 콘솔
대시보드
사용자 관리
사용자 관리
그룹 관리
역할 관리
봇 관리 모듈
등록
사용자 초대
사용자 등록을 위한 대량 초대 보내기
사용자 및 사용자 데이터 가져오기
Active Directory에서 사용자 동기화
보안 및 준수
싱글 사인 온 사용
보안 설정
Kore.ai 커넥터
봇 관리자용 분석
Billing (지원하지 않음)
  1. Docs
  2. Virtual Assistants
  3. Analyzing Your Bot
  4. Conversation Flows

Conversation Flows

Conversation Flows is a visual representation of the user journeys. The user interactions with the virtual assistants are analyzed by the platform to provide insights into the commonly used intents, paths traversed, and the drop-off points.

Note: The Conversation Flow feature is available only for the Published Bots.

The Conversation Flows provides the following views:

  • Intents Flow: This view provides an aggregated view of how each of the virtual assistant’s intents is executed. The intents are rolled up to the top-level, irrespective of what stage of a conversation they were initiated by the users. For example, intents invoked at the beginning of a conversation as well as any other stage during the conversation are all rolled up to the top level. This is the default view when you navigate to Conversation Flows. The View tasks by sessions toggle should be turned off to access this view.
  • Session Flow: This view provides the user journeys across the different intents in the order they were executed during a conversation session. Every flow starts with the intent used to initiate a conversation session and is followed by the other intents invoked in that session. Turn on the The View tasks by sessions toggle to access this view.

Access

To view the conversation flows, from the top menu, select Analyze -> Conversation Flows.

By default, the Intents Flow is presented along with the intents. Selecting any node will expand the flow to present the subsequent nodes in that path.

You can select session-wise view by toggling the View tasks by sessions option.

Purpose

The Conversation Flows can be used to identify the following:

  • Popular utterances – Utterances that are used to invoke the virtual assistant’s intents. Utterances are automatically grouped by similarity to provide a simplified view. 
  • False Positives – A quick review of the utterance groups will help you in identifying utterances going to an incorrect intent. You can analyze these utterances and make the necessary training updates. 
  • False Negatives – Utterances that did not result in any intent identification are presented as ‘Not Handled Utterances’. You can analyze these utterances and add them to the training corpus if required. 
  • Popular Intents and Flows – Helps in understanding the popular intents of your users and the flows used to execute these intents
  • Drop-off Points – Analyze the specific areas of the conversations that are resulting in drop-offs. A conversation is marked as drop-off if the user has abandoned it without providing a valid input. 
  • Agent Hand-offs – View the flows that are leading to agent hand-offs. Agent Hand-offs are conversations that resulted in navigating to the Agent Node from any of the Dialog Tasks.

Key Features

The following are the details presented along with the flows:

  • Utterance Groups– Every flow starts with an utterance from the user that initiated the conversation and expands to show further interactions. These utterances are grouped based on their similarity, ignoring the stop words and values for entities. These utterance nodes lead to one of the following intents:
    • Individual task intents,
    • FAQs,
    • Small Talk,
    • Help and
    • Not Handled utterances
  • Nodes are the individual points plotted on the conversation flow across various levels. Only the nodes that need input from the user are plotted on the graph. Following are the nodes that are plotted on the graph:
    • Intent Nodes: Includes Dialog as well as FAQ intents
    • Entity Nodes 
    • Confirmation Nodes 
    • User Input Nodes (using on_intent transition) 
    • Message Nodes 
  • Node Details: Following are the details presented for each node:
    • Percentage of total utterances leading to this Node. Click on percentage to display the list of user utterances that triggered this Node;
    • Node Name will be the task/entity name with the following details displayed on hover over the Node:
      • Conversation and Drop-offs details,
      • See Responses shows the User’s response, where applicable, to this Node;
    • Percentage of Drop-offs where applicable
    • Path Indicators are visible on the path between two nodes, where applicable, indicating:
      • any Script/Service Nodes visited during the transition between the nodes;
      • any Tasks executed as part of the Hold and Resume scenarios.
  • Chat History is viewed by clicking the utterance from the User Utterance window for either input (percentage) or response information.

Filters

The Conversation Flows can be filtered using one or more of the following criteria:

  • Date Period – Default is set to Last 7 days. You can change it to 24 Hrs. You can also set the start and end dates using the Custom option and selecting the dates from the calander.
  • Languages  – In case of multi-lang bots, you can filter the conversation flows by selecting one or more languages from the presented drop-down list. Default is All Languages.
  • Channels – Selecting one or more channels the bot was published on, you can filter the flow based upon the channel used by the user. Default is All Channels.
  • Custom Tags – In case you have added any meta/custom tags to your bot, you can filter based on the same. This requires the selecting of the Tag Name and the value for the tag you want to filter the conversations. By default, no tag is selected.

Conversation Flows

Conversation Flows is a visual representation of the user journeys. The user interactions with the virtual assistants are analyzed by the platform to provide insights into the commonly used intents, paths traversed, and the drop-off points.

Note: The Conversation Flow feature is available only for the Published Bots.

The Conversation Flows provides the following views:

  • Intents Flow: This view provides an aggregated view of how each of the virtual assistant’s intents is executed. The intents are rolled up to the top-level, irrespective of what stage of a conversation they were initiated by the users. For example, intents invoked at the beginning of a conversation as well as any other stage during the conversation are all rolled up to the top level. This is the default view when you navigate to Conversation Flows. The View tasks by sessions toggle should be turned off to access this view.
  • Session Flow: This view provides the user journeys across the different intents in the order they were executed during a conversation session. Every flow starts with the intent used to initiate a conversation session and is followed by the other intents invoked in that session. Turn on the The View tasks by sessions toggle to access this view.

Access

To view the conversation flows, from the top menu, select Analyze -> Conversation Flows.

By default, the Intents Flow is presented along with the intents. Selecting any node will expand the flow to present the subsequent nodes in that path.

You can select session-wise view by toggling the View tasks by sessions option.

Purpose

The Conversation Flows can be used to identify the following:

  • Popular utterances – Utterances that are used to invoke the virtual assistant’s intents. Utterances are automatically grouped by similarity to provide a simplified view. 
  • False Positives – A quick review of the utterance groups will help you in identifying utterances going to an incorrect intent. You can analyze these utterances and make the necessary training updates. 
  • False Negatives – Utterances that did not result in any intent identification are presented as ‘Not Handled Utterances’. You can analyze these utterances and add them to the training corpus if required. 
  • Popular Intents and Flows – Helps in understanding the popular intents of your users and the flows used to execute these intents
  • Drop-off Points – Analyze the specific areas of the conversations that are resulting in drop-offs. A conversation is marked as drop-off if the user has abandoned it without providing a valid input. 
  • Agent Hand-offs – View the flows that are leading to agent hand-offs. Agent Hand-offs are conversations that resulted in navigating to the Agent Node from any of the Dialog Tasks.

Key Features

The following are the details presented along with the flows:

  • Utterance Groups– Every flow starts with an utterance from the user that initiated the conversation and expands to show further interactions. These utterances are grouped based on their similarity, ignoring the stop words and values for entities. These utterance nodes lead to one of the following intents:
    • Individual task intents,
    • FAQs,
    • Small Talk,
    • Help and
    • Not Handled utterances
  • Nodes are the individual points plotted on the conversation flow across various levels. Only the nodes that need input from the user are plotted on the graph. Following are the nodes that are plotted on the graph:
    • Intent Nodes: Includes Dialog as well as FAQ intents
    • Entity Nodes 
    • Confirmation Nodes 
    • User Input Nodes (using on_intent transition) 
    • Message Nodes 
  • Node Details: Following are the details presented for each node:
    • Percentage of total utterances leading to this Node. Click on percentage to display the list of user utterances that triggered this Node;
    • Node Name will be the task/entity name with the following details displayed on hover over the Node:
      • Conversation and Drop-offs details,
      • See Responses shows the User’s response, where applicable, to this Node;
    • Percentage of Drop-offs where applicable
    • Path Indicators are visible on the path between two nodes, where applicable, indicating:
      • any Script/Service Nodes visited during the transition between the nodes;
      • any Tasks executed as part of the Hold and Resume scenarios.
  • Chat History is viewed by clicking the utterance from the User Utterance window for either input (percentage) or response information.

Filters

The Conversation Flows can be filtered using one or more of the following criteria:

  • Date Period – Default is set to Last 7 days. You can change it to 24 Hrs. You can also set the start and end dates using the Custom option and selecting the dates from the calander.
  • Languages  – In case of multi-lang bots, you can filter the conversation flows by selecting one or more languages from the presented drop-down list. Default is All Languages.
  • Channels – Selecting one or more channels the bot was published on, you can filter the flow based upon the channel used by the user. Default is All Channels.
  • Custom Tags – In case you have added any meta/custom tags to your bot, you can filter based on the same. This requires the selecting of the Tag Name and the value for the tag you want to filter the conversations. By default, no tag is selected.

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