- Release notes
- Overview
- Getting started
- Marketplace Vendors
- Marketplace Customers
- Publishing Guidelines
- Publishing Guidelines for Ready-to-go Automations
- Publishing Guidelines for Solution Accelerators
- Publishing Guidelines for Integration Service Connectors
- Publishing Guidelines for Process Mining app templates
- Security & IP Protection
- Other UiPath Listings
- Node-RED
- Analyze general tone
- Personality insights
- Analyze customer engagement
- Setup
- Teams
- Microsoft Teams scope
- Create team
- Create team from group
- Get team
- Get teams
- Channels
- Create channel
- Delete channel
- Get channel
- Get channels
- Update channel
- Chats
- Get chat
- Get chats
- Get chat members
- Messages
- Get message
- Get messages
- Get message replies
- Reply to message
- Send message
- Events
- Create event
- Delete event
- Get event
- Get events
- Users
- Get user presence
- How it works
- Technical references
- Get started
- About
- Setup
- Technical references
- Azure Form Recognizer scope
- Activities
- Analyze form
- Analyze form async
- Get analyze form result
- Analyze receipt
- Analyze receipt async
- Get analyze receipt result
- Analyze layout
- Analyze layout async
- Get analyze layout result
- Train model
- Get models
- Get model keys
- Get model info
- Delete model
- Connectors
- How to create activities
- Build Your Integration

Marketplace user guide
Analyze customer engagement

Analyzes customer service and support conversations such as transcripts of a conversation between a call center agent and a customer. There are 7 tones that can be identified:
Sad, Frustrated, Satisfied, Excited, Polite, Impolite, Sympathetic
Each conversation analyzed may contain at most 50 utterances.
Each utterance may contain at most 500 characters.
Properties
Common
- DisplayName - The display name of the activity.
Credentials
- APIKey - The API key generated for your Tone Analyzer instance on IBM Cloud.
- URL - The URL generated for your Tone Analyzer instance on IBM Cloud.
Input
-
ConversationJSON - The conversation to analyze as a stringified JSON object having the following format:
{ "utterances": [ { "text": "Hi, I can't get your software to work.", "user": "customer" }, { "text": "OK, what seems to be the problem?", "user": "agent" }, ... ] }{ "utterances": [ { "text": "Hi, I can't get your software to work.", "user": "customer" }, { "text": "OK, what seems to be the problem?", "user": "agent" }, ... ] } -
ConversationTable - The conversation to analyze as a DataTable with columns Speaker & Utterance. The Speaker column may contain only Agent & Customer. For example:
Speaker Utterance Customer "Hi, I can't get your software to work." Agent "OK, what seems to be the problem ... ... Important:Note that ConversationJSON and ConversationTable represent the same input but in different formats. The two are mutually exclusive.
Misc
- InLanguage - The language of the inputted text.
- OutLanguage - The language in which the outputted tones are written.
- Private - If selected, the values of variables and arguments are no longer logged at Verbose level.
Output
- Utterance Tones - An
Array<SentenceTone>variable holding analyses of each individual utterance in the submitted conversation.SentenceTonevariables contain:- SentenceNumber - The index (starting at 0) at which the described utterance appears in the conversation.
- Text - The isolated text of the utterance.
- ToneName - The name of the tone found in this utterance.
- Confidence - A value between 0 and 1 indicating the Tone Analyzer's confidence that the tone selected accurately describes the utterance.