The export functionality allows users to generate comprehensive reports based on the data from conversations, customers, and agents. The system supports two types of exports: a Generic Export for aggregated data, and a Single Conversation export, a focused, record-by-record analysis of an individual conversation.
Generic export
Exports can be generated only for filtered data based on user-defined filters. Unlike for other datastreams, scheduled export is not available for conversations.
The export includes the following sheets:
Conversation
The purpose of this sheet is to offer a summary of each conversation, along with its associated metadata and analysis results.
- This sheet contains conversations and aggregates data by conversation.
- Includes conversation-level metadata (e.g., conversation length, customer ID, agent ID)
- Results of text analysis at the conversation level, including:
- Aggregate sentiment scores Overall sentiment, Starting sentiment, Ending sentiment
- Recognized Custom Labels (CLs) for the entire conversation
- Reason of contact
Messages
The purpose of this sheet is to allow users to view each message in its full detail with associated metadata and analysis results.
- This sheet contains all individual messages in the dataset, one message per row.
- Metadata for each message (e.g., message timestamp, customer ID, agent ID, etc.)
- Results of text analysis, including:
- Sentiment score
- Recognized Custom Labels
Customer
The purpose of this sheet is to provide a summary of each customer’s interactions, including key insights based on the customer’s messages and text analysis results.
- This sheet aggregates data by customer ID.
- Customer-level metadata (e.g., total number of conversations, average conversation length)
- Results of text analysis aggregated by customer, including:
- Average sentiment score
- SUM sentiment score
- All recognized Custom Labels (CLs)
- Reason of contacts in conversations
Agent
The purpose of this sheet is to provide a summary of each agent’s performance, including insights based on the messages they’ve handled.
- This sheet aggregates data by agent ID.
- Agent-level metadata (e.g., total number of conversations handled, average conversation length)
- Results of text analysis aggregated by agent, including:
- Average sentiment score
- All recognized Custom Labels (CLs) associated with the agent’s conversations
- All recognized reason of contacts associated with the agent’s conversations
Single Conversation Export
The Single Conversation Export is designed for users who require a detailed export of one specific conversation. Available directly from the extended view of a conversation, this export includes every message within the conversation, as well as all related metadata and text analysis results.
The Single Conversation Export includes the following sheets:
Conversation
- Contains all messages from the specific conversation, listed message by message.
- Included Data:
- Message-level metadata (e.g., message timestamp, customer ID,customer name, agent ID, agent name)
Metadata
- Contains the aggregated metadata for the entire conversation.
- Included Data:
- Conversation-level metadata (e.g., conversation ID, customer ID, agent ID, total duration)
- Starting sentiment, closing sentiment, reason of contact
- Any other metadata provided alongside the conversation
Customer Text Analytics
- Structure: Contains all messages from the customer, listed row by row.
- Included Data:
- Message-level metadata (e.g., message timestamp)
- Results of text analysis for each customer message, including sentiment score, positive/negative phrases, and recognized Custom Labels.
Agent Text Analytics
- Structure: Contains all messages from the agent, listed row by row.
- Included Data:
- Message-level metadata (e.g., agent ID, agent name)
- Results of text analysis for each agent message, including sentiment score, positive/negative phrases, and recognized Custom Labels (CLs).