πŸ“ŠPost-Conversation Analysis

Automatically extract structured data from every conversation and send results to external systems via webhook when a conversation ends.

The Conversation analysis tab lets you define what information to extract from conversations after they close, and optionally forward those results to an external webhook.

Conversation analysis tab showing Post-Conversation Analysis and Conversation Analysis Flow cards

The page has two sections:

  • Post-Conversation Analysis β€” define the variables the AI will extract from each conversation

  • Conversation Analysis Flow β€” configure a webhook URL to receive results automatically


How it works

The analysis runs automatically in two situations:

  • When the agent calls the Close Conversation action to end the interaction

  • When a conversation times out after 24 hours of inactivity

Once triggered, the AI reviews the conversation and extracts the values of any variables you have defined, then saves the results. If a webhook URL is configured, it sends the full payload to your endpoint immediately after.

No manual action is required.


Post-Conversation Analysis

Adding a variable

Click + Add Variable to open the variable configuration modal.

Add Variable modal showing Type, Name, Instruction, Scope and Required fields

Fill in the following fields:

Field
Description

Type

The data type for this variable (see types below)

Name

A unique identifier used in the analysis output (e.g. customer_email)

Instruction

A prompt telling the AI how to extract this value from the conversation

Scope

Persistent β€” carries across multiple sessions. Session β€” extracted fresh each conversation

Required

Whether this variable must be present in the analysis

Click Confirm to save the variable.


Variable types

Type dropdown showing all available variable types
Type
Use for

Text

Names, descriptions, open-ended answers

Selector

A value chosen from a fixed set of options

Boolean

Yes/No or true/false values

Number

Quantities, scores, or numeric values

Date

Calendar dates

DateTime

Date and time combined

Email

Email addresses

Phone

Phone numbers

URL

Web addresses

JSON

Structured data objects


Writing good instructions

The Instruction field is a prompt that tells the AI exactly what to look for. Be specific:

"Extract the email address the user provided during the conversation. If none was given, return null."

"Identify the product or service the user expressed interest in. Return only the product name."

"Determine if the user confirmed an appointment. Return true if confirmed, false otherwise."


Editing and deleting variables

Click any variable in the list to open the editor modal and modify its settings. To remove it, open the variable and click Delete.


Conversation Analysis Flow

Enter an HTTPS webhook URL in the Webhook URL field to have analysis results sent automatically when each conversation closes.

The URL must begin with https://. If left empty, results are saved but not forwarded anywhere.

The webhook sends a POST request with a 10-second timeout. If the request fails, the analysis is still saved β€” the failure does not affect conversation data.


Webhook payload

Field
Description

id

Unique identifier for this analysis record

conversation_id

The conversation this analysis belongs to

session_index

Session number, incremented automatically per conversation

success

Whether the conversation met its goal (evaluated automatically)

success_score

Confidence score from 0 to 100

success_reason

Explanation of the evaluation

variable_snapshots

Key-value map of variable names to their extracted values

created_at

Timestamp of when the analysis was created


Saving your configuration

Click Save Agent (top right) after making any changes to variables or webhook URL. Changes take effect on the next conversation that closes after saving.

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