Evaluations

Analyze the quality of your agent’s conversations with rich filters, scores, and per-conversation details.

Evaluations is a deep-dive analytics view of your agent’s completed conversations. Unlike the Supervise > Conversations view which shows all conversations at a glance, Evaluations is built for quality analysis—it surfaces scored, classified, and filterable conversation data so you can identify what’s working and what needs improvement.

What you’ll see

The Evaluations view shows a table of conversations with additional quality metrics attached to each one:

Column	Description
Channel	Where the conversation took place
Topic	The auto-classified topic of the conversation
Sentiment	Positive, neutral, or negative user sentiment
Task success	Whether the agent successfully resolved the user’s request
CSAT	Customer satisfaction score (if collected)
Date	When the conversation took place

Click any row to open the conversation panel and read the full transcript, summary, and resolution details.

Filters

Use the filter bar at the top to slice the data:

• Date range — select a period or use presets (MTD, QTD, YTD, custom)
• Channel — filter by the communication channel
• Topic — filter by one or more auto-classified topics
• Sentiment — positive, neutral, negative
• Task success — filter for resolved or unresolved conversations
• CSAT score — set a minimum and maximum CSAT threshold (1–5)
• Tags — filter by tags assigned to conversations
• Conversation IDs — jump directly to specific conversations

Metadata Filters

Below the standard filters, you can expand a Metadata Filters section to filter conversations by user metadata passed from your integrated channels (for example, customer_id, email, or any custom attribute).

• Metadata fields are grouped by channel (e.g., Freshchat Bubble, WhatsApp Meta).
• Type a value into any field to filter conversations where that metadata matches.
• Use the ✕ button on a channel header to clear all metadata filters for that channel.
• Collapse or expand each channel group to keep the filter bar organized.

Combine metadata filters with topic or sentiment filters for highly targeted analysis. For example, filter by a specific customer_id and negative sentiment to see all problematic conversations for a single customer.

The metadata fields displayed depend on what your integrated channels send. If no metadata has been received, the section shows an informational message.

Start by filtering for unresolved conversations with negative sentiment — this combination usually reveals the highest-priority issues to address in your agent’s knowledge or prompts.

Connection to Hotspots

Evaluations and Hotspots work together. When you click on a topic in the Hotspots view, you’re taken directly to Evaluations pre-filtered by that topic and date range. This lets you go from “this topic has a high priority score” to “let me read the actual conversations” in one click.

Best practices

• Review low CSAT conversations to understand what frustrated users and improve agent responses.
• Sort by task success to find patterns in unresolved conversations—are they all about the same topic?
• Use topic filters to focus your analysis on a specific area of your product or service.
• Use metadata filters to drill down into conversations for specific customers or user segments.
• Export data for external analysis or stakeholder reporting using the CSV export option in the table toolbar.