Post-Call Metrics | Smallest AI Docs

Post-call metrics let you pull specific insights from conversations after they end. Define what you want to know — satisfaction scores, call outcomes, issue categories — and Atoms analyzes each call to fill in the answers.

Location: Left Sidebar → Post Call Metrics

Post-call metrics list — Post-call metrics dashboard

How It Works

You define metrics — What questions do you want answered about each call?
Call ends — Conversation completes normally
AI analyzes — Atoms reviews the transcript against your metrics
Data populated — Your metrics get filled in automatically
Access anywhere — View in logs, receive via webhook, export

Creating a New Metric

Click the Add Metrics + button to open the configuration panel. You’ll see two options:

Disposition Metrics

Templates

Build a custom metric from scratch. Fill in the Identifier, Data Type, and Prompt — see details below.

Use Add Another + to create multiple metrics at once.

Don’t forget to hit Save in the Disposition tab once you’re done.

Configuring a Metric

Each metric needs three things:

Field	Required	Description
Identifier	Yes	Unique name for this metric. Lowercase, numbers, underscores only.
Data Type	Yes	What kind of value: String, Number, or Boolean
Prompt	Yes	The question you want answered about the call

Identifier

This is the key used to reference the metric in exports, webhooks, and the API.

customer_satisfaction
call_outcome
follow_up_needed

Naming rules: Lowercase letters, numbers, and underscores only. No spaces or special characters.

Data Type

Type	Use for	Example values
String	Free text, categories	”resolved”, “escalated”, “billing issue”
Boolean	Yes/no questions	true, false
Integer	Whole numbers, scores	1, 5, 10
Enum	Fixed set of options	One of: “low”, “medium”, “high”
Datetime	Dates and times	”2024-01-15T10:30:00Z”

Prompt

This is the question the AI answers by analyzing the transcript. Be specific.

Good prompts:

“Did the agent acknowledge and respond to customer concerns effectively?”
“Rate customer satisfaction from 1 to 5 based on tone and words used.”
“What was the primary reason for this call? Options: billing, technical, account, other”

Vague prompts to avoid:

“Was it good?”
“Customer happy?”

Start with 3-5 metrics. Too many can slow analysis and clutter your data. Add more as you learn what insights matter most.

Example Metrics

Call Outcome

Satisfaction Score

Follow-Up Needed

Issue Category

Field	Value
Identifier	`call_outcome`
Data Type	String
Prompt	”What was the outcome of this call? Options: resolved, escalated, transferred, abandoned, callback_scheduled”

Conversation Logs

View metrics for individual calls

Analytics Dashboard

See aggregated trends across calls