AI Sentiment Analysis

Understanding how a customer feels during a call is as important as understanding what they said. JustCall AI classifies sentiment in real time and tracks how it shifts throughout the conversation.

How Sentiment Analysis Works

1. The call is completed and transcribed.
2. AI analyzes the transcript segment by segment, evaluating tone, word choice, and conversational patterns.
3. Each segment receives a sentiment label: positive, negative, or neutral.
4. An overall sentiment score is assigned to the call.

What You See

Call-Level Sentiment

Every call in your call log displays a sentiment badge — a quick visual indicator of how the conversation went. Click into the call for the full breakdown.

Sentiment Timeline

Inside the call detail view, the Sentiment tab shows a timeline chart plotting sentiment across the call duration. This reveals:

• Where the conversation started (customer's initial mood).
• Turning points — the moment sentiment shifted from negative to positive, or vice versa.
• How the call ended — did the agent leave the customer in a better state than they started?

This timeline is especially useful for coaching. Managers can pinpoint the exact moment an agent recovered a frustrated customer or, conversely, where things went wrong.

Aggregate Trends

The Analytics → AI Insights → Sentiment dashboard shows sentiment distribution across your team:

• Percentage of calls classified as positive, negative, and neutral over a selected time period.
• Sentiment trends over time — is customer satisfaction improving or declining?
• Per-agent sentiment breakdown — which agents consistently handle calls that end positively?
• Sentiment by phone number or queue — identify which product lines or departments generate the most negative calls.

Practical Uses

Prioritize Callbacks

Filter your call log by negative sentiment to build a callback list of unhappy customers who may need additional attention. Addressing these quickly reduces churn risk.

Coach with Specifics

Instead of telling an agent to "be more empathetic," show them the sentiment timeline from a real call. Point to the moment sentiment dropped and discuss what happened.

Measure Campaign Impact

Running a promotion or making a policy change? Track sentiment trends before and after to measure how customers reacted.

Set Up Alerts

Create a workflow that triggers when a call ends with negative sentiment:

• Trigger: call.completed
• Condition: Sentiment = Negative
• Action: Notify the agent's manager via Slack or email with the call summary and recording link.

This ensures negative experiences get management attention immediately.

Accuracy Considerations

Sentiment analysis relies on language patterns. A few factors affect accuracy:

• Sarcasm is difficult for AI to detect. A customer saying "Great, just great" sarcastically may be classified as positive.
• Monotone delivery may be classified as neutral even if the words suggest frustration.
• Multilingual calls are analyzed in the detected language. Accuracy is highest in English and Spanish.

Review the sentiment timeline alongside the transcript for the most complete picture.

Plan Availability

Sentiment Analysis is available on the Business plan and above, or as part of the AI add-on.

What to Read Next

• AI Coaching Insights — Combine sentiment with talk ratios and other coaching metrics.
• AI Call Summaries — Summaries include overall sentiment.
• Workflow Actions — Automate follow-ups based on sentiment.

Sentiment analysis surfaces the emotional undercurrent of every call. Use it to catch problems early, coach effectively, and measure how your team makes customers feel.