AI Agent Analytics

Your AI voice agents handle calls around the clock, but how well are they doing? The AI Agent Reports page gives you a complete picture of performance—from containment rates to customer sentiment—so you can fine-tune your agents and get more out of them.

You'll find it under Reports → AI Agents (the page lives at /reports/ai-agents). It's part of the Analytics suite and needs the AI Agents feature on your plan.

Key Performance Metrics#

When you open the AI Agent Reports page, you'll see six metric cards at the top. Each card shows the current value and compares it to the previous period so you can spot trends at a glance.

Total AI Calls tracks every call your AI agents handled during the selected time period. This number helps you understand your AI's workload and how it changes over time.

Containment Rate is the percentage of calls fully resolved by your AI without human intervention. Higher is better—it means your AI is handling more calls independently. Most businesses aim for 70% or higher.

Self-Service Actions counts successful completions like appointment bookings, information lookups, or call transfers. Each action represents a task your AI completed without human help.

Average Handle Time shows how long calls typically last. Shorter times often mean your AI is efficient, but context matters—complex inquiries naturally take longer.

Escalation Rate is the flip side of containment. It shows what percentage of calls got transferred to a human agent. Lower is better, but some escalation is normal for complex issues.

Cost Savings estimates how much you're saving by having AI handle calls instead of human agents. dialnote calculates this at $3 per contained call, which is the typical cost of a human-handled customer service call.

Understanding Call Outcomes#

Each AI-handled call falls into one of six outcome categories:

• Fully Contained – The AI resolved the call completely. This is your goal for most calls.
• Escalated to Human – The caller was transferred to a team member. Check escalation reasons to understand why.
• Voicemail Left – The caller chose to leave a voicemail rather than continue with the AI.
• Abandoned by Caller – The caller hung up before the AI could help them.
• No Answer – The call failed to connect before anyone answered.
• Call Failed – A technical issue prevented the call from completing.

The calls table shows every AI-handled call with details like caller info, duration, outcome, and sentiment. Click any row to see the full transcript and summary.

Sentiment Analysis#

dialnote analyzes each AI conversation to determine how the caller felt during the interaction:

• 😊 Positive – The caller sounded happy or satisfied
• 😐 Neutral – Neither positive nor negative
• 😟 Negative – The caller seemed frustrated or unhappy

The sentiment breakdown chart shows the distribution across all calls. High positive sentiment usually correlates with good containment rates and effective AI responses.

Escalation Analysis#

The escalation section shows two things: your containment rate trend over time and your top reasons for escalation.

The Containment Rate Chart plots daily (or weekly/monthly) containment percentages. Look for patterns—did a recent knowledge base update improve performance? Did a new product launch cause more escalations?

The Top Escalation Reasons table lists why calls ended or got transferred, with a count and percentage for each. The labels come straight from how each call disconnected. Common ones you'll see:

• Customer Requested Human – The caller asked to speak with a person
• Transferred to Human – The AI handed the call off to a team member
• Reached Voicemail – The call rolled to voicemail
• Customer Hung Up – The caller dropped before the AI finished
• AI Agent Ended Call – The agent wrapped up the conversation
• No Response from Customer – The caller went silent

Focus on your most common reason first. If "Customer Requested Human" tops the list, your AI might need a warmer personality or clearer answers. If a lot of calls end with no response, look at whether the agent's prompts are too long or confusing. Adjust the agent in AI Agent configuration or expand its knowledge bases.

AI Insights#

At the bottom of the dashboard, you'll find automatically generated insights split into two categories:

Top Opportunities highlights areas for improvement. These trigger on set thresholds—negative sentiment above 20%, escalation rate above 30%, or a containment rate that dropped more than 5% versus the previous period. You might see suggestions like:

• "Containment rate dropped by 8%—review your AI agent's knowledge base"
• "High escalation rate detected—31% of calls went to a human"
• "High negative sentiment detected—review call recordings to find pain points"

What's Working Well celebrates your wins:

• "Containment rate improved by 12% this week"
• "Escalation rate decreased from 35% to 27%"
• "Average handle time reduced by 45 seconds"

Filtering Your Data#

Use the filters at the top of the page to narrow your view:

• Date Range – Pick a preset (Today, Yesterday, Last 7 days, Last 30 days, Last 90 days, Month to date, Quarter to date, Year to date) or set a custom range
• Phone Numbers – Filter to specific phone numbers if you have multiple lines with AI agents
• Tags – Filter by AI call tags to focus on a topic, outcome, or priority
• Granularity – Switch between Daily and Weekly views for the trend charts

Your filter selections persist in the URL, so you can bookmark specific views or share them with teammates. The calls table has its own Export CSV option if you want the raw rows in a spreadsheet.

What's Next#

• AI Agents overview – set up and configure your voice and message agents
• Sentiment Analysis – how dialnote scores caller sentiment
• Call Scoring – AI call evaluation and quality scores
• Analytics overview – the full Reports suite, including team and call reports
• Disposition Codes – the Call Tags & FCR breakdown