Analytics

Track your AI agent's performance, understand customer behavior, and make data-driven decisions to improve your support operations.

Accessing Analytics #

Click Analytics in the left sidebar to view your performance dashboard.

Overview Dashboard #

Your analytics home shows the most important metrics at a glance.

Key Performance Indicators (KPIs) #

Total Conversations

How many customer interactions you've had
Tracks growth over time
Filter by date range to see trends

Resolution Rate

Percentage of conversations solved without human intervention
Good: 70-85%
Excellent: 85%+
Needs work: Below 60%

Average Response Time

How quickly customers get their first answer
Excellent: Under 3 seconds
Good: 3-10 seconds
Acceptable: 10-30 seconds

Customer Satisfaction

Based on customer ratings (👍 thumbs up/down)
Shown as percentage of positive ratings
Excellent: 90%+
Good: 75-90%
Needs improvement: Below 75%

Escalation Rate

Percentage of conversations requiring human help
Excellent: Under 15%
Good: 15-30%
High: Over 30% (consider more training)

Conversation Analytics #

Dive deeper into conversation data.

Conversation Volume #

Daily/Weekly/Monthly views:

Line chart showing conversation volume over time
Identify busy periods
Plan staffing accordingly
Spot unusual spikes or drops

By Channel:

Which channels get most traffic?
Web chat vs WhatsApp vs Email
Allocate resources appropriately

By Time of Day:

When are customers most active?
Peak hours vs quiet periods
Plan support coverage
Consider time zone differences

Conversation Outcomes #

Resolved Successfully:

AI handled completely
Customer got their answer
No escalation needed
✅ This is your goal!

Escalated to Human:

Needed human intervention
See reasons for escalation
Identify training opportunities

Abandoned:

Customer left before resolution
May indicate frustration
Could signal response time issues

Still Open:

Active conversations
Waiting for response
In progress

Conversation Duration #

Average conversation length:

How many messages exchanged?
How long did it take?
Shorter usually better (faster resolution)

Duration by Topic:

Simple questions: 1-3 messages
Complex issues: 5-10 messages
Very complex: 10+ messages

Use this to:

Identify areas needing better documentation
Find topics that consistently take longer
Optimize agent instructions

Agent Performance #

Track how each AI agent is performing.

Per-Agent Metrics #

For each agent, see:

Conversations handled - Volume
Resolution rate - Success without escalation
Response time - Speed
Customer satisfaction - Ratings
Most common topics - What they handle most

Comparing Agents #

If you have multiple agents:

Which performs best?
Which needs improvement?
Which handles specific topics better?
Should you consolidate or specialize?

Agent Improvement Tracking #

Week over week:

Is resolution rate improving?
Are response times faster?
Are customers more satisfied?

Track impact of changes:

Added new documents → Resolution rate up?
Updated instructions → Better responses?
New playbook → Fewer escalations?

Topic & Intent Analysis #

Understand what customers are asking about.

Intent Detection #

What do customers want?

Information seeking (most common)
Problem solving
Transaction/action needed
Complaint/frustration

Rising:

Topics increasing in frequency
May indicate new product launch
Or emerging issue needing attention

Falling:

Topics decreasing
May indicate successful resolution
Or reduced interest

Time-Based Analytics #

Response Time Analysis #

First response time:

How long until customer gets first reply
Goal: Under 5 seconds for AI

Average response time:

Throughout the conversation
Should stay consistently fast

Resolution time:

Total time from start to resolution
Lower is usually better (unless complex issue)

Peak Times #

Busiest hours:

When do most conversations happen?
Plan team coverage
Ensure AI is performing well during peaks

Quietest times:

Best for maintenance
Good for training updates
Review and optimization time

Day of Week Patterns #

Weekday vs Weekend:

Different volumes?
Different types of questions?
Adjust staffing and AI settings

Customer Satisfaction Metrics #

Rating System #

Customers can rate messages with:

👍 Helpful/good response
👎 Not helpful/poor response

Satisfaction Trends #

Track over time:

Is satisfaction improving?
Which responses get best ratings?
Which get worst ratings?

Feedback Comments #

When customers leave feedback:

Read the comments
Identify patterns
Address common complaints
Learn from praise

Net Promoter Score (NPS) #

If you ask "How likely are you to recommend us?":

Score of 9-10: Promoters
Score of 7-8: Passives
Score of 0-6: Detractors

NPS = % Promoters - % Detractors

Source Performance #

Document Usage #

Which documents are referenced most?

High usage = Very valuable
Zero usage = Maybe not needed or poorly tagged
High usage + low ratings = Needs improvement

For each document:

Times referenced
Success rate when used
Customer satisfaction
Last used date

Use this to:

Identify valuable documents
Find gaps in coverage
Update or remove unused docs
Improve unclear documents

Playbook Performance #

For each playbook:

Times triggered
Completion rate
Resolution rate
Average duration
Customer satisfaction

Insights:

Which playbooks work best?
Which need improvement?
Which are underutilized?
Should any be retired?

Channel Performance #

By Channel Comparison #

Compare metrics across channels:

Metric	Web Chat	WhatsApp	Email
Volume	500/day	200/day	100/day
Resolution	82%	75%	88%
Satisfaction	89%	85%	92%
Avg Response	3s	4s	2s

Insights:

Which channels are most efficient?
Where should you focus improvements?
Are expectations different by channel?

Custom Reports #

Creating a Custom Report #

Go to Analytics → Reports
Click Create Report
Choose metrics to include
Select date range
Add filters (agent, channel, topic)
Choose visualizations (charts, tables)
Save and generate

Report Types #

Summary Report:

High-level overview
Key metrics only
Great for executives

Detailed Analysis:

Deep dive into specific area
Multiple metrics and dimensions
For operations team

Performance Report:

Agent and playbook performance
Identify training needs
Quality assurance

Trends Analysis:

Changes over time
Seasonal patterns
Growth tracking

Scheduling Reports #

Set up automatic reports:

Create your custom report
Click Schedule
Choose frequency (daily, weekly, monthly)
Select recipients
Choose format (PDF, CSV, dashboard link)
Save schedule

Common schedules:

Daily summary report (every morning)
Weekly performance review (Monday mornings)
Monthly executive summary (first of month)

Exporting Data #

Export Options #

PDF Report:

Professional formatted document
Charts and graphs included
Great for presentations

CSV Export:

Raw data for analysis
Import into Excel/Google Sheets
Custom calculations

Interactive Dashboard:

Share live dashboard link
Updates automatically
Collaborative analysis

What You Can Export #

All conversations (with filters)
Performance metrics
Customer satisfaction data
Agent statistics
Topic analysis
Time-based data

Interpreting Your Data #

Understanding Trends #

Improving metrics:

✅ What changed recently?
✅ What should you keep doing?
✅ Can you apply this to other areas?

Declining metrics:

❌ What changed?
❌ External factors? (seasonality, marketing campaign)
❌ What needs to be fixed?

Red Flags to Watch #

Resolution rate dropping:

New types of questions?
Agent needs more training?
Documentation outdated?

Response time increasing:

Too many conversations?
Need to optimize?
Technical issues?

Satisfaction decreasing:

Read recent conversations
What's frustrating customers?
Quick wins to improve?

Escalation rate rising:

Why are more going to humans?
Can AI handle these?
Need new playbooks?

Using Analytics to Improve #

Weekly Review Routine #

Every week, check:

Key metrics vs last week
Any unusual spikes or drops?
Read 5-10 recent conversations
Check top escalation reasons
Review lowest-rated responses
Identify one thing to improve

Monthly Deep Dive #

Every month:

Full trend analysis
Compare to previous months
Review all agents and playbooks
Identify documentation gaps
Plan next month's improvements
Set specific goals

Setting Goals #

Example goals:

Increase resolution rate from 75% to 80%
Reduce escalation rate by 10%
Improve satisfaction score to 90%
Cut response time to under 3 seconds

Track progress:

Monitor weekly
Adjust tactics if not improving
Celebrate when goals reached!

Common Analytics Questions #

Why do my numbers seem low at first? #

Brand new agents need time to learn and optimize. Expect metrics to improve over 2-4 weeks as you:

Add more documents
Refine playbooks
Adjust agent instructions

What's a "good" resolution rate? #

Depends on your industry and complexity, but generally:

Simple FAQ-based support: 80-90%
E-commerce support: 70-85%
Technical support: 60-75%
Complex B2B: 50-70%

Should I worry about negative feedback? #

Some negative ratings are normal. Focus on:

Overall trends (improving or declining?)
Patterns in negative feedback
Opportunities for improvement

If satisfaction is 80%+, you're doing well!

How often should I check analytics? #

Daily: Quick glance at key metrics (5 min)
Weekly: Deeper review and planning (30 min)
Monthly: Comprehensive analysis (2 hours)

Can I compare my performance to others? #

Industry benchmarks coming soon! For now, compare to your own historical performance.

Next Steps #

Use insights to improve your Agents
Create better Playbooks based on data
Add Documents for low-performing topics
Monitor your Queue for escalation patterns