Service Analytics helps you monitor, analyze, and improve your shop's performance using key chat metrics.

It helps you:

• Track response speed and coverage
• Review customer satisfaction trends
• Understand how chats are handled and resolved
• See how chat activity relates to purchases

How to Access Service Analytics

1. Go to Customer Messages
2. Click the Service Analytics icon in the top-right corner
   

You'll see analytics related to how your chats are handled.

Chats Overview

The Service Analytics page shows high-level performance metrics for your shop, including:

• Satisfaction rate
• 24-hour response rate
• Conversion rate

This is your main snapshot of chat performance.
Service Analytics Metrics

All Chats

The All Chats page lets you review individual conversations.
You can:

• Filter chats to focus on specific issues
• Transfer active, unresolved chats to another agent

Available Filters

• Chat Type
  • Helps identify chats that impact performance and need review.
• Chat Tag
  • Shows common topics customers contact you about.

If a chat is still active and unresolved, they can be transferred to any agent.

Chat Details

This view summarizes how chats were handled during the selected time period.
Chat Status Indicators

• 24h Human-Responded Chats
  • Chats answered by a human agent within 24 hours.
• Assistant-Solved Chats
  • Chats resolved by automated replies (such as FAQ cards).
  • Does not include greetings or off-hours auto replies.
• Late-Responded Chats
  • Chats answered by a human agent after 24 hours.
• Non-Responded Chats
  • Chats that required a human reply but never received one.

Agent details Agent details break down performance by each agent on your team and other performance metrics, including:

• 24-hour response rate
• Satisfaction rate
• Average response time
• Chat handling volume

Example Use Cases

Chat Volume and Response Gaps

You want to understand how many customers contacted your shop and how well those chats were handled.
By reviewing metrics such as 24-hour response rate, late-responded chats, and non-responded chats, you can see:

• How many chats required a human reply
• Which chats were answered after the 24-hour window
• Which chats were never answered

This helps you identify response gaps, improve reply times, and reduce future SLA misses.

Customer Satisfaction Trends

You want to understand how customers feel about the support your shop provides.
By reviewing satisfaction rate and customer ratings, you can identify patterns in positive or negative feedback.

• If your dashboard shows few or no ratings, it may indicate that chats were not responded to or did not progress far enough for customers to leave feedback.
• Improving response timeliness and engagement increases the likelihood of receiving ratings and helps you better understand what drives positive customer experiences.

Assistant vs. Agent Efficiency

You want to understand how effectively automation supports your customer service team.
By comparing assistant-solved chats to chats handled by human agents, you can see:

• How much workload is handled by automation
• Which types of inquiries still require human support

If assistant-solved chats are low or zero, this may indicate an opportunity to enable or optimize automated responses. Balancing assistant and agent coverage can help maintain faster response times and consistent coverage.

Chat Activity and Conversion Signals

You want to understand how customer conversations relate to purchasing behavior.
By reviewing potential customers, converted customers, and conversion rate, you can see whether chat interactions are leading to completed purchases.

• A low or 0% conversion rate may indicate that pre-purchase inquiries are not being answered in time or with enough clarity.
• Improving response speed and quality for pre-purchase questions can help customers make decisions with more confidence.