Skip to main content

Chat Analytics

The Chat Analytics page provides comprehensive insights into your conversation volumes, customer engagement patterns, and support team activity. Track how many chats your team handles daily, identify peak hours, and visualize trends to optimize staffing and improve response times.

Chat Analytics Overview

Use the date range selector to compare metrics across different time periods and spot trends that can help you improve your customer service operations.

  • View total chats handled in any selected time window
  • Identify daily high and low periods for conversation volume
  • Spot patterns in customer engagement with the activity heatmap
  • Compare performance across different date ranges

Key Metrics

The Chat Analytics dashboard displays the following core metrics:

Total Chats

The overall number of customer conversations handled during the selected period.

Daily Breakdown

Chat counts for each day, helping identify daily trends and peak activity days.

Visualizations

The Chat Analytics page includes multiple visual representations of your data:

Chats by Date Chart

Line chart showing daily chat volumes over the selected period. Use this to identify:

  • Daily patterns and recurring trends
  • Peak days with high conversation volume
  • Weekly or seasonal variations in customer inquiries

Activity Heatmap

Heatmap showing activity by day of week and hour. Reveals:

  • Busiest days of the week
  • Peak hours for customer inquiries
  • Optimal times to schedule team members

Date Range Filters

Select from predefined date ranges to analyze different time periods:

  • Last 7 days — See recent weekly activity
  • Last 14 days — Compare two-week trends
  • Last 30 days — Monthly overview (default)
  • Last 60 days — Two-month analysis for broader patterns
  • Last 90 days — Quarterly trends and long-term patterns

Empty data tip: If your selected date range shows no chat data, try increasing the lookback period to see if data exists for earlier dates.

Using Chat Analytics Insights

Here are some ways to use Chat Analytics to improve your customer service:

Team Scheduling

Use the heatmap to identify peak hours and days to ensure adequate team coverage during busy periods.

Trend Identification

Monitor daily trends to spot seasonal patterns, promotional campaign impacts, or changes in customer behavior.

Performance Comparison

Compare metrics across different date ranges to measure the impact of process improvements or new features.

Capacity Planning

Understand your volume growth trajectory to plan team expansion and resource allocation.

Chat Analytics — Fiko Docs