Metrics Compare

Metrics Compare

Compare support performance between two time periods to identify improvements, regressions, and trends. Surface actionable insights from the data.

Process

Step 1: Parse Periods

Interpret the user's request into two concrete date ranges. Common patterns:

• "this week vs last week" — Current Mon-Sun vs previous Mon-Sun
• "March vs February" — Full calendar months
• "last 7 days vs previous 7 days" — Rolling windows
• "this quarter vs last quarter" — Q1/Q2/Q3/Q4 boundaries

Use the configured timezone (default: UTC) for all date calculations. If the user provides ambiguous ranges, ask for clarification before proceeding.

Step 2: Fetch Data

1. Fetch metrics for Period A using get_metrics with the first date range
2. Fetch metrics for Period B using get_metrics with the second date range
3. Fetch channel analytics for both periods using get_channel_analytics to break down by channel
4. Fetch agent performance for both periods using get_agent_performance to see individual trends
5. Optionally fetch trend data using get_trends for a continuous view across both periods

Step 3: Calculate Deltas

For each metric, compute:

• Absolute change: Period B value minus Period A value
• Percentage change: ((Period B - Period A) / Period A) * 100
• Direction indicator: Up arrow for increase, down arrow for decrease, right arrow for no change

Step 4: Assess Significance

Apply the significance threshold to highlight meaningful changes:

• Changes greater than +10% or less than -10% are flagged as significant
• Changes between -10% and +10% are considered stable
• For metrics where lower is better (response time, resolution time), a decrease is positive

Step 5: Present Comparison

Format the results as a side-by-side comparison table with insights.

Delta Calculation Rules

• Percentage change: Always calculate relative to Period A (the earlier period)
• Division by zero: If Period A value is 0, show "New" instead of a percentage
• Rounding: Round percentages to one decimal place
• Direction context: For some metrics, "up" is good (resolution rate, CSAT) and for others "up" is bad (response time, open conversations). Apply appropriate color coding in the assessment.

Output Format

Metrics Comparison: [Period A Label] vs [Period B Label]

Key Insights:

• First response time improved significantly (-35.7%) — likely due to AI automation increase
• Conversation volume is up 18.3% — monitor team capacity
• CSAT improved slightly but within normal variance

Significant Changes (>10%):

• Total conversations: +18.3%
• Resolved conversations: +21.1%
• First response time: -35.7% (improvement)
• AI auto-resolved: +18.4%

When reporting channel breakdowns, add a secondary table showing per-channel comparisons.

Examples

• "Compare this week to last week" — Fetches metrics for both 7-day windows and presents the full comparison table with insights.
• "How did March compare to February?" — Uses calendar month boundaries for both periods.
• "Show me the trend over the last 30 days" — Compares the last 15 days vs the 15 days before that, and supplements with trend data for a continuous chart description.
• "Is our response time getting better?" — Focuses the comparison on response time metrics specifically, with agent-level breakdown.
• "Week over week comparison for the past month" — Runs four weekly comparisons and presents them as a trend summary.
• "Compare email vs chat performance this month" — Uses channel analytics to compare metrics across channels within the same period.

Edge Cases

• No data for one period: If one period returns empty metrics, report "No data available for [period]" and show only the available period's data. Do not calculate deltas.
• Periods overlap: If the two date ranges overlap, warn the user that overlapping periods will produce misleading comparisons. Suggest adjusted ranges.
• Partial data: If one period has fewer days of data (e.g., current week is only 3 days in), note this and suggest per-day averages for a fairer comparison.
• Very small numbers: When Period A values are very small (under 5), percentage changes can be misleadingly large. Note this context — e.g., "2 to 4 is +100% but the absolute change is small."
• Metric not available: If a specific metric is not returned by the API for either period, omit it from the table and note its absence.

Settings

Cross-Skill References

• Use /weekly-report for the current period's standalone snapshot before comparing.
• Use /team-workload to correlate metric changes with staffing or workload shifts.
• The support-analyst agent (if available) can provide deeper statistical analysis on comparison data.

Guidelines

• Always label periods clearly so the user knows which column is which
• Present percentage changes with direction context — "response time decreased 35%" is an improvement, make that clear
• When volume increases significantly, proactively mention capacity implications
• For CSAT and satisfaction scores, note that small absolute changes (e.g., 4.1 to 4.3) can be meaningful at scale
• If the user asks for a trend rather than a two-period comparison, use get_trends and describe the trajectory narratively
• Round all numbers appropriately: times to one decimal, percentages to one decimal, counts to whole numbers