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Time-based analysis lets you explore how metrics change across time using dates in your data.

Grouping by Time

Use time-based grouping to analyze trends:
  • “Revenue by month”
  • “Orders per day”
  • “Quarterly revenue”
You can group by:
  • Day
  • Week
  • Month
  • Quarter
  • Year
You can also extract date components:
  • “Revenue by day of week”
  • “Orders by hour”
  • “Revenue by month of year”

Analysis Types

Analysis TypeDescriptionExamples
Time ComparisonsCompare values across periods (month-over-month, year-over-year, custom date ranges). Can show absolute differences or percentage changes.• “Compare revenue this month vs last month”
• “Show growth compared to last year”
• “Percent change from previous quarter”
Rolling & Cumulative MetricsTrack change over time with running totals and rolling averages (e.g., 7-day, 30-day).• “Running total of revenue”
• “7-day moving average of orders”
• “3-month rolling average of revenue”
Before & After ComparisonsCompare metrics before and after an event. Specify the change point clearly to structure the comparison correctly.• “Compare order volume in the 30 days before and after the price change”
• “How did conversion rate change after we redesigned the checkout flow?”
Cohort AnalysisGroups users by start date to analyze behavior over time.• “Revenue by signup month”
• “Retention rate by acquisition cohort”