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Refunds chart

Weekly refund counts and totals with selectable date range and CSV export guidance.

This page documents the Refunds chart — weekly refunds across a selected period, how to set the date range and how to interpret and export refund data.

At a glance

  • Purpose: show weekly refund activity (counts and monetary refunds) so teams can monitor refund volume and value over time.
  • Primary visual: a weekly time series chart showing refund counts and refund totals across the selected date range.
  • Controls: a date range selector to set from/to dates and an export option to download the weekly rows as CSV.

Chart overview

  • Visual: a weekly chart (bars or lines). You may show refund totals (monetary) as bars and refund counts as a line, or vice versa.
  • Axes: the X axis shows the week label or start date; the Y axis shows refund totals (monetary). A secondary axis can show refund counts when both are displayed.
  • Behaviour: set a custom date range to control which weeks are plotted; hover a point to see exact refund counts and totals for the week.

Typical metrics available:

  • Refunds count: number of refund transactions processed in the week.
  • Refunds total: monetary total refunded in the week.
  • (Optional) Refund rate: refunds divided by orders or units sold in the same week, if units_sold or order_count data is available.

Filters and controls

  • Date range selector: set the start and end dates to limit which weeks are included in the chart.

How to interpret the chart

  • Rising refund counts or totals: may indicate product quality problems, incorrect listings, or fulfilment issues.
  • Spikes in refunds: correlate with promotions, product launches or shipping issues to find root causes.
  • Declining refunds: could indicate bug fixes, product improvements or successful policy changes.

Walkthrough: quick start

Choose the from and to dates to define the period you want to analyse (the chart will aggregate by week).

Hover each week to see the exact refund counts and totals; use the table beneath the chart to review week-by-week values.

How is this guide?

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