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Analytics Reference

Risk Distribution

How your returns split across LOW / MEDIUM / HIGH risk zones.

The Risk Distribution chart is the headline view in Insights → Risk overview. It tells you what proportion of your returns landed in each risk zone over the selected period. One chart, one number, big signal.

Reading the chart

A horizontal stacked bar with three segments:

  • Green = LOW (0-30) — Routine returns. Process and move on.
  • Amber = MEDIUM (31-65) — Worth a glance.
  • Red = HIGH (66-100) — Likely abuse or fraud.

Each segment shows both the percentage and the absolute count. Hover any segment to see the breakdown of the top reason clusters and product types contributing to it.

What “healthy” looks like

For a typical Shopify apparel store with default thresholds, expect roughly:

  • LOW: 65-75%
  • MEDIUM: 18-25%
  • HIGH: 5-10%

These ranges are wide on purpose — “normal” depends heavily on your product category, customer base, and return policy. A flash-sale store will skew higher; a luxury single-SKU store will skew lower.

What it tells you

Too much HIGH (> 15%) — Either you have a real fraud problem worth investigating, or your thresholds are set too aggressively and you’re over-flagging legitimate returns. Cross-check with financial impact — if HIGH-risk returns are mostly low-value, the score is probably noisier than the dollar exposure.

Too little HIGH (< 3%) — Either you genuinely have very clean customers (lucky you), or your thresholds are too lax. If chargebacks or refund losses are still happening despite HIGH being < 3%, lower the HIGH boundary in Settings → Risk thresholds.

MEDIUM bigger than LOW — Almost always means thresholds are misaligned for your business. The simulator will show this in seconds.

Trend over time

Below the headline bar there’s a sparkline of the risk distribution over the selected period (defaults to last 30 days, daily granularity). Use this to spot drift — risk slowly creeping up over weeks is the kind of thing you only catch when you look at trend lines, not snapshots.

Common follow-up actions