Documentation

Your daily command center for reviewing scored returns and refunds.

The historical-data scoring pass that runs on install. Stages, troubleshooting, and what happens next.

The one-shot post-backfill report. Patterns, KPIs, and what to act on first.

Pre-fulfilment risk surface. Hold orders before they ship.

The post-refund operator view. Works for native, third-party, and manual refund flows.

Customer-level risk profiles, return history, and manual overrides.

The analyst surface — products, reasons, refund methods, cohorts, and networks.

Flexible drill-down across any two dimensions of your return data.

Every dispute, with RefundSentry's prediction accuracy overlaid.

Dollar-impact summary of what RefundSentry has saved you.

Customer tagging, order holds, Shopify Flow templates, auto-watch, and custom workflow rules.

Focused one-at-a-time workflow for clearing risky events.

The queue of paused fulfilments. Release, deny, or escalate.

Customers RefundSentry is actively monitoring.

Permanent do-not-fulfill list. Forces HIGH score on every event.

Replay historical returns against proposed thresholds before applying them.

Shadow-score incoming returns through two configurations and compare.

Configure thresholds, notifications, integrations, experiments, and advanced options.

Your plan, usage, and how billing is managed via Shopify.

Read-only access for finance teams, contractors, and the board.

Opt-in integration that writes RefundSentry scores into Shopify's native risk panel.

Understanding the 0-100 risk score, the three risk zones, and the 80+ signals behind every score.

Adjust the LOW / MEDIUM / HIGH zone boundaries to match your store's tolerance.

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

How free-text return reasons are grouped into actionable categories.

Cross-reference return reasons with product types to find systematic issues.

Map products against their average risk scores to prioritise interventions.

Rank product types by return volume to guide inventory and merchandising decisions.

Department-level return volume to find which areas need the most attention.

Track the monetary cost of returns over time and measure the ROI of your policies.

Compare return metrics between any two time periods to measure improvement.

See which refund methods customers prefer and where exchanges out-perform refunds.

Identify SKUs and categories with high sizing-driven return rates.