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Card class: Non-Hero • Category: Payment Gateway

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At a glance

Refund volume as a percentage of total Square volume. The companion to squ_refund_volume. Industry-benchmarked: bookshops 1, 3%, apparel 15, 30%, digital <1%. Spikes signal product / fulfilment issues; gentle creep signals subscription churn.
What it countsSUM(refunds.amount) / SUM(payments.amount) * 100 over the period, both status = COMPLETED.
CurrencyPer-currency rate.
Time window30D vsP.
Alert trigger>10% absolute, OR +30% relative spike. Sentiment inverse-gauge: good <=3, warn >=8.
Rolesowner, finance, operations

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Calculation

Calculated automatically from your Square data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.

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Worked example

30 days, Austin bookshop: 
Refund volume    = USD 1,840
Total volume     = USD 129,020
Refund rate      = 1,840 / 129,020 * 100 = 1.43%
Subset:
SubsetRefund rate
POS chip + tap0.7%
Square Online2.3%
Cash App Pay1.5%
Square Invoices12.3% (the one preorder cancellation)
Reads:
  1. Blended 1.43% is well below the 10% alert threshold. Bookshops sit in the 1, 3% peer band.
  2. Invoices subset 12.3% is a single-event distortion. One USD 590 refund on a USD 4,800 invoice base. Always slice when sample is small.
  3. Online 2.3% is normal for non-apparel ecom.

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Sibling cards merchants should reference together

CardWhy pair
squ_refund_volumeThe numerator.
squ_total_volumeThe denominator.
squ_dispute_rateInverse-correlated; refunding promptly prevents disputes.
Stripe stripe_refund_rateCross-PSP.

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Reconciling against the vendor’s own dashboard

Where to look in the Square Dashboard: Square Dashboard does not surface refund-rate as a headline KPI; you compute from refunds tile / sales tile. Why ours may differ:
ReasonDirection
Period boundaryA refund processed today for a payment from last month: how it’s bucketed
Cash inclusionBoth numerator and denominator
Cross-connector reconciliation: refund-rate diverges across PSPs by traffic mix; multi-rail merchants typically see 0.5, 1.5pp difference between Square (retail-leaning) and Stripe (digital-leaning) for the same business.

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Known limitations / merchant FAQs

“My rate jumped to 8%, what to look at first?” Slice by reason, channel, and SKU. Most rate spikes are concentrated (one bad shipment, one defective product). If spread across many SKUs, it’s a customer-quality issue (bad ad traffic). “Industry benchmarks for Square retail?” Bookshops 1, 3%. Coffee / cafe <1%. Apparel boutique 8, 15%. Salon services 0.5, 1%. Restaurants <0.5%. “How do I bring my rate down?” Three levers: better product descriptions (online), better fitting/sizing data (apparel), faster customer service (cancellations before fulfilment cost real money). “Subscription refunds, prorated, count here?” Yes; the prorated amount is the refund value. “Cash refunds in the rate?” Yes if rung up as a Square cash refund. “Multi-currency, single rate?” Per-currency rate (refund-USD vs volume-USD; refund-CAD vs volume-CAD). “Refund-rate vs return-rate, are they different?” Yes. Return-rate is units returned ÷ units shipped (commerce-side metric). Refund-rate is dollars refunded ÷ dollars charged (payment-side). They diverge when a return is replaced rather than refunded. “Square Online vs in-store rate, why so different?” Online customers can’t inspect before buying; returns are 3, 5x higher than walk-in. Universal across retail-plus-ecom.

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Tracked live in Vortex IQ Nerve Centre

Refund Rate is one of hundreds of KPI pulses Vortex IQ tracks across Square and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. Start for free or book a demo to see this metric running on your own data.