The Fraud KPIs Every Shopify Store Should Track

Most Shopify merchants know their conversion rate and AOV cold, but ask them their chargeback ratio or false-positive rate and you get a shrug. That gap is expensive. Fraud is one of the few areas of a store where a few well-chosen numbers tell you exactly whether your defenses are too loose, too tight, or about right.

This is the short list of KPIs worth tracking, the targets to aim for, and how to assemble a dashboard you will actually look at.

The core four

If you track nothing else, track these.

1. Chargeback ratio

What it is: Chargebacks divided by total transactions (or total order value), over a rolling window.

Why it matters: This is the metric your payment processor watches. Cross a threshold and you risk higher fees, reserves, or losing your account entirely.

Target: Keep it under 1% of transactions. Under 0.5% is healthy. Above 1% is a flashing warning light.

How to read it: A rising ratio means fraud is getting through. A ratio near zero with a high block rate might mean you are blocking too aggressively.

2. Block rate

What it is: The share of checkout attempts your rules stop before an order is created.

Why it matters: It shows how much your filters are actually doing. A tool like Shieldy — Fraud Filter blocks at the checkout level via Shopify Functions, so this is the number that tells you how many bad attempts never became orders.

Target: There is no universal "right" number — it depends on your traffic mix. What matters is the trend and composition. A sudden spike usually means an attack; a slow climb with rising customer complaints means your rules are catching real shoppers.

How to read it: Segment it. Blocks by Tor/proxy are almost always good. Blocks by country or VPN deserve a second look against your customer base.

3. False-positive rate

What it is: The share of blocked or flagged orders that were actually legitimate.

Why it matters: Fraud prevention that blocks real customers is just a different kind of revenue loss. This is the KPI that keeps your rules honest.

Target: Aim for a false-positive rate under 5% of your flags. You will rarely measure this perfectly — you learn it from customer complaints, support tickets ("I can't check out"), and spot-audits of blocked orders.

How to read it: If support tickets about failed checkouts climb after a rule change, your false-positive rate just went up even if the dashboard looks clean.

4. Revenue protected

What it is: An estimate of fraudulent order value you prevented, plus avoided chargeback fees.

Why it matters: It reframes fraud tooling from cost to return. It is also the number that justifies the plan you are on.

How to estimate it: Sum the value of blocked orders that matched high-confidence fraud signals (Tor, confirmed-bad IPs, geo mismatch on high AOV), then add the chargeback fees you would have paid on the fraud that historically got through. Label it clearly as an estimate — it is directional, not exact.

The supporting metrics

These add context and help you diagnose *why* the core four move.

• Manual review volume — how many orders need human eyes. Rising volume means rules are too loose or too vague.
• Average review time — how long a flagged order sits before a decision. Long times delay fulfillment and annoy good customers.
• Chargeback win rate — of chargebacks you dispute (representment), how many you win. Below ~30% usually means weak evidence packages.
• Repeat-offender catches — how often your blocklist stops a known-bad email or IP. Confirms your blocklist is earning its keep.
• Fraud by segment — break chargebacks down by country, payment method, and product. Concentrations tell you where to tighten.

Setting targets that fit your store

Copy-paste targets are a trap. Calibrate to your baseline:

1. Measure your last 90 days for each KPI before setting any goal.
2. Set the chargeback ratio target first — it is the one with external consequences. Keep it under 1%, full stop.
3. Let block rate and false-positive rate be balancing metrics. If you tighten rules to protect chargeback ratio, watch false positives rise; if you loosen, watch chargebacks. They move against each other.
4. Review targets quarterly. Fraud patterns shift; static targets go stale.

Building a simple dashboard

You do not need a BI stack. A single spreadsheet updated weekly beats a fancy dashboard nobody opens.

Suggested layout — one row per week:

Then add three things that turn data into decisions:

• A trend sparkline for chargeback ratio and false-positive rate — direction matters more than any single week.
• A threshold color — green under target, yellow approaching, red over. You want to react before you cross a line, not after.
• A notes column — record every rule change with its date, so you can tie shifts in the numbers to what you actually changed.

Turning KPIs into action

The dashboard is only useful if it triggers behavior:

• Chargeback ratio trending up → tighten rules on the segment driving it, and improve your representment evidence.
• False positives trending up → loosen the specific rule generating complaints (often an over-broad country or VPN block).
• Block rate spikes overnight → likely an attack; check for card-testing patterns and add velocity limits.
• Revenue protected flat while orders grow → your rules may be stale; re-tune thresholds.

Start measuring this week

Pick the core four, pull your last 90 days, and set one target: chargeback ratio under 1%. Everything else builds from there.

If you want the block-rate and revenue-protected numbers to reflect real checkout-level enforcement, Shieldy — Fraud Filter stops bad orders before they are created — and you can start on the free plan and see the pricing tiers as your volume grows.