Purpose-built for Shopify DTC brands

Stop promo abuse. Grow revenue.

PromoGuard stops multi-account discount abuse before it hits your margins with zero friction for your real customers and zero impact on checkout speed.

Start Protecting Revenue See how it works

promoguard.app/live-feed

Real-Time Decisions

System Active

john.doe+1@gmail.com

Known alias pattern

Blocked

Risk: 98 | 0ms

sarah.smith@company.com

Clean history

Allowed

Risk: 12 | 42ms

m.jones199@yahoo.com

Shared device ID

Blocked

Risk: 85 | 18ms

Revenue Protected Today

$4,250

Avg Abuse Rate

14.2%

$48B

lost to ecommerce promo abuse annually

Juniper Research

12-18%

of promo codes are abused in DTC

Industry avg.

$3.75

total cost per $1 of promo abuse losses

LexisNexis

98%

of your shoppers are legitimate

Signifyd

The Problem

Your welcome flow is leaking cash.

Growth teams spend heavily on acquisition, offering 15-20% off for first-time buyers. But sophisticated shoppers exploit this with endless aliases, and the tools built to stop them create a new problem: blocking your real customers.

The Alias Problem

Customers use john@gmail, j.ohn@gmail, and john+1@gmail to claim your welcome discount three times. Gmail ignores dots and plus signs. Your system does not.

Competitor Scraping

Competitors and bot networks automate checkouts to test pricing, deplete ad budgets, or steal inventory before real customers can buy.

Margin Decay

A 15% discount on a 40% margin product cuts profit by nearly half. Repeated discount abuse destroys unit economics and makes paid acquisition unprofitable.

The False Decline Tax

Legacy fraud tools block legitimate buyers. Industry data shows 2-3% of real orders are wrongly declined, costing more in lost revenue than fraud itself.

The Enterprise Trap

Purpose-built beats general-purpose.

Enterprise fraud platforms are built for banks and telcos. They charge six-figure setup fees, require months of integration work, and add checkout friction that suppresses legitimate order approval rates. PromoGuard targets precisely what you need addressed.

12-18%

Avg Promo Abuse Rate

How It Works

Precise. Invisible. Zero tolerance.

PromoGuard integrates via a lightweight Shopify app and operates silently within the checkout flow, analyzing hundreds of signals the moment a discount code is applied with no impact on the experience for legitimate buyers.

Device Recognition

Identifies repeat abusers across browsers, incognito sessions, and different email addresses.

Smart Heuristics

Catches the '+1' trick, Gmail dot variations, and disposable email domains in real time.

Targeted Blocking

Only blocks the abusive discount. Legitimate buyers complete their purchase normally.

Zero Checkout Friction

Runs invisibly inside your existing Shopify checkout. No extra steps for real customers.

Decision_Engine_v2.4

Live

Online

[EVENT] checkout_started[INPUT] apply_code "WELCOME20"[ANALYZE] email="j.smith+1@gmail.com"[MATCH] device_id=x89f...21a (Prev usage: 3)[ACTION] BLOCK_DISCOUNT[ACTION] ALLOW_CHECKOUT

Checkout delay

0ms

Discount action

Blocked

Order action

Allowed

Analytics Framework

Why traditional fraud tools miss the point entirely.

Payment fraud tools are optimized to catch stolen cards and identity theft. Promo abuse is a different problem: the payment is real, the person is real, and the loss is invisible to every fraud platform on the market.

Primary capabilitySupporting signal onlyNot addressed

Signal	What It Detects	PromoGuard	Traditional Fraud Tools
Identity Clustering	Links real customers across multiple accounts to catch repeat promo abuse by the same person.	Blocks policy abuse by real people.	No reason to block because payment is legitimate.
Promo Redemption Velocity	Catches real customers redeeming new customer offers multiple times across linked accounts.	Flags and blocks.	Transaction looks clean and passes through.
Return Rate by Identity Cluster	Tracks serial returners across linked accounts, not just a single account.	Surfaces hidden return abusers.	Post-purchase and outside scope.
Referral Self-Gaming Detection	Catches real customers referring themselves across accounts to pocket referral credits.	Detects and stops.	Payment is real, so it is ignored entirely.
Device Fingerprint Matching	Ties multiple different accounts to the same physical device.	Used to stop policy abuse.	Used only to catch stolen card fraud.
Discount Stacking Patterns	Identifies real customers combining codes to exceed intended discount thresholds.	Configurable thresholds and blocks.	Shopify permits it and fraud tools ignore it.
Lifetime Value vs. Lifetime Cost	Reveals customers who buy often but cost more than they generate.	Surfaces unprofitable customer clusters.	Not in scope for any fraud tool.
IP & Network Intelligence	Detects VPN and proxy use across accounts.	Supporting signal only.	Core fraud detection signal.
Email Signal Analysis	Flags disposable emails and low-trust domains used to create throwaway accounts.	Blocks fake account creation at signup.	Only flagged alongside payment risk.
Chargeback Rate by Cluster	Tracks dispute patterns across linked identities.	Supporting signal.	Core fraud tool capability.

What We Catch

Built for the problem. Not the budget.

Legacy fraud platforms are built for banks and telcos. PromoGuard is purpose-built to catch the abuse patterns that legitimate payment fraud tools cannot see.

The Problem

What We Catch

Your best customer just redeemed a "new customer" code for the 4th time.

Promo Redemption Abuse

Same person, 6 different accounts, 6 referral bonuses paid out.

Referral Self-Gaming

80% return rate across 3 "different" customers who share a device.

Serial Return Clustering

Codes stacked beyond your intended discount on every order.

Discount Stacking

Real payment, real person, real loss, invisible to NoFraud, SEON, and Forter.

All of the above

Book Demo

Recover margin. Starting this month.

Schedule a 15-minute product overview. We will show you exactly how PromoGuard works, walk through the Shopify install, and quantify how much revenue you are currently losing to promo abuse.

Shopify install walkthrough

Revenue leakage estimate

Policy abuse review

Book a Product Overview

Tell us where promo abuse is showing up in your Shopify store.