The Real Cost of Ad Fraud in Mobile E-Commerce: A Benchmark Guide

Ad fraud in mobile e-commerce can waste acquisition spend and distort the data used to judge campaign performance. Traffy shares reference KPI ranges and illustrative fraud patterns across the click-to-purchase journey, helping teams spot suspicious traffic, investigate weak points, and understand the potential financial impact of fraud.

Fraud in E-Commerce Is Harder to Spot Than It Used to Be

Ten years ago, ad fraud mostly meant obvious junk—a flood of fake clicks and installs that never opened. Today it hides inside numbers that look perfectly reasonable: a healthy install volume, a decent conversion rate, and a campaign that seems to scale. Industry estimates now put invalid traffic at around a third of mobile app traffic, and the schemes keep changing faster than most default filters can keep up with.

The reason it slips through is that people tend to look at metrics one at a time. On its own, a high install count tells you nothing. A good conversion rate can be faked. You only catch fraud when you read several signals together and actually know what a normal range looks like for each of them—which is exactly what most teams don’t have written down anywhere.

To make those signals easier to assess, Traffy has set out the benchmark ranges it uses for mobile e-commerce campaigns. The examples below illustrate how suspicious activity can appear in the data and which combinations of metrics warrant closer investigation. 

Anti-Fraud Benchmarks: Typical KPI Ranges

Traffy uses these reference values for mobile e-commerce apps. Real numbers depend on product category, GEO, traffic sources, pricing, and attribution model, so use them as a starting point for investigation rather than a hard cutoff.

What Fraud Actually Looks Like in the Data

Traffy uses these illustrative scenarios to show where suspicious activity may appear, from the first click through to a purchase or refund. Each pattern is a reason to investigate further, rather than proof of fraud on its own. 

• Click spam. 1,000,000 clicks turn into 8,000 installs—a 0.8% CTI—and most of those installs land several days after the click. That delay is the tell: someone is flooding clicks and waiting to claim organic installs as their own.
• Click injection. 55% of installs have a click-to-install time under 5 seconds. Real users don’t move that fast, so a spike this size means the clicks are being fired the moment an install begins.
• Fake installs. 50,000 installs produce 500 registrations—1%. When volume is high but almost nobody engages, you’re usually looking at bots or an install farm.
• Fake orders. 2,000 orders get created, 1,200 actually get paid—60%. Either a lot of orders are being abandoned, or they’re being generated just to trigger affiliate commissions.
• Refund fraud. The platform average refund rate is 3%. Affiliate X sits at 14%. Their users keep returning products after the commission has already been paid out.
• Affiliate fraud. Average order value across the platform is $120; from this affiliate’s traffic, it’s $28. A basket that small combined with high conversion volume usually means incentivized or low-quality traffic.
• Bot traffic. 90% of users open the app once, sessions last under 5 seconds, no product pages get viewed, no checkout happens. That’s about as clean a bot signature as you’ll find.

Read the Signals Together, Not One by One

The most useful habit in fraud detection is refusing to judge any metric alone. Most fraud only becomes obvious when two things show up at once:

Take any single row on its own, and you could explain it away—a rough GEO, a bad week, a weird cohort. Put two of them side by side, and the excuse stops working.

The Fraud Dashboard Traffy Recommends for E-Commerce Apps 

Traffy recommends tracking the following metrics in a mobile e-commerce fraud dashboard:

• Traffic quality: Click-to-Install Time (CTIT), Click-to-Install Rate (CTI), Install → Registration Rate, Registration → Purchase Rate
• Transactions and payouts: Payment Success Rate, Order Confirmation Rate, Cancellation Rate, Refund Rate, Chargeback Rate
• Value and retention: Repeat Purchase Rate, Revenue per Install (RPI), Customer Lifetime Value (LTV), Average Order Value (AOV)
• Technical signals: Device Reputation, IP Reputation, Duplicate Device Rate, Event Sequence Validation (SDK vs. Backend)

None of these is decisive alone, but tracked together they cover the whole journey—from the first click to the delivered order and the partner payout.

Final Thoughts

Fraud isn’t something you fix once and forget. Whatever filter you set last quarter, the schemes have already adjusted to it, which is why baselines matter more than any single tool. Know your normal ranges, watch the metrics in combination, and dig in the moment a pattern breaks—that’s most of the job.

Not sure where your traffic stands? Traffy runs free fraud audits for e-commerce apps. They’ll check your GEOs, sources, and funnel against these ranges and show you where the budget is leaking before you spend more on it.

Get in touch with Traffy to book your audit.

About Traffy

Traffy is a performance marketing agency with 10+ years of expertise in mobile and paid social user acquisition—from media buying and creative production to anti-fraud and funnel analytics—delivering 30M+ app installs annually across 50+ GEOs for e-commerce, fintech, crypto, and iGaming brands.