Click fraud auditing for non-Google ad buyers

The moment this becomes a real problem: a media buyer running campaigns on a mid-tier ad network — think traffic arbitrage, native advertising networks, or niche B2B PPC — starts seeing suspicious click patterns but every fraud detection tool they evaluate either flat-out doesn't support that network or puts the relevant features behind an enterprise tier they can't justify.

This gap persists because the major click fraud vendors built their businesses around Google Ads and Meta, where the volume justifies the engineering investment. Supporting a long tail of ad networks means maintaining integrations that each serve a small slice of the market — there's no incentive for an incumbent to prioritize Taboola, MGID, or traffic exchanges when their bread and butter is already locked in. The buyer here is often a solo media buyer or small agency, not a procurement team that shows up in a vendor's CRM as a target account.

What existing tools get wrong: users specifically complained that 'finding out about ad networks is just limited and it doesn't work with other PPC organizations.' That's not a bug — it's a deliberate product boundary. These tools were never designed to cover the edges of the ad ecosystem.

This is a recurring business, not a one-time audit, because media buyers who run campaigns on non-Google networks do it every month. Invalid traffic doesn't stop. If they can't detect it, they're paying for clicks that never convert, and they have no data to dispute with the network. The cost is direct — wasted budget with no recourse — and it repeats every billing cycle.

What to build

Build a click fraud detection service that ingests raw click logs via UTM parameters or postback URLs from any ad network — not just Google and Meta — and flags invalid traffic patterns per source, giving buyers documented evidence they can take back to the network for credit disputes.

Where to start

Start with affiliate marketers running traffic on networks like PropellerAds or TrafficJunky, where fraud rates are notoriously high and there's almost no tooling — they're already talking about this in forums and paying out of pocket for manual audits.

The hard part

Getting enough click volume data across obscure networks to build reliable fraud signatures is genuinely hard early on — you need customers before you have the data, and you need the data before your detection is credible enough to win customers.

How it makes money

Monthly subscription tiered by number of tracked campaigns, with a 14-day free trial where the buyer connects one active campaign and gets a real fraud report before paying anything.