Click fraud IP intelligence reporting for Google Ads managers

The moment it breaks down: a PPC manager pulls their weekly click fraud report, sees that 12% of clicks were flagged, and has nowhere to go from there. No subnet patterns, no geolocation clustering, no repeat offender timelines — just a number that tells them fraud happened but not where it's coming from or whether their exclusion lists are actually working.

This gap persists for a structural reason: existing click fraud tools are built to automate blocking, so deep investigative reporting is a secondary concern for them. Their incentive is to show you the block count went up, not to hand you a forensic breakdown that might reveal their blocking logic is imprecise. The buyer is usually the agency or in-house PPC team, but the person who feels the pain daily is the analyst who has to explain budget waste to a client — and that person has no political power to demand better tooling from the vendor.

What users actually complain about is the IP layer specifically: 'more details around IP monitoring can be helpful to identify the exact source of click frauds.' Current tools show flagged IPs in isolation. They don't show you that 40 flagged IPs share a /24 subnet, or that the same CIDR range has been hitting your account across three campaigns over six weeks, or that a specific ISP is responsible for 70% of your invalid clicks. Without that, you can't make a case to Google for a refund, you can't build exclusion logic, and you're blocking IPs one by one like whack-a-mole.

This is a business and not a feature because the underlying need recurs on every campaign billing cycle — advertisers have to justify spend, agencies have to defend their management fees, and neither can do that with a single aggregate fraud percentage. The analysis has to be redone every month, for every client account, with no institutional memory carried forward. A tool that builds longitudinal IP intelligence across campaigns — so you can say 'this subnet has cost this account $4,200 over 90 days' — gets used every single billing cycle and becomes the source of truth for refund claims and exclusion strategy.

What to build

Build a reporting layer that ingests raw click log data via Google Ads API, clusters flagged IPs by subnet and ASN, surfaces repeat-offender patterns across campaigns over a rolling 90-day window, and exports a structured PDF suitable for submitting to Google's invalid click refund process.

Where to start

Start with agencies that are already disputing invalid click charges with Google — they have the strongest motivation, they already believe the fraud exists, and they need exactly the subnet-level evidence you produce to make the case. One successful refund claim becomes a case study that sells itself.

The hard part

Getting clean, granular click log data is the hard part — Google Ads exposes click data at a level that obscures the forensic detail you need, so you may have to push users to install a landing page tag or route traffic through a tracking domain you control, which adds friction at the exact point where you need adoption to be frictionless.

How it makes money

Monthly subscription per Google Ads account connected, priced so that a single successful refund claim covers several months of fees — roughly $49–$99 per account per month, with volume discounts for agencies connecting 10+ accounts.