How to Prevent Click Fraud in PPC Campaigns

Reduce easy exposure first. Review your network and placement settings, exclude poor-performing or irrelevant placements, refine geographic and scheduling targeting, and add negative keywords. On Search Partners and Display especially, audit where your ads actually appear.

None of this requires new tools, and each change shrinks the surface fraud can reach. A campaign that only serves in its real market, during real business hours, on audited placements gives bots and click farms far less to click.

You can only prevent what you can see. Record clicks at the source and score them against IP, ASN, device, repeat behavior, timing and engagement, so suspicious sources are surfaced continuously rather than discovered later.

Continuous visibility also protects your ability to recover money: Google limits invalid-traffic investigations to the past 60 days, so an attack you notice a quarter later is an attack you mostly can't claim back.

Turn detection into action. Google Ads lets you exclude up to 500 IP addresses per campaign, entered under a campaign's additional settings, and you can use an asterisk wildcard to exclude a whole block at once. That capacity sounds like a lot until you watch a real attack: botnets and click farms rotate addresses constantly, so a static list written once goes stale within weeks while the same operators return from new ranges. Treat the 500 slots as a working set that gets pruned and refilled. Add sources backed by fresh evidence, expire entries that stop appearing, and prioritize datacenter and proxy ranges over individual residential addresses, which change hands quickly. And since IP exclusions only cover the platforms that support them, pair the list with bot filtering at your landing page so automated traffic is identified whichever channel it arrives from. Keep the exclusions updated so repeat offenders don't simply come back.

Prevention isn't only about clicks. It's about data. Keep fake clicks and fake leads out of the conversions that feed Smart Bidding, or automation will keep optimizing toward invalid traffic.

This is the quiet, compounding cost of click fraud: a polluted conversion history keeps steering budget toward junk long after the original clicks were credited or forgotten.

Manual prevention breaks down at scale. A tool like Didva scores each click in real time, auto-excludes high-confidence threats, holds borderline traffic for review, and feeds clean signals back to your bidding, continuously, without constant manual work.

That continuous loop is what separates the 0.7% fraud rate IAS measures in protected campaigns from the 10.9% in unprotected ones. The gap comes from coverage: a system that scores every click catches the attacks that land between manual reviews.