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How we filter invalid traffic before it reaches your campaign

Invalid traffic is the tax every ad network pays. The question is who pays it — the advertiser, or the platform. At RuidaAds it is the platform: suspicious impressions are filtered before they are billed, and publishers are paid only for traffic that passes verification.

Layer 1: pre-bid publisher review

Every publisher application is reviewed manually. We check domain age, content category, traffic sources, and whether the site has a real audience. Sites with adult, pirated or malware-adjacent content are rejected outright, as are traffic sources that cannot be explained.

Layer 2: request-level signals

Each ad request carries device, browser, IP, user-agent and referrer data. We score the request against known data-center ranges, mismatched user agents, impossible device combinations and abnormal request rates. Requests that fail the threshold are dropped before an ad is served.

Layer 3: behavioural analysis

After delivery, we look at click-to-impression ratios, time-on-page, conversion patterns and session depth by site. A domain producing 40% CTR with zero downstream events is not a performance miracle — it is a signal to investigate and usually to block.

Layer 4: advertiser-side controls

Advertisers can exclude domains, cap frequency, restrict device types and set GEO-level bids. Combined with our global blocklists, these controls let buyers isolate suspicious inventory quickly without pausing an entire campaign.

What happens when we find fraud

Confirmed invalid traffic is removed from billing, the publisher is suspended pending review, and any unpaid balance tied to the traffic is withheld. Advertisers receive a credit on the affected ad group. We publish the policy in the Advertising & Anti-Fraud Policy so the rules are the same for everyone.

What advertisers should still do

Platform filtering is necessary but not sufficient. Run your own post-click verification, reconcile conversions daily, and tell your account manager when a source looks wrong. The fastest fraud investigations start with a buyer noticing a number that does not make sense.


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