How invalid traffic gets caught
The layers of defence between a bot and an advertiser’s budget: lists, signals, behaviour and after-the-fact audits.
How invalid traffic gets caught
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A visit arrives
Every impression starts as a visit from a device. Some are people; some are crawlers, scripts or hijacked phones pretending to be people.
- A visit arrives: Every impression starts as a visit from a device. Some are people; some are crawlers, scripts or hijacked phones pretending to be people.
- Layer 1: known lists: The easy catches: declared crawlers on the IAB/ABC Spiders & Bots List, known data-center IP ranges, non-browser user agents. The MRC calls this GIVT.
- Layer 2: device and network signals: Next, deeper checks: does the device claim to be an iPhone but behave like a Linux server? Is it a headless browser or a residential proxy? Inconsistencies are red flags.
- Layer 3: behaviour: Bots can fake a fingerprint, but it is hard to fake human behaviour at scale: timing, scrolling, click-to-install gaps, impossible volumes. Behavioural analysis catches SIVT.
- One score to act on: Signals are combined into a score buyers can act on in real time. ClearTrust’s TQI Score™, for example, rolls 150+ filters into a single number.
- Pre-bid: don’t buy it: With pre-bid filtering, bad traffic is never bought. Clean requests go through to the auction.
- Post-bid: prove it and claw it back: Post-bid measurement audits what was bought. Invalid impressions are reported, excluded from billing and, where contracts allow, refunded.
Step by step
- A visit arrivesEvery impression starts as a visit from a device. Some are people; some are crawlers, scripts or hijacked phones pretending to be people.
- Layer 1: known listsThe easy catches: declared crawlers on the IAB/ABC Spiders & Bots List, known data-center IP ranges, non-browser user agents. The MRC calls this GIVT.
- Layer 2: device and network signalsNext, deeper checks: does the device claim to be an iPhone but behave like a Linux server? Is it a headless browser or a residential proxy? Inconsistencies are red flags.
- Layer 3: behaviourBots can fake a fingerprint, but it is hard to fake human behaviour at scale: timing, scrolling, click-to-install gaps, impossible volumes. Behavioural analysis catches SIVT.
- One score to act onSignals are combined into a score buyers can act on in real time. ClearTrust’s TQI Score™, for example, rolls 150+ filters into a single number.
- Pre-bid: don’t buy itWith pre-bid filtering, bad traffic is never bought. Clean requests go through to the auction.
- Post-bid: prove it and claw it backPost-bid measurement audits what was bought. Invalid impressions are reported, excluded from billing and, where contracts allow, refunded.