Detect bots and invalid traffic across social networks, with every click scored 0–100 per campaign and publisher.
On social platforms the invalid-traffic surface isn't publisher arbitrage — it's placement quality. The auction and creative are usually sound; the leakage is in specific placements and ad sets where automated or incentivised engagement slips into otherwise strong inventory.
Social invalid traffic tends to live in three places:
The core in-feed placements usually perform; the leakage concentrates in a subset of placements and ad sets, which is why placement-level visibility matters more than a campaign average.
Because the social platforms auto-tag each click with a placement-aware id (e.g. `fbclid`), ValidVisit can attribute each scored click back to the originating campaign, ad set, and placement. Each click is weighed against 100+ independent data points — its network origin, the device behind it, and how the visitor behaves — combined into a single 0–100 quality score. That blend is especially diagnostic for automated app environments and engagement-farm tooling, so a pixel fire with no plausible human behind it is separated from a genuine but low-engagement visitor.
Be clear-eyed about the levers: social platforms are largely walled, so you can't blacklist an individual bad publisher the way you can on a native or pop network. What you can do is turn off the audience/extended network (e.g. Meta's Audience Network), exclude the weak placement type where the platform allows it, shift budget toward the placements ValidVisit scores clean, and use the evidence to request invalid-click credits. ValidVisit rolls the score up by placement and ad set so those decisions are grounded — but if you want true sub-source exclusion, that lives on the self-serve native, push and pop networks.
Every click is weighed against more than a hundred independent data points and reduced to a single, sortable 0–100 quality score.
Each data point is combined rather than checked in isolation, so a genuine human almost never trips enough of them to be flagged — and bots that beat one rarely beat the rest.
The detection model is ours and stays that way. What you get is a clear verdict on every click — not a single brittle rule you can game, and not an unexplained number you can't act on.
Every verdict maps to the campaign, publisher and placement that sent the click — so you know exactly which source to cut.
Illustrative example — the same 0–100 score, per source, worst first.
Platforms filter at their own definition of invalidity and report it in aggregate. ValidVisit gives you an independent, transparent second measurement — every click scored 0–100 and attributed to the exact placement and ad set — so you can verify quality rather than take the aggregate on trust.
Most often in extended audience-network inventory served across third-party apps, and in engagement-farm activity on short-form placements. Both concentrate in specific placements, which is why ValidVisit attributes scores at the placement and ad-set level.
See which campaigns and publishers send real, converting traffic vs bots — every click scored 0–100.
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