Banner / Display ad networks: click fraud & invalid traffic
Detect bots and invalid traffic across banner / display networks, with every click scored 0–100 per campaign and publisher.
Programmatic display reaches enormous breadth through layers of exchanges and resellers, and that depth is where invalid traffic hides. The format's economics reward impression and click volume, which creates room for low-quality inventory — made-for-advertising sites, stacked or hidden placements — to absorb spend with little genuine attention behind it.
ExoClickWhere invalid traffic concentrates
Display invalid traffic clusters in a few recognisable structures:
- Made-for-advertising (MFA) sites — pages built primarily to carry ads, often fed by cheap acquired traffic, where the click context looks valid but the audience intent is absent.
- Ad stacking and hidden placements — multiple ads layered in one slot, or units rendered where no human could see them, generating clicks and impressions without genuine exposure.
- Datacenter-sourced click sweeps that hit specific domains or placements in bursts.
Across the programmatic chain the meaningful unit is the placement and the publishing domain, which the supply path can otherwise obscure.
What ValidVisit scores
Banner clicks are weighed against 100+ data points that span network origin, device, and behaviour — the server-farm and automation origins that dominate display sweeps, server-side bots that never genuinely load the page, and the traces left by automated browsers — all combined into a single 0–100 quality score. ValidVisit captures the outbound domain and the network's placement tokens on each click, so the score is attributed to the exact domain and placement rather than to a campaign aggregate.
Pinpointing the sub-source
Because programmatic supply chains are deep, the most valuable output is a clean per-domain and per-placement breakdown. ValidVisit surfaces which publishing domains and placements carry concentrated invalid traffic, giving you the evidence to refine inclusion/exclusion lists inside your buying platform — a decision that stays yours to make.
How ValidVisit detects the fraud
Data points → one score
Every click is weighed against more than a hundred independent data points and reduced to a single, sortable 0–100 quality score.
Many angles, combined
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.
Proprietary, not a black box
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.
Pinned to the source
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.
Banner / Display networks — FAQ
What is a made-for-advertising (MFA) site and why does it matter?+
An MFA site is a page built mainly to host ads, usually fed by cheap acquired visitors. Clicks from it can look technically valid while the audience has no real intent, so it quietly absorbs display budget. ValidVisit scores those clicks per domain so the pattern is visible and actionable.
Can ValidVisit see through the programmatic supply chain?+
It scores the click that actually lands on your page — capturing the outbound domain, placement tokens, and 100+ data points across network origin, device, and behaviour — and attributes the result to the specific domain and placement. That gives you ground-truth on which sub-sources are clean, independent of how the impression was bought.
Catch the fake clicks on Banner / Display networks.
See which campaigns and publishers send real, converting traffic vs bots — every click scored 0–100.
Free trial at launch · lock in early-access pricing
One script · raw IP never stored · GDPR legitimate-interest basis