source domain in OnClickAValidVisit flags the bad [DOMAIN]; add those source domains to your OnClickA campaign blacklist.
OnClickA is a self-serve, multi-format network (push, popunder, in-page, banner) with a wide publisher base. It exposes the source [DOMAIN] (the publisher domain a click came from), [CAMPAIGN_ID], an ad id ([WEB_PUSH_ID]) and a [CLICK_ID] on every click — and the domain is the unit you blacklist in the campaign. ValidVisit reads those tokens as each click lands, then weighs the click against 100+ independent data points — the network and publisher it came through, the device on the other end and the way the visitor actually behaves — and folds them into one 0–100 quality score. The result is a per-domain readout of which source domains are carrying non-human traffic.
https://yoursite.com/landing?utm_source=onclicka&utm_medium=push&vv_campaign_id=[CAMPAIGN_ID]&vv_publisher_id=[DOMAIN]&vv_ad_id=[WEB_PUSH_ID]&vv_click_id=[CLICK_ID]OnClickA's popunder and in-page formats fire without a deliberate click, so automated page-loaders can trigger events at scale — and they concentrate by source domain. The dominant pattern is automated loaders running out of hosting infrastructure or rented residential proxies, clustered in specific [DOMAIN] values rather than spread evenly across the campaign.
A second pattern is mismatched client behavior — connections whose technical profile doesn't line up with a genuine browser on the OS it claims, the kind of gap that scripted clients and modified browser builds leave behind. A third is inert visitors: domains with a disproportionate share of clients that load the page but never behave like a person operating it. Because [DOMAIN] rides on every click, the 0–100 score pins each of these to the individual source domain, so one bad domain stays separable from a campaign that is otherwise clean.
Rank active [DOMAIN] values by quality and by the share of clicks in the suspicious/bad tier. Domains above your baseline are blacklist candidates.
Pop and in-page clicks routed through cloud infrastructure or proxy networks rarely convert. ValidVisit ties each of these findings back to the [DOMAIN] so you blacklist the offending sources cleanly.
Clients whose technical profile contradicts the browser they claim, plus an elevated share of visitors who load but never genuinely engage within a domain, point to automated loaders — patterns far harder to fake than a user-agent string.
A spike in [CAMPAIGN_ID] clicks without conversions usually traces to a specific source domain the per-domain breakdown will identify.
Each OnClickA macro maps to a normalized parameter, so every scored click is pinned to the right campaign, creative and publisher.
| Token | OnClickA macro | Maps to | Identifies |
|---|---|---|---|
| Campaign ID | [CAMPAIGN_ID] | campaign_id | campaign |
| Source Domain | [DOMAIN] | publisher_id | publisher |
| Ad ID | [WEB_PUSH_ID] | ad_id | ad |
| Click ID | [CLICK_ID] | click_id | click |
[CAMPAIGN_ID][DOMAIN][WEB_PUSH_ID][CLICK_ID]OnClickAitself isn’t the problem — bots and invalid traffic concentrate in a handful of its sub-sources: the publisher, site or zone, and the placement or widget within it. So we roll the score up by those OnClickA tokens, not by creative (which says nothing about whether a click was human).
Illustrative example — OnClickA traffic scored 0–100 per sub-source, worst first.
See your own OnClickA sub-sources scored this way.
Bot / invalid-traffic score broken down by:
[DOMAIN]The referrer / publisher domain the click came from — the source you blacklist.Per-click id: OnClickA passes a unique click id, so we also run velocity, deduplication and repeat-source checks on every click.
Compare bot & invalid-traffic breakdown across every ad network →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.
Add ValidVisit's script to your landing page and append OnClickA's macros — [DOMAIN], [CAMPAIGN_ID], [WEB_PUSH_ID] and [CLICK_ID] — to your destination URL. The pixel captures them as the visit lands and stores a scored verdict per click, segmented by source domain, with nothing on the click path.
Yes. Because [DOMAIN] is on every click, ValidVisit ranks your source domains by quality and by what's dragging their scores down, and you blacklist the offenders in your OnClickA campaign. ValidVisit reports the evidence; the block is applied in your account.
No. The score is built from 100+ technical and behavioral data points about the network, the device and the visitor — not from time-on-page, which is naturally low for pop. A genuine person and an automated loader on a hosting connection produce very different combinations of those signals, so real humans pass even when they linger only briefly.
See which campaigns and publishers send real, converting traffic vs bots — every click scored 0–100.
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