Which OnClickA zones send real traffic?
Not all OnClickA traffic is equal. ValidVisit scores every visit 0–100 and pins it to the exact zone that sent it — so you can tell real humans from bots and invalid clicks, worst zones first.
site + individual ad spot in OnClickAThe buyer selects one or more campaigns, opens the blacklist feature, and adds the bad site or spot IDs to the campaign's blacklist (spot blacklist works as a separate target on top of the site white/blacklist), or sets a $0.00 micro-bid on the bad source.
ValidVisit reports the device, OS, browser — down to the version — plus the language and ISP behind every flagged visit, and OnClickA supports OS version, browser version, language, device type and connection type targeting. The segments we flag are segments you can exclude.
How invalid traffic slips in through OnClickA zones.
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 visit 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.
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.
What to watch on OnClickA
Rank active [DOMAIN] values by quality and by the share of visits 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.
Pinpoint the bot publishers & placements in OnClickA.
OnClickA itself 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).
Bought as one OnClickA line, your spend is a single number. Scored per sub-source it runs from 85 down to 28 — the worst is nearly all bots. That’s the leak a blended average hides.
OnClickA traffic scored 0–100 per sub-source, worst first — down to the placement you buy.
Bot / invalid-traffic score broken down by:
- Source Domain
[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 visit.
Compare bot & invalid-traffic breakdown across every ad network →See your own OnClickA sub-sources scored this way.
How ValidVisit attributes OnClickA traffic
Each OnClickA macro maps to a normalized parameter, so every scored click is pinned to the right campaign, creative and publisher.
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]| 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 |
- OnClickA macro
[CAMPAIGN_ID]- Maps to
- campaign_id
- Identifies
- campaign
- OnClickA macro
[DOMAIN]- Maps to
- publisher_id
- Identifies
- publisher
- OnClickA macro
[WEB_PUSH_ID]- Maps to
- ad_id
- Identifies
- ad
- OnClickA macro
[CLICK_ID]- Maps to
- click_id
- Identifies
- click
How the detection works.
Data points → one score
Every visit 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 visit — 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.
How ValidVisit helps you cut fraud and bad site + individual ad spots on OnClickA.
Scoring and attribution are the means — the point is cutting the OnClickA traffic that wastes your spend. Here's how ValidVisit gets you a list you can act on.
- Score
See what's actually landing
You buy OnClickA clicks; what arrives are visits. ValidVisit scores each one 0–100 so real humans stand out from bots and invalid traffic — one script, no funnel hop, no fingerprinting.
- Attribute
Pin the fraud to its source
Every scored visit is tied to the exact OnClickA site + individual ad spot and zone via the network's own tokens — so the bad traffic has an address, not just a headline percentage.
- Cut
Take the site + individual ad spots off your buy
You get the worst offenders as a ready-to-use list plus postbacks to your tracker — so you can exclude them in OnClickA and put your next dollar behind the traffic that converts.
OnClickA traffic quality, answered.
How do I set up ValidVisit for OnClickA?+
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 visit, segmented by source domain, with nothing on the click path.
Can ValidVisit tell me which OnClickA domains to blacklist?+
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.
Will real but low-engagement pop visits score badly?+
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.
Detect fraud on other push networks
Find the bots in your OnClickA spend.
See which publishers and placements send real buyers vs bots — every visit scored 0–100, worst first.
Free trial at launch · just your email
One script · no cookies · no fingerprinting · raw IP never stored