zone in AdcashValidVisit names the bad zone id; add it to Adcash's campaign block list.
Adcash operates one of the larger pop-under and interstitial exchanges in the performance advertising space, connecting advertisers to a wide publisher network that spans tier-1 markets through long-tail regional inventory. That breadth is what makes pop traffic both scalable and difficult to evaluate: a small number of bot-heavy zones can quietly absorb a disproportionate share of your budget while campaign-level metrics remain ambiguous. ValidVisit captures Adcash's [zone] and [campaign] tokens on every click and weighs each visit against more than 100 independent data points — covering where the click originated, the device behind it, and how the visitor actually behaves — to land on a single 0–100 quality score. The result is publisher-level intelligence that tells you which specific zones are driving non-human traffic, rather than a campaign-wide verdict that conflates clean inventory with bad.
https://yoursite.com/landing?utm_source=adcash&utm_medium=pop&vv_campaign_id=[campaign]&vv_click_id=[clickid]&vv_publisher_id=[zone]&vv_creative_id=[ban]Pop-under and interstitial channels have a different invalid-traffic profile from intent-driven formats like search or native. Because the ad fires automatically on page entry or exit, there is no deliberate user click to serve as a quality filter — automated page-loaders and scripted browsers can trigger pop events at scale without a human ever viewing the landing page. On Adcash specifically, the IVT patterns ValidVisit surfaces fall into a few categories worth understanding in terms of this network's inventory structure. First, network-origin clustering: traffic arriving from hosting ranges and proxy or VPN pools tends to concentrate inside particular zones rather than spreading organically across publishers — a pattern that points to coordinated traffic injection at the supply level rather than normal audience variation. Second, device and connection mismatches: the technical profile of an inbound visit can quietly contradict what a genuine browser on that operating system would produce, a discrepancy that holds up even when the user-agent string looks perfectly plausible. Third, environment gaps: when a client renders the page but never behaves like a real, interactive session, that hollow profile shows up disproportionately in certain zones and is a reliable marker of automation rather than people. Because every Adcash click is scored across 100+ data points and tied back to its [zone] token, ValidVisit can attribute all of these signals to individual publisher zones, letting you separate a single problematic zone from the rest of a campaign that is otherwise performing as expected.
Sort your active zones by average quality score and by the share of clicks landing in the suspicious or bad tier. A zone where that share runs well above your campaign baseline warrants manual review before you scale spend into it.
Pop traffic arriving from cloud-hosting ranges or proxy/VPN pools almost never converts. ValidVisit ties each origin finding to the specific [zone] token so you can identify which publisher sub-sources to add to your Adcash campaign exclusions without touching zones that are delivering real users.
Visits whose technical profile contradicts a genuine browser, plus an elevated rate of sessions that load but never behave like real people, are strong indicators of automated page-loaders within a zone. These are among the 100+ data points ValidVisit weighs, and they are far harder for traffic sellers to spoof than user-agent strings alone, making them particularly useful for assessing pop inventory quality.
Cross-reference [campaign] click volume against your conversion events. A campaign segment where clicks spike sharply but conversions remain flat often indicates a new bot-heavy zone being rotated in by the supply side — the zone-level breakdown in ValidVisit lets you confirm which zone triggered the shift.
Each Adcash macro maps to a normalized parameter, so every scored click is pinned to the right campaign, creative and publisher.
| Token | Adcash macro | Maps to | Identifies |
|---|---|---|---|
| Campaign ID | [campaign] | campaign_id | campaign |
| Click ID | [clickid] | click_id | click |
| Zone (traffic source) | [zone] | publisher_id | publisher |
| Creative ID | [ban] | creative_id | creative |
[campaign][clickid][zone][ban]Adcashitself 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 Adcash tokens, not by creative (which says nothing about whether a click was human).
Illustrative example — Adcash traffic scored 0–100 per sub-source, worst first.
See your own Adcash sub-sources scored this way.
Bot / invalid-traffic score broken down by:
[zone]Encrypted ID of the traffic source/zone, including appended Sub1 and Sub2 IDs.Per-click id: Adcash 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.
Place ValidVisit's tracking script on your landing page and append the Adcash dynamic macros — [zone], [campaign], and [clickid] — as URL parameters in your campaign destination URL. When a pop fires and the user's browser loads your page, the pixel captures those values on arrival, weighs the visit across 100+ data points into a single quality score, and stores the result tied to each [clickid]. You end up with a per-click audit trail segmented by zone and campaign. Because ValidVisit scores post-arrival on the landing page itself, there is no extra hop added to the pop event and no change to how the ad loads for the user.
Yes, that is the primary output. Because [zone] is captured on every click, the ValidVisit dashboard can rank your active zones by quality score distribution and by the kinds of signals dragging those scores down — hosting origin, proxy or VPN match, device mismatch, hollow non-interactive sessions, and so on. You can export that zone list and paste it directly into your Adcash campaign exclusions. ValidVisit surfaces which zones to act on; the exclusion itself is applied manually inside your Adcash account.
No. The 0–100 score is built from 100+ verifiable data points spanning the network the click came from, the device behind it, and how the visitor behaves — not from blunt proxies like time-on-page or scroll depth that are inherently low for pop traffic. A real person who closes a popped tab in three seconds produces a very different overall profile than an automated client or a hosting-network visit triggering the same event. This distinction is what makes IVT scoring useful for pop specifically: you can identify genuinely non-human traffic without penalizing the real, if briefly engaged, human audience that pop inventory does reach.
See which campaigns and publishers send real, converting traffic vs bots — every click scored 0–100.
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