website / feed in PopCashValidVisit names the bad website/feed id; add it to PopCash's campaign blacklist.
PopCash runs one of the largest pop-under networks globally, pulling traffic from publisher sites across news, entertainment, downloads, and adult verticals. The reach is genuine, but the format creates a specific measurement problem: a pop-under fires automatically on page load with no deliberate user action, which means automated browsing sessions, traffic generation scripts, and bot-populated publisher sites can produce technically valid-looking landing page visits without a human ever engaging with your offer. The absence of any intent signal — no keyword, no deliberate click — makes pop traffic uniquely dependent on zone-level and site-level quality filtering after the fact. ValidVisit integrates with PopCash campaigns by capturing the [clickid], [siteid], and [campaignid] macros in your destination URL, then scoring each incoming session once it arrives by weighing it against 100+ independent data points — where the traffic came from, the device behind it, and how the visitor actually behaves — which roll up into a single 0-100 quality score that genuine humans clear and bots fail. Those scores are attributed back to the specific site IDs and content categories responsible. You see exactly where non-human traffic is concentrated; you then exclude those sources inside the PopCash campaign dashboard using their site-exclusion tools.
https://yoursite.com/landing?utm_source=popcash&utm_medium=pop&vv_click_id=[clickid]&vv_campaign_id=[campaignid]&vv_campaign_name=[campaignname]&vv_publisher_id=[siteid]&vv_keyword=[category]Pop-under inventory has a structural IVT exposure that differs from display or native formats: because no user gesture is required to trigger the ad, server farms and automated browsing environments can participate in pop delivery at scale without simulating anything more complex than a page load. On PopCash specifically, this tends to show up in two distinct patterns rather than one uniform signal. The first is infrastructure clustering — sessions arriving from hosting and datacenter networks dressed up to look residential, often concentrated on a small number of [siteid] values that quietly share the same upstream pipes. Because every click is measured across the full spread of 100+ data points, that shared origin surfaces as a tight cluster of low quality scores rather than a scatter of borderline ones. The second pattern is uniformity across the technical profile of the visitors themselves: automated clients built on the same underlying setup behave and present in near-identical ways even when they rotate IP addresses and user-agent strings, so that sameness becomes a reliable tell of coordinated traffic generation that IP-level analysis alone would miss. Beyond non-human traffic, some PopCash zones serve genuinely human audiences who simply have no alignment with typical advertiser offers — visitors from file-sharing portals or streaming proxies produce real sessions with near-zero conversion intent. ValidVisit separates these cases: a healthy quality score paired with shallow session depth points to audience mismatch, while a low quality score points to non-human origins. Both show up broken down by [siteid] and [category] so you can act at the right level.
A well-distributed pop campaign spreads impressions across a wide range of site IDs with varied engagement patterns. If a tight cluster of [siteid] values accounts for a disproportionate share of your sessions while producing session depths well below your campaign baseline, those IDs warrant a closer look at their quality scores. ValidVisit ties every scored session to the originating [siteid], letting you rank sources by IVT rate and identify which ones to exclude in the PopCash site-exclusion interface.
PopCash passes a content category for each placement, and certain categories — file-sharing, streaming-proxy, and specific adult sub-niches — tend to attract tool-assisted or bot-populated audiences at higher rates than mainstream content. Segmenting your IVT rate by [category] lets you identify which verticals are structurally incompatible with your offer before those sessions distort your conversion and optimization data, rather than discovering the pattern after budget has shifted toward the wrong zones.
When you run multiple PopCash campaigns in parallel, IVT rates can diverge materially between them even when geographic and device targeting overlap — because PopCash's delivery algorithm weighs bid price when allocating across site inventory, lower-bid campaigns often get routed toward remnant zones with weaker quality signals. The [campaignid] dimension in ValidVisit lets you compare IVT rates across campaigns side by side and connect bidding strategy to inventory quality.
Pop-under formats require only a page load to trigger delivery, making them a low-friction target for traffic generation infrastructure. ValidVisit scores every incoming session across 100+ data points spanning its network origin, the device behind it, and its behavior, including the proxy and VPN routing bad actors lean on. When a [siteid] produces an unusually homogeneous mix — many sessions that look and act like carbon copies of one another — that sameness is a strong signal of coordinated automated traffic regardless of how IP addresses and user agents appear individually.
Each PopCash macro maps to a normalized parameter, so every scored click is pinned to the right campaign, creative and publisher.
| Token | PopCash macro | Maps to | Identifies |
|---|---|---|---|
| Click ID | [clickid] | click_id | click |
| Campaign ID | [campaignid] | campaign_id | campaign |
| Campaign Name | [campaignname] | campaign_name | campaign |
| Site ID | [siteid] | publisher_id | publisher |
| Category | [category] | keyword | keyword |
[clickid][campaignid][campaignname][siteid][category]PopCashitself 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 PopCash tokens, not by creative (which says nothing about whether a click was human).
Illustrative example — PopCash traffic scored 0–100 per sub-source, worst first.
See your own PopCash sub-sources scored this way.
Bot / invalid-traffic score broken down by:
[siteid]Publisher's website / source identifier where the ad was shownPer-click id: PopCash 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.
ValidVisit handles the scoring and attribution side: every session is assigned a 0-100 quality score and linked to its [siteid] and [category] tokens from PopCash, so you can sort your site IDs by IVT rate and see exactly which sources are driving non-human traffic. Applying the exclusion is a manual step inside the PopCash campaign dashboard using their site-exclusion feature — ValidVisit gives you the ranked list to work from, which turns what would otherwise be hours of log analysis into a targeted review. Automated blocklist delivery to ad platforms is on the ValidVisit roadmap for supported networks, but is not a current capability.
ValidVisit does not depend on a user-initiated click event to begin evaluating a session. When a PopCash pop-under fires and your landing page loads — with [clickid] and [siteid] macros appended — ValidVisit weighs that arriving session against 100+ independent data points: the network it came in on, whether it is riding proxy or VPN routing, the device presenting itself, and how the visitor behaves once the page is up. Those signals combine into a single 0-100 quality score so real humans pass cleanly while automated clients stand out. The whole evaluation happens after the click lands and is attached to that [clickid], with nothing on the click path and no added latency to your funnel.
Pop traffic routinely produces this combination, and it usually reflects two separate problems that most single-signal tools collapse into one. High bounce rates with almost nothing flagged typically mean the traffic is human but intent-misaligned — visitors arriving from [category] placements like download portals or streaming proxies have no reason to engage with a lead-generation or ecommerce offer. That is an audience-quality problem, not an IVT problem, and a tool leaning on one narrow check will miss it entirely. ValidVisit surfaces both dimensions in the same dashboard: because each session is graded across 100+ data points, the quality score by [siteid] isolates the non-human sessions, while session-depth and engagement signals flag the low-intent human sessions. Acting on only one leaves half the problem in place.
See which campaigns and publishers send real, converting traffic vs bots — every click scored 0–100.
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