Which Adcash zones send bots and invalid traffic?
Not all Adcash 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.
zone in AdcashThe buyer pastes bad zone/sub IDs (collected via the [zone] macro in the landing URL or Performance page → Group by Zone/Source) into a Zones List, then applies that list to the campaign with the "exclude" action (Apply targeting rule); limits: 100 lists, 1,000 zones/list, 30k zones/campaign, exclude OR target-only but not both on the same list.
ValidVisit reports the device, OS, browser — down to the version — plus the language and ISP behind every flagged visit, and Adcash 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 Adcash zones.
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 valid inventory with bad.
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 visit 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.
What to watch on Adcash
Sort your active zones by average quality score and by the share of visits landing in the suspect or invalid 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.
Pinpoint the bot publishers & placements in Adcash.
Adcash 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 Adcash tokens, not by creative (which says nothing about whether a click was human).
Bought as one Adcash line, a buy reads as a single number. Scored per sub-source, a spread like this illustration runs from 88 down to 12 — the worst is nearly all bots. That’s the leak a blended average hides.
Illustrative: Adcash traffic scored 0–100 per sub-source, worst first — down to the placement you buy.
Bot / invalid-traffic score broken down by:
- Zone (traffic source)
[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 visit.
Compare bot & invalid-traffic breakdown across every ad network →See your own Adcash sub-sources scored this way.
How ValidVisit attributes Adcash traffic
Each Adcash 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=adcash&utm_medium=pop&vv_campaign_id=[campaign]&vv_click_id=[clickid]&vv_publisher_id=[zone]&vv_creative_id=[ban]| 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 |
- Adcash macro
[campaign]- Maps to
- campaign_id
- Identifies
- campaign
- Adcash macro
[clickid]- Maps to
- click_id
- Identifies
- click
- Adcash macro
[zone]- Maps to
- publisher_id
- Identifies
- publisher
- Adcash macro
[ban]- Maps to
- creative_id
- Identifies
- creative
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 zones on Adcash.
Scoring and attribution are the means — the point is cutting the Adcash 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 Adcash 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 Adcash zone and zone via the network’s own tokens — so the bad traffic has an address, not just a headline percentage.
- Cut
Take the zones 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 Adcash and put your next dollar behind the traffic that converts.
Adcash traffic quality, answered.
What exactly do I paste into my Adcash campaign to get ValidVisit scoring?
Just the Adcash click macros — [zone], [campaign], and [clickid] — added as URL parameters on whatever landing page the pop points to, plus ValidVisit’s tracking script on that same page. The moment a pop fires and the browser loads your page, the pixel reads those macro values, runs the visit through the 100+-point scoring model, and stores the resulting quality score against that [clickid]. Nothing changes about how the ad itself loads — scoring happens entirely after arrival, so there’s no added hop and no delay on the pop event.
Once ValidVisit flags a zone, how do I actually stop buying it?
You export it and paste it in yourself. Because [zone] rides on every scored click, the dashboard can rank every zone you’ve run by its quality distribution and by which signals are pulling the worst ones down — hosting origin, proxy/VPN match, device mismatch, sessions that never behave like a person. Take that list of offending zone IDs into your Adcash campaign settings and add them to your exclusions there. ValidVisit’s job stops at handing you the ranked list and the reasoning behind it; the block itself happens in your Adcash account.
Doesn’t pop’s low engagement drag every visit’s score down?
No — the 0–100 score draws on more than 100 data points spanning the network a click came from, the device behind it and how the visitor behaves, not on blunt stand-ins like time-on-page or scroll depth that are naturally thin for pop. A real person closing a popped tab after three seconds still looks nothing like an automated client or a hosting-network visit firing the same event once you look at the full picture — which is exactly why this kind of scoring works for a format that intent-based metrics can’t evaluate fairly.
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See which publishers and placements send real buyers vs bots — every visit scored 0–100, worst first.
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