placement in AdsterraValidVisit flags the bad placement / domain; block those placement IDs in Adsterra's campaign settings.
Adsterra operates one of the largest push notification and pop-under networks on the web, aggregating inventory from thousands of independent publishers across dozens of verticals and geographies. That scale is a genuine asset for reach — and a genuine challenge for traffic quality. Push notification inventory is built on subscriber lists that publishers accumulate over time; when those lists age, get traded, or are inflated through incentivized opt-ins, the clicks that flow from them look nothing like genuine user intent. Pop-under and direct-link placements introduce a different pressure: automated tools can cycle through landing page URLs in non-interactive sessions, generating click events without a human ever engaging with the content. ValidVisit examines every click arriving from Adsterra and reduces it to a single 0–100 quality score drawn from 100+ independent data points — covering the network the click came from, the device behind it, and how the visitor behaves — so you can pinpoint the specific zones and placements generating the problem and exclude them directly inside your Adsterra campaign settings.
https://yoursite.com/landing?utm_source=adsterra&utm_medium=push&vv_click_id=##SUB_ID_SHORT(action)##&vv_campaign_id=##CAMPAIGN_ID##&vv_placement_id=##PLACEMENT_ID##&vv_publisher_id=##ZONE_ID##&vv_creative_id=##BANNER_ID##Push and pop inventory on Adsterra expose different IVT mechanics, and both are worth watching. On the push side, the clearest signal is subscriber-list automation: clicks arrive in tight mechanical bursts from a narrow set of network origins rather than the organic scatter of real users opening notifications across different times and connections. The same cloud-hosted infrastructure showing up repeatedly against one Zone ID is a particularly strong tell — genuine push subscribers receive notifications on residential or mobile connections, not server farms. Proxies and VPN exit nodes are a secondary pressure, used by bad actors to make automated traffic appear geographically diverse and obscure its true origin.
On the pop and direct-link side, the picture shifts toward how the visiting session actually behaves once it lands. ValidVisit weighs each click against 100+ separate data points — what kind of environment the session is running in, whether its device characteristics hang together the way a real browser's would, and whether the on-page behavior matches a human reading a page rather than a script touching a URL — and folds all of it into one 0–100 quality score. Automated click injectors that never really render the page tend to leave gaps across several of those measurements at once, even when their headline click event looks clean. Because Adsterra passes Zone ID (##ZONE_ID##) and Placement ID (##PLACEMENT_ID##) at the click level, every quality score can be mapped directly to the sub-source that generated it, making it straightforward to tell whether a problem is isolated to one underperforming zone or spread across a broader slice of inventory.
When a single ##ZONE_ID## value produces a disproportionate share of clicks within a short window — and those clicks share near-identical session durations with no downstream micro-events — you are likely seeing subscriber-list automation rather than real engaged users. Filter your ValidVisit reports by zone to isolate and review these clusters before excluding the zone in Adsterra campaign settings.
##PLACEMENT_ID## segments that show sustained click volume but zero conversions or engagement signals across multiple days are worth treating as a quality flag. ValidVisit's quality score separates bot-driven clicks from simply low-intent human traffic, which matters for the decision to exclude a placement outright versus adjusting your bid or creative for that segment.
Genuine push subscribers are overwhelmingly on residential and mobile network connections. When ValidVisit surfaces a concentration of clicks originating from hosting infrastructure tied to the same ##ZONE_ID##, it indicates the subscriber list behind that zone contains automated or non-human entries — not real opted-in users. The ##SUB_ID_SHORT(action)## token lets you trace the click chain back to the originating action for additional context.
Pop-under and direct-link placements are a common target for non-interactive browser automation because the format requires no visible user gesture. ValidVisit looks at how each session actually loads and behaves once it reaches your page; a ##PLACEMENT_ID## where a meaningful share of clicks never show the on-page behavior of a real visit is a sign that those sessions are not running in a genuine browser environment.
Each Adsterra macro maps to a normalized parameter, so every scored click is pinned to the right campaign, creative and publisher.
| Token | Adsterra macro | Maps to | Identifies |
|---|---|---|---|
| Click ID (Sub ID) | ##SUB_ID_SHORT(action)## | click_id | click |
| Campaign ID | ##CAMPAIGN_ID## | campaign_id | campaign |
| Placement ID | ##PLACEMENT_ID## | placement_id | placement |
| Zone ID | ##ZONE_ID## | publisher_id | publisher |
| Banner ID (Creative) | ##BANNER_ID## | creative_id | creative |
##SUB_ID_SHORT(action)####CAMPAIGN_ID####PLACEMENT_ID####ZONE_ID####BANNER_ID##Adsterraitself 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 Adsterra tokens, not by creative (which says nothing about whether a click was human).
Illustrative example — Adsterra traffic scored 0–100 per sub-source, worst first.
See your own Adsterra sub-sources scored this way.
Bot / invalid-traffic score broken down by:
##ZONE_ID##Zone identifier (publisher/site zone) the traffic originated from.Bot / invalid-traffic score broken down by:
##PLACEMENT_ID##ID of the actual traffic source / placement where the ad was shown.Per-click id: Adsterra 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.
The two most diagnostic tokens are ##ZONE_ID## and ##PLACEMENT_ID## — they identify the publisher inventory unit generating each click and are the dimensions you will actually use to make exclusion decisions inside Adsterra. Append them to your destination URL as ValidVisit query parameters so the quality score is tied to the exact zone and placement. ##CAMPAIGN_ID## is useful for campaign-level segmentation, and ##SUB_ID_SHORT(action)## gives you the action-level click identifier for tracing click chains. No funnel hop is involved — ValidVisit reads these values on arrival and scores the click in place.
ValidVisit is a detection and scoring tool, not an enforcement layer. Every click receives a 0–100 quality score visible in the dashboard, and you can export the high-risk zone and placement IDs that emerge from that analysis. The exclusion step is manual: take those ##ZONE_ID## and ##PLACEMENT_ID## values and submit them as source exclusions inside your Adsterra campaign settings. That workflow keeps you in control of the decision and means you are excluding based on validated signal, not automated rules.
Adsterra's internal reporting confirms that a click was delivered and billed within its system. ValidVisit measures what happens on your landing page after that click arrives, weighing the visit against 100+ independent data points — where the session came from, what the device behind it looks like, and how the visitor behaves on the page — and collapsing them into one 0–100 quality score. An automated session can produce a click that clears the network's delivery validation while still scoring low here, because the network it rode in on, the device it claims to be, or its behavior on arrival simply don't add up to a real human. That post-arrival layer is where ValidVisit operates, and it is orthogonal to what any network's own fraud filter measures.
See which campaigns and publishers send real, converting traffic vs bots — every click scored 0–100.
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