zone / feed in ClickaduValidVisit flags the bad zone/feed id; paste it into Clickadu's campaign blacklist.
Clickadu operates as a popunder and pop-up exchange where delivery is counted in tab-load events rather than deliberate user clicks. That mechanic opens a specific accountability gap: a page load fires whether or not a human triggered it, so bot operators and low-quality publisher zones can pile up delivery counts that look identical to real visits until you dig below the campaign surface. ValidVisit closes that gap by weighing each inbound click against 100+ independent data points — covering the network and route the visit travelled, the device sitting behind it, and how the visitor actually behaves once the page is open — and folding all of them into a single 0-100 quality score. Genuine humans clear that bar comfortably; automation, click farms, and proxy-routed traffic stand out. Because Clickadu passes the originating zone through its {zoneid} macro, ValidVisit can pin every score to the exact zone that sent the visit, turning an otherwise opaque volume channel into a ranked list of sub-sources you can review and manually exclude inside Clickadu's campaign targeting interface.
https://yoursite.com/landing?utm_source=clickadu&utm_medium=pop&vv_campaign_id={campaignid}&vv_click_id=${SUBID}&vv_publisher_id={zoneid}&vv_creative_id={bannerid}Pop and popunder inventory scatters delivery across a wide zone pool, which means invalid traffic tends to arrive dispersed rather than concentrated — any single bad zone can look tolerable on its own while the aggregate quietly drains a meaningful share of budget with no obvious alert. On Clickadu specifically, the patterns ValidVisit most often surfaces fall into two distinct buckets. The first is infrastructure-level automation: visits that come from hosting ranges or residential-proxy pools where the IP looks like a consumer ISP but the wider picture points to a server farm or proxy provider. These visits usually carry a believable browser user-agent yet score poorly because too many of the supporting data points disagree with what a real browser on a real connection would produce. The second bucket is session-shell traffic: the pop fires, the page technically loads, but nothing a genuine person would generate follows — no real engagement, no natural timing, no sign of a live session. ValidVisit catches this even when the on-page environment has been carefully dressed up to look human, because the score draws on so many independent signals at once that a hollow session can't satisfy all of them. Both buckets resolve to specific {zoneid} values in ValidVisit's reporting, so you can tell a zone with a structural automation problem apart from one that simply draws a geo with lower engagement.
Rank your active zones by average ValidVisit score using the {zoneid} token. Pop networks spread delivery across a long tail of publisher zones, and a small handful of those zones will usually account for a wildly disproportionate share of low-scoring visits. Pulling those zones out manually inside Clickadu's targeting interface is the single biggest lever for lifting traffic quality without cutting volume across the board.
Residential-proxy operations thrive on pop inventory because the tab-fire event needs no sustained interaction, which makes it cheap for bot farms to cycle through proxy pools. The score reflects when a visit's origin looks like a hosting or proxy provider even though the IP presents as residential, and ValidVisit surfaces the associated {zoneid} so you can exclude the zone rather than sacrificing an entire geo.
ValidVisit's quality score weighs how a visitor actually behaves after the page opens, independent of any single on-page check. On Clickadu pop traffic, clusters of low-behavior, low-scoring visits tied to specific zones are a strong tell for session-shell traffic — cases where the tab-load event fired but no real browser session followed. Because the score leans on many signals together, it still catches automation that has been hardened against any one conventional check.
Use the {campaignid} token alongside {zoneid} to track whether a campaign's zone pool composition drifts over time. A sudden jump in the share of delivery coming from zones with consistently poor scores — with no matching change in your targeting settings — can mean low-quality zones are backfilling available inventory as the better zones hit their delivery caps.
Each Clickadu macro maps to a normalized parameter, so every scored click is pinned to the right campaign, creative and publisher.
| Token | Clickadu macro | Maps to | Identifies |
|---|---|---|---|
| Campaign ID | {campaignid} | campaign_id | campaign |
| Click ID (SubID) | ${SUBID} | click_id | click |
| Zone ID | {zoneid} | publisher_id | publisher |
| Banner/Creative ID | {bannerid} | creative_id | creative |
{campaignid}${SUBID}{zoneid}{bannerid}Clickaduitself 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 Clickadu tokens, not by creative (which says nothing about whether a click was human).
Illustrative example — Clickadu traffic scored 0–100 per sub-source, worst first.
See your own Clickadu sub-sources scored this way.
Bot / invalid-traffic score broken down by:
{zoneid}ID of the ad zone (publisher site/zone) where the ad was displayed.Per-click id: Clickadu 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 is a detection and reporting tool. It scores traffic after the click has already arrived and never blocks, diverts, or intercepts anything in the click path. What you get is a scored, zone-attributed record of every visit: you see which {zoneid} values are sending a disproportionate share of low-scoring traffic, export that list, and then manually add those zones to the exclusion list inside your Clickadu campaign targeting. The value is in making that zone-level call with signal instead of guesswork — the exclusion itself happens inside Clickadu's interface, not inside ValidVisit.
For diagnosing traffic quality, {zoneid} is the primary dimension. Invalid traffic on pop inventory originates at the publisher zone — the individual site or zone group that fires the pop event — not at the campaign level. {campaignid} is useful for working out which of your campaigns is drawing from a particularly rough zone pool, and for separating performance issues that are zone-driven from ones that might reflect targeting or landing-page factors. The actionable exclusion unit, though, is always the zone.
Clickadu applies platform-level filtering aimed at protecting delivery integrity across its whole network. That filtering isn't transparent to you as an advertiser — you can't see what was filtered, which specific zones were dropped, or whether the thresholds match your own campaign's risk tolerance. ValidVisit runs on your side of the click, scoring traffic against your campaign's actual conditions by weighing 100+ independent data points into a single 0-100 quality score, then tying that score to specific {zoneid} values. The two layers answer different questions: Clickadu's filtering is about network-wide delivery hygiene; ValidVisit is about understanding which sub-sources inside Clickadu's delivery are polluting your conversion and optimization data.
See which campaigns and publishers send real, converting traffic vs bots — every click scored 0–100.
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