zone in EvaDavValidVisit ranks the bad {ZONE_ID}; add those zones to your EvaDav campaign blacklist.
EvaDav is a self-serve push, pop and native network built on a large subscriber and publisher base. Its reporting is organised around the {zoneid} — the EvaDav publisher identifier each click came from — with a {source_id} carrying the fuller source segment, plus {campaign_id} and a {clickid}. The zone is the unit you blacklist in the campaign, so zone-level intelligence turns directly into action. ValidVisit captures these tokens as each click lands, then measures it against 100+ independent data points — the network path it travelled, the device on the other end and the way the visitor actually behaves — and rolls them into a single 0–100 quality score, so real people clear and automation surfaces. It reports which zones carry non-human traffic.
https://yoursite.com/landing?utm_source=evadav&utm_medium=push&vv_campaign_id={CAMPAIGN_ID}&vv_publisher_id={ZONE_ID}&vv_source={SOURCE_ID}&vv_click_id={CLICKID}EvaDav's push and pop formats inherit the quality of the underlying subscriber lists and publisher zones. On the push side, the defining variable is how a subscriber feed was acquired: feeds built on incentivised or bot-inflated opt-ins click in unnaturally regular bursts aligned to send windows, and when ValidVisit weighs that pattern against the full set of behavioural and environmental data points it carries, it stands apart from a genuine subscriber.
On the pop side, the issue is automated page-loaders firing events from hosting or proxy infrastructure, concentrated in specific {zoneid} values. Across both, clicks whose technical and behavioural picture simply doesn't add up to a real browser — and zones with a thin, machine-like interaction profile — pull low quality scores that point to automation rather than real users. Because {zoneid} and {source_id} ride on every click, ValidVisit attributes all of these to the individual zone, so one bad zone is separable from a clean campaign.
Rank active {zoneid} values by quality and by the share of clicks in the suspicious/bad tier. Zones above your baseline are blacklist candidates.
Unnaturally even click bursts aligned to notification schedules point to bot-inflated subscriber feeds; ValidVisit flags the zones where that concentrates.
Pop clicks routed through cloud servers or proxies rarely convert. ValidVisit ties each such finding back to the {zoneid} so you blacklist the offending zones cleanly.
A cluster of clicks whose device and behaviour signals don't resolve to a real browsing session points to automation — far harder to disguise than a user-agent string.
Each EvaDav macro maps to a normalized parameter, so every scored click is pinned to the right campaign, creative and publisher.
| Token | EvaDav macro | Maps to | Identifies |
|---|---|---|---|
| Campaign ID | {CAMPAIGN_ID} | campaign_id | campaign |
| Zone ID | {ZONE_ID} | publisher_id | publisher |
| Source ID | {SOURCE_ID} | source | source |
| Click ID | {CLICKID} | click_id | click |
{CAMPAIGN_ID}{ZONE_ID}{SOURCE_ID}{CLICKID}EvaDavitself 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 EvaDav tokens, not by creative (which says nothing about whether a click was human).
Illustrative example — EvaDav traffic scored 0–100 per sub-source, worst first.
See your own EvaDav sub-sources scored this way.
Bot / invalid-traffic score broken down by:
{ZONE_ID}EvaDav publisher / zone identifier — the unit you blacklist in the campaign.Per-click id: EvaDav 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.
Add ValidVisit's script to your landing page and append EvaDav's macros — {zoneid}, {source_id}, {campaign_id} and {clickid} — to your destination URL. The pixel captures them as the click lands and stores a scored verdict per click, segmented by zone and campaign, with nothing on the click path.
Yes. Because {zoneid} is on every click, ValidVisit ranks your zones by quality and by what is dragging their scores down, and you blacklist the offenders in your EvaDav campaign. ValidVisit reports the evidence; the blacklist is applied in your account.
Push clicks run through the same 0–100 scoring as everything else, with timing regularity folded into the 100+ data points: a feed built on incentivised or bot subscribers clicks in unnaturally even bursts, which separates it from a genuine subscriber and pins it to the {zoneid}.
See which campaigns and publishers send real, converting traffic vs bots — every click scored 0–100.
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