PushWhich EvaDav zones send real traffic?
Not all EvaDav 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 + sub-source in EvaDavThe buyer creates an Audience (a named list of zone IDs / source IDs pasted comma-separated, or auto-filled by automated rules on spend/lead conditions), marks it as a blacklist, then attaches it in the campaign's Targeting & Audiences > Blacklist field (type first 3 chars of the audience name and select).
ValidVisit reports the device, OS, browser — down to the version — plus the language and ISP behind every flagged visit, and EvaDav supports OS version, browser, language, device type and connection type targeting. The segments we flag are segments you can exclude.
How invalid traffic slips in through EvaDav zones.
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 the visit 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.
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.
What to watch on EvaDav
Rank active {zoneid} values by quality and by the share of visits 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.
Pinpoint the bot publishers & placements in EvaDav.
EvaDav 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 EvaDav tokens, not by creative (which says nothing about whether a click was human).
Bought as one EvaDav line, your spend is a single number. Scored per sub-source it runs from 82 down to 14 — the worst is nearly all bots. That’s the leak a blended average hides.
EvaDav traffic scored 0–100 per sub-source, worst first — down to the placement you buy.
Bot / invalid-traffic score broken down by:
- Zone ID
{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 visit.
Compare bot & invalid-traffic breakdown across every ad network →See your own EvaDav sub-sources scored this way.
How ValidVisit attributes EvaDav traffic
Each EvaDav 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=evadav&utm_medium=push&vv_campaign_id={CAMPAIGN_ID}&vv_publisher_id={ZONE_ID}&vv_source={SOURCE_ID}&vv_click_id={CLICKID}| 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 |
- EvaDav macro
{CAMPAIGN_ID}- Maps to
- campaign_id
- Identifies
- campaign
- EvaDav macro
{ZONE_ID}- Maps to
- publisher_id
- Identifies
- publisher
- EvaDav macro
{SOURCE_ID}- Maps to
- source
- Identifies
- source
- EvaDav macro
{CLICKID}- Maps to
- click_id
- Identifies
- click
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 zone + sub-sources on EvaDav.
Scoring and attribution are the means — the point is cutting the EvaDav 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 EvaDav 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 EvaDav zone + sub-source and zone via the network's own tokens — so the bad traffic has an address, not just a headline percentage.
- Cut
Take the zone + sub-sources 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 EvaDav and put your next dollar behind the traffic that converts.
EvaDav traffic quality, answered.
How do I set up ValidVisit for EvaDav?+
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 visit, segmented by zone and campaign, with nothing on the click path.
Can ValidVisit tell me which EvaDav zones to blacklist?+
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.
How does ValidVisit handle EvaDav's push subscriber traffic?+
Push visits 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}.
Detect fraud on other push networks
Find the bots in your EvaDav spend.
See which publishers and placements send real buyers vs bots — every visit scored 0–100, worst first.
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