PushWhich Mondiad zones send bots and invalid traffic?
Not all Mondiad 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 MondiadThe buyer pastes the bad ZoneIDs/SubIDs into the campaign’s Standalone blacklist, or saves them as a reusable Traffic Audience set to Blacklist mode and attaches it to campaigns (editing the audience updates every campaign using it); Smart Optimization Rules can auto-blacklist zones/SubIDs that spend without converting
ValidVisit reports the device, OS, browser — down to the version — plus the language and ISP behind every flagged visit, and Mondiad 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 Mondiad zones.
Mondiad is a self-serve push, native and pop network whose optimisation runs on the [zoneid] (a publisher, grouping many subids) and the granular [subid]. Both are units you can blacklist or custom-bid in the campaign, so zone/subid intelligence converts straight into action. Mondiad passes [zoneid], [subid], [campaignid] and a [clickid] on every click. ValidVisit captures these the moment the click lands, weighs the visit against 100+ independent data points — covering the network it came through, the device on the other end and how the visitor actually behaves — and folds them into one 0–100 quality score, then reports which zones and subids carry non-human traffic so you act on the exact sources rather than the campaign average.
Mondiad’s push inventory inherits the quality of its subscriber zones, and the pop/native side adds publisher-arbitrage pressure. The defining push pattern is subscriber-feed quality by zone: a [zoneid] built on incentivised or bot-inflated opt-ins clicks in unnaturally regular bursts aligned to send windows, and that mechanical rhythm is one of the things ValidVisit’s scoring weighs apart from a genuine subscriber.
Across formats, the same idea applies — genuine humans look nothing like server farms or automation routed through proxies, so the two sit at opposite ends of the score once 100+ signals about the network, the device and the visitor’s behaviour are combined. Automated traffic also tends to cluster inside specific zones rather than spread evenly across them. Because [zoneid] and [subid] ride on every click, ValidVisit attributes all of this back to the individual zone or subid — so a bad source is separable, and you can tell whether to blacklist it outright or simply lower its bid.
What to watch on Mondiad
[zoneid]) IVT distributionRank active [zoneid] values by quality and by the share of visits in the suspect/invalid tier. Zones above your baseline are blacklist or down-bid candidates.
Where a zone is mostly valid but one [subid] is bad, Mondiad’s custom-bid-by-subid lets you cut just that segment — ValidVisit scores at the subid level to support it.
Unnaturally even click bursts aligned to notification schedules point to bot-inflated subscriber zones; ValidVisit flags where that concentrates.
When low-quality clicks pile up inside one zone rather than spreading across them, that concentration is a strong tell for automation — and the 0–100 score makes it stand out against the human baseline.
Pinpoint the bot publishers & placements in Mondiad.
Mondiad 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 Mondiad tokens, not by creative (which says nothing about whether a click was human).
Bought as one Mondiad line, a buy reads as a single number. Scored per sub-source, a spread like this illustration runs from 86 down to 13 — the worst is nearly all bots. That’s the leak a blended average hides.
Illustrative: Mondiad traffic scored 0–100 per sub-source, worst first — down to the placement you buy.
Bot / invalid-traffic score broken down by:
- Zone ID
[zoneid]Publisher id (a group of subids) — the unit you blacklist or bid-adjust in the campaign.
Bot / invalid-traffic score broken down by:
- Sub ID
[subid]Granular sub-source within a zone, for per-subid optimisation.
Per-click id: Mondiad 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 Mondiad sub-sources scored this way.
How ValidVisit attributes Mondiad traffic
Each Mondiad 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=mondiad&utm_medium=push&vv_campaign_id=[campaignid]&vv_publisher_id=[zoneid]&vv_placement_id=[subid]&vv_click_id=[clickid]| Token | Mondiad macro | Maps to | Identifies |
|---|---|---|---|
| Campaign ID | [campaignid] | campaign_id | campaign |
| Zone ID | [zoneid] | publisher_id | publisher |
| Sub ID | [subid] | placement_id | placement |
| Click ID | [clickid] | click_id | click |
- Mondiad macro
[campaignid]- Maps to
- campaign_id
- Identifies
- campaign
- Mondiad macro
[zoneid]- Maps to
- publisher_id
- Identifies
- publisher
- Mondiad macro
[subid]- Maps to
- placement_id
- Identifies
- placement
- Mondiad 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 zones on Mondiad.
Scoring and attribution are the means — the point is cutting the Mondiad 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 Mondiad 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 Mondiad 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 Mondiad and put your next dollar behind the traffic that converts.
Mondiad traffic quality, answered.
What do I need to change in Mondiad to get ValidVisit scoring?
Add ValidVisit’s script to your landing page and carry Mondiad’s macros — [zoneid], [subid], [campaignid] and [clickid] — through your destination URL. The pixel reads them on arrival and stores a scored verdict broken out by zone and subid. Nothing changes about how the click itself fires; scoring is a post-arrival step.
How do I decide which Mondiad zones and subids to act on?
ValidVisit ranks every [zoneid] and [subid] you’ve run by its 0–100 quality score, since both ride on every click. You take that ranking and either blacklist or down-bid the offenders inside your Mondiad campaign — ValidVisit’s role stops at the report, the change itself is applied in your account.
For a low-scoring zone, is a blacklist or a bid cut the right move?
The score itself tells you which. A zone dragged down by traffic that reads as automated is a blacklist candidate outright, while one that’s merely full of low-intent but genuinely human visitors is often better handled with a lower bid — which is exactly why Mondiad supports custom bids at both the zone and subid level.
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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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