Which Kadam publishers send real traffic?
Not all Kadam traffic is equal. ValidVisit scores every visit 0–100 and pins it to the exact publisher that sent it — so you can tell real humans from bots and invalid clicks, worst publishers first.
site in KadamThe buyer pastes site IDs (one per line) into the campaign's site blacklist field — the list activates in ~10-15 minutes; alternatively clicks "Add to Blacklist" next to a site ID in the statistics report.
ValidVisit reports the device, OS, browser — down to the version — plus the language and ISP behind every flagged visit, and Kadam 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 Kadam publishers.
Kadam is a self-serve native-teaser and push network with a wide publisher base across global and CIS markets. Like other native inventory, its quality varies sharply by publisher, and the CPC teaser model gives some sites an incentive to maximise clicks over outcomes. Kadam exposes a {site_id} on every click — the publisher site the click came from, and the unit you blacklist in the campaign — plus {ad_id} and {campaign_id}, and a {click_id} for conversion matching. ValidVisit captures those on arrival and judges each visit against more than 100 independent data points — the network it came through, the device on the other end and how the visitor actually behaves — folding them into one 0–100 quality score, then reports invalid traffic per site so you can act on the specific publishers rather than the network as a whole.
Native teaser traffic on Kadam carries IVT shaped by the supply chain rather than the format. The dominant pattern is publisher arbitrage: a site acquires cheap visitors from pop or push sources, uses them to build teaser-impression volume, and a share of the resulting clicks come from low-intent visitors or automated sessions. Because these arrive through a real browser on a real publisher URL, IP-only filters miss them — ValidVisit doesn't lean on the address alone but reads the full picture of where the click originated and what's behind it, which matters because arbitrage sites often route through residential proxy pools that look ordinary on paper.
A second pattern is automated clicking from scripts and modified browser builds, easier to surface on native because the click path runs through several hops and the machinery behind the request rarely matches a genuine person sitting at a screen. A third is low-intent human traffic bounced onto teaser pages who click reflexively; the score separates this from automation, because the remedy differs — a bot-heavy {site_id} warrants a blacklist, a low-intent one may warrant a bid cut. All of it is attributed to the {site_id}.
What to watch on Kadam
Rank active {site_id} values by quality score and by the share of visits in the suspicious/bad tier. Sites well above your campaign baseline are blacklist candidates before you scale into them.
Arbitrage sites frequently route through residential or hosting proxies. ValidVisit ties each of those origin findings to the {site_id} so you blacklist the offending publishers without losing sites that deliver real users.
When a single {site_id} shows a cluster of clicks whose underlying technical and behavioural signals don't add up to a real browser, that points to automated clickers rather than people — patterns that hold up even when the user-agent looks plausible.
The quality score distinguishes automation from involuntary human arrival, so you can blacklist genuinely bot-heavy sites while only reducing bids on the merely low-intent ones.
Pinpoint the bot publishers & placements in Kadam.
Kadam 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 Kadam tokens, not by creative (which says nothing about whether a click was human).
Bought as one Kadam line, your spend is a single number. Scored per sub-source it runs from 83 down to 18 — the worst is nearly all bots. That’s the leak a blended average hides.
Kadam traffic scored 0–100 per sub-source, worst first — down to the placement you buy.
Bot / invalid-traffic score broken down by:
- Site ID
{site_id}Publisher site the click came from — the unit you blacklist in the campaign.
Per-click id: Kadam 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 Kadam sub-sources scored this way.
How ValidVisit attributes Kadam traffic
Each Kadam 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=kadam&utm_medium=native&vv_campaign_id={campaign_id}&vv_publisher_id={site_id}&vv_ad_id={ad_id}&vv_click_id={click_id}| Token | Kadam macro | Maps to | Identifies |
|---|---|---|---|
| Campaign ID | {campaign_id} | campaign_id | campaign |
| Site ID | {site_id} | publisher_id | publisher |
| Ad ID | {ad_id} | ad_id | ad |
| Click ID | {click_id} | click_id | click |
- Kadam macro
{campaign_id}- Maps to
- campaign_id
- Identifies
- campaign
- Kadam macro
{site_id}- Maps to
- publisher_id
- Identifies
- publisher
- Kadam macro
{ad_id}- Maps to
- ad_id
- Identifies
- ad
- Kadam macro
{click_id}- 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 sites on Kadam.
Scoring and attribution are the means — the point is cutting the Kadam 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 Kadam 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 Kadam site and zone via the network's own tokens — so the bad traffic has an address, not just a headline percentage.
- Cut
Take the sites 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 Kadam and put your next dollar behind the traffic that converts.
Kadam traffic quality, answered.
How do I set up ValidVisit for Kadam?+
Add ValidVisit's script to your landing page and append Kadam's macros — {site_id}, {ad_id}, {campaign_id} and {click_id} — to your destination URL. The pixel captures them on arrival and stores a scored verdict per visit, segmented by site and campaign, with nothing on the click path.
Can ValidVisit tell me which Kadam sites to blacklist?+
Yes. Because {site_id} is on every click, ValidVisit ranks your publisher sites by quality and by what is dragging the low scorers down, and you add the offenders to your Kadam campaign site blacklist. ValidVisit surfaces the evidence; the blacklist is applied in your Kadam account.
Native teaser clicks are cheap — won't real visits score poorly?+
No. The score rests on more than 100 technical and behavioural data points — where the click came from, the device behind it and how the visitor moves through the page — not on engagement proxies that are naturally low for teaser traffic. A real, briefly-engaged visitor looks completely different from an automated session or a proxy-routed click, so genuine human traffic isn't penalised.
Detect fraud on other native networks
Find the bots in your Kadam spend.
See which publishers and placements send real buyers vs bots — every visit scored 0–100, worst first.
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