Snapchat Ads operates across two meaningfully different supply tiers. The first is Snapchat's own inventory: Discover, Story, and Spotlight placements where traffic is authenticated Snapchat users. The second is the Snap Audience Network (SAN) — an off-platform SDK network that lets third-party app developers monetize through Snapchat's demand. That second tier is where invalid traffic (IVT) risk concentrates. SAN publishers are independent app developers; inventory quality varies by property, and advertisers almost always see blended campaign metrics that obscure which individual publisher is dragging down performance. ValidVisit closes that gap by scoring every inbound click after it lands, attaching a single 0-100 quality score per click, and mapping each session to the site_source_name dimension that Snapchat surfaces in its own reporting — so you can identify specific SAN properties generating suspicious patterns, rather than making exclusion decisions blind from aggregate data.
https://yoursite.com/landing?utm_source=snapchat-ads&utm_medium=social&vv_campaign_id={{campaign.id}}&vv_campaign_name={{campaign.name}}&vv_adset_id={{adSet.id}}&vv_ad_id={{ad.id}}&vv_creative_id={{creative.name}}&vv_publisher_id={{site_source_name}}&vv_click_id=ScCidTwo distinct IVT patterns show up on Snapchat campaigns, and they tend to concentrate in different parts of the supply stack. The first is mobile emulator traffic from the Snap Audience Network. Operators running Android or iOS emulators at scale push synthetic click events through publisher SDKs, and those sessions behave like server hardware dressed up as a handset rather than a genuine mobile phone — the kind of contradiction that surfaces when ValidVisit weighs each click against 100+ independent data points covering the network it arrived on, the device underneath it, and how the visitor actually behaves, then folds them into one 0-100 quality score. The second pattern is proxy and server-farm-routed traffic that arrives on Snapchat's owned surfaces — Discover and Story placements — by way of residential proxy chains or rented server ranges, often tied to incentivized click operations chasing app-install or lead-gen offers. These sessions look superficially mobile (correct user-agent, mobile-range screen resolution) but the picture falls apart once their network origin and behavior are weighed together against everything a real human session looks like. On the publisher side, Snapchat's site_source_name token is the most actionable diagnostic dimension available: when a single SAN property produces a disproportionate share of low-scoring clicks — well above your campaign's own baseline — that sub-source is the variable worth isolating, not the ad set or the creative. ValidVisit scores each click and records the ScCid alongside it so you can cross-reference suspicious sessions with Snapchat's own click log rather than relying solely on downstream conversion discrepancies to spot the problem.
In your ValidVisit dashboard, segment by the site_source_name dimension and look for any single publisher property whose click volume and quality-score distribution diverge sharply from the rest of your SAN mix. Legitimate app-publisher traffic spreads across varied session times and network origins; a bot-heavy property shows compressed session characteristics with a disproportionate share of low quality scores relative to your campaign baseline.
Snapchat appends a unique ScCid to each click. ValidVisit flags sessions where the same ScCid appears across multiple distinct IP addresses or devices — a pattern consistent with click parameter recycling rather than genuine individual users following an ad.
Snapchat's user base is almost entirely on iOS and Android handsets. ValidVisit's scoring isolates sessions that present a plausible mobile user-agent string but whose underlying device and connection profile read like server or emulator infrastructure instead of a real phone — exactly the kind of emulator-driven bot traffic that can spoof the surface but not the full behavior of a genuine device.
Owned Snapchat surfaces (Discover, Story) are not immune to proxy-routed click farm traffic. By weighing the network origin of every click as one of its 100+ data points, ValidVisit drops the quality score on sessions traced to known server ranges and residential proxy pools, giving you an IVT signal even on clicks that present as ordinary mobile visits.
Each Snapchat Ads macro maps to a normalized parameter, so every scored click is pinned to the right campaign, creative and publisher.
| Token | Snapchat Ads macro | Maps to | Identifies |
|---|---|---|---|
| Campaign ID | {{campaign.id}} | campaign_id | campaign |
| Campaign Name | {{campaign.name}} | campaign_name | campaign |
| Ad Set ID | {{adSet.id}} | adset_id | adset |
| Ad ID | {{ad.id}} | ad_id | ad |
| Creative Name | {{creative.name}} | creative_id | creative |
| Site Source Name | {{site_source_name}} | publisher_id | publisher |
| Snapchat Click ID (ScCid) | ScCid | click_id | click |
{{campaign.id}}{{campaign.name}}{{adSet.id}}{{ad.id}}{{creative.name}}{{site_source_name}}ScCidSnapchat Adsitself 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 Snapchat Ads tokens, not by creative (which says nothing about whether a click was human).
Illustrative example — Snapchat Ads traffic scored 0–100 per sub-source, worst first.
See your own Snapchat Ads sub-sources scored this way.
Bot / invalid-traffic score broken down by:
{{site_source_name}}App or site (publisher) where the ad was served; useful for Snap Audience Network attribution.Per-click id: Snapchat Ads 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 operates at the click level rather than the conversion-event level, so it is compatible with both Snapchat's browser pixel and its Conversions API (CAPI). When a user clicks your ad, Snapchat appends the ScCid to the destination URL. ValidVisit scores that session once it arrives and records the 0-100 quality assessment alongside the ScCid in its dashboard. From there, you can cross-reference low-scoring ScCids with your MMP or CRM records and choose to exclude those events from your CAPI payload manually — giving you a cleaner conversion signal without any automated interception of the click path.
The site_source_name parameter is the most diagnostic for SAN inventory — it identifies the specific third-party app publisher behind each click. Passing ScCid links each scored session back to Snapchat's own click record. If you run multiple ad sets or creatives, including the ad set ID and ad ID lets you isolate whether IVT is clustering around a particular targeting group versus a specific publisher. For SAN campaigns in particular, site_source_name is the variable that most directly maps to the exclusion decision you will make in Ads Manager.
ValidVisit does not write to your Snapchat Ads Manager settings — it produces the scored, site_source_name-attributed data you need to make that decision yourself. Once you identify which publisher properties consistently generate low quality scores, you can exclude those specific site_source_name values inside Ads Manager's placement targeting controls. That surgical approach lets you retain the SAN publisher relationships that produce clean traffic while removing the ones that do not, rather than abandoning off-platform inventory as a whole.
See which campaigns and publishers send real, converting traffic vs bots — every click scored 0–100.
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