Media & Advertising
Keep automated clicks off your paid campaigns, keep fake signups out of your first-party audiences, and let the AI assistants that send you readers through.
Every automated visit costs someone money
Click farms and automated scripts hit paid campaigns. Scrapers copy articles at scale. Fake signups fill registration walls. Meanwhile search crawlers, AI assistants, and syndication partners read the same pages, and they bring the audience.
Treat it all as one block and you lose the distribution that fills the funnel. Treat none of it as risk and your numbers stop holding up with advertisers. CHEQ classifies each entity: what it is, whether it is authentic, and what it intends.
Buy and sell media against real audiences, not automation
Media businesses are paid per click, impression, and registration. Automation produces all three, so budget drains and reported performance drifts from what actually happened.
Protect media spend
Keep budget aimed at audiences that exist instead of automation that clicks and leaves.
Report real numbers
Give clients and advertisers campaign and audience figures that reflect people, not automated sessions.
Keep audiences real
Protect the value of registration lists and retargeting pools you built to sell against.
Stay readable
Decide which crawlers and AI assistants read your archive, and at what rate.
The automation media actually faces
Media threats sit on both sides of the transaction: the campaigns you buy and the inventory and content you sell. Each calls for a different response.
Paid campaign click fraud
Automated clicks drain the search and social budgets you manage, and the charge lands before any report shows the campaign underperforming.
Polluted retargeting audiences
Invalid visits enter retargeting and lookalike pools, so the next campaign spends its budget finding more of the automation that built the audience.
Affiliate and partner fraud
Partners paid per click or lead have every reason to inflate volume, and sourced visits arrive looking ordinary until they are classified by source.
Invalid visits on your inventory
Automated visits to your articles register as impressions you bill an advertiser for, and the advertiser's own measurement flags the discrepancy back to you.
Content and archive scraping
Aggregators and content farms pull whole articles and republish them, so your work ranks and earns somewhere you do not control.
AI crawlers and assistants
Assistants cite your reporting and send readers back. Training crawlers consume the archive without that referral. Both arrive as automation and need different answers.
Fake registrations
Registration walls and newsletters carry the first-party audience media sells against. Bulk automated signups fill it with records that were never people.
Subscriber account takeover
Credential lists get replayed against your paywall login, and a working subscription is resold or shared until the real subscriber cancels.
Third-party ad script risk
Ad-funded pages carry more third-party creative and measurement scripts than anyone reviews, and a changed one reads your audience data from inside the page.
Why this holds up when clicks are billed
Media buying is judged on numbers someone else audits, and access decisions on your content are commercial. Both need a verdict you can explain.
Triple-layer intelligence
Click farms defeat any single filter, so Traffic, Trust, and Identity are weighed together.
Proportional enforcement
Rate-limiting a training crawler costs nothing in referrals, while cutting off a citing assistant does.
Defensible reporting
Reason codes reach individual UTMs, devices, and geos, so a client challenge can be answered with evidence.
Built into ad platforms
Classifications reach Google Ads, Meta, LinkedIn, TikTok, and DV360 as exclusions, not a separate console to check.
Media compliance obligations
Media and advertising pages carry heavy third-party data collection, and consent choices have to hold across every tag on them.
Advertising consent enforcement
Helps enforce consent choices on advertising and measurement tags, so a rejected purpose does not fire anyway.
Opt-out signal handling
Supports honoring opt-out preferences across the third-party tags collecting on your pages, with a real-time audit log.
Ad script visibility
Detects unauthorized or misbehaving scripts on ad-funded pages before they leak reader data or skew measurement.
Related solutions and industries
Media & advertising questions
How does CHEQ identify invalid clicks when the ad platform already reports the campaign as clean?
CHEQ classifies the visit after the click, on your own pages, rather than relying on the ad platform’s own reporting. An ad platform sees its own delivery. CHEQ’s detection runs on the page the click lands on, where the session itself can be assessed.
Each visit runs through more than 2,000 cybersecurity challenges, which supports classification across three signal families:
- Traffic Intelligence, covering environment and behavioral signals, spoofing, and network anomalies
- Trust Intelligence, covering what runs inside the session
- Identity Intelligence, covering risk scoring, synthetic identity signals, and cross-session consistency
Because the classification happens on your side, reporting goes down to individual UTMs, devices, and geos, and invalid IP addresses can be blocked in real time in Google Ads.
Can CHEQ keep bots out of retargeting and lookalike audiences?
Yes. Invalid entities can be excluded from targeting audiences down to the individual campaign, so a polluted pool does not compound into the next flight.
This matters because retargeting spends against an audience you already built. Every automated visit that enters it becomes budget aimed at more of the same.
Audience exclusion is supported across the platforms media teams actually buy on:
- Search and social, including Bing, Meta, LinkedIn, X, Reddit, TikTok, Snapchat, and Pinterest
- Video and display, including YouTube, DV360, and Criteo
- Regional platforms, including Yahoo, Yandex, and Baidu
Google Ads adds real-time IP blocking, so repeat invalid clicks can be blocked rather than reclaimed after the fact.
How does CHEQ handle AI crawlers that use your content without sending readers back?
CHEQ classifies each crawler as its own entity and surfaces what it is and what it appears to be doing, so access becomes a decision you make rather than a default.
Not all automation is adversarial. For a media business, being read and cited is part of how the audience arrives, so the useful distinction is not automated versus human.
CHEQ separates crawlers into entity types that can carry different policy:
- Search engine crawlers, where indexing is the point
- AI assistants answering a live query, where a citation can return a reader
- Training and bulk extraction crawlers, where the archive is consumed at scale
- Undeclared automation, where the operator does not identify itself at all
Identification looks at the operator and ownership chain behind the request rather than the user-agent string it declares. Because enforcement is proportional, an unfamiliar crawler can be monitored or throttled while you decide.
How does CHEQ keep fake signups out of a registration wall or newsletter list?
CHEQ assesses each registration during the session and passes a verdict into the systems your audience team already runs, so a fake record is flagged before it enters the list.
For a media business the cost is not the signup itself, it is what the list is used for. A registration wall exists to build a first-party audience you can sell against, and inflated records make that audience less valuable, not more.
Several signal types combine at the point of submission:
- User data validation, which flags suspicious or invalid email addresses and phone numbers
- Identity Intelligence, covering risk scoring, synthetic identity signals, and cross-session consistency
- Behavioral and network signals, which reflect how the form was completed rather than only what it contains
Detection is calibrated against your own confirmed abuse, so a free newsletter and a paid subscription can carry different bars.
How does CHEQ identify fraud coming from affiliates and media partners?
By classifying every visit by its source, so invalid activity can be attributed to the partner that sent it rather than absorbed into a channel total.
Partners paid per click, lead, or signup have a direct incentive to inflate volume, and sourced visits arrive on your pages looking like any other.
Log-level reporting exposes that activity in the detail an escalation needs:
- By source and campaign, so a single partner can be isolated rather than a whole channel
- By UTM, device, and geo, which is where coordinated patterns become visible
- By threat type, so each classification carries the reason codes behind it
CHEQ’s threat research has traced this pattern before. In one investigation, 10 million fraudulent affiliate visits were identified for People Connect, isolating botnet patterns and enabling partner escalation.
How does CHEQ fit into an existing media and advertising stack?
CHEQ’s classifications are built to move into the systems your team already runs rather than living in a separate console. The data is designed to be granular, explainable, portable, and integrable.
On the buying side, classifications support audience exclusion across Google Ads, Bing, Meta, LinkedIn, TikTok, YouTube, DV360, and Criteo, plus real-time IP blocking in Google Ads.
On the measurement side, pre-built connectors cover Adobe Analytics, GA and GA360, Amazon S3, and a retrospective data API for exporting classifications. CHEQ is an Adobe Gold Technology Partner, and 55% of its top 250 customers run on Adobe.
On the site side, classifications reach infrastructure through CloudFront and Cloudflare, so the verdict is available at the edge and not only in reporting.
Ready to tell real audiences from automation?
Your last campaign, with automated clicks separated from the readers you actually paid for.