Every visitor that hits your site is different. Some are real prospects; some are just researching; others are bots, scrapers or organized traffic sources. Until you see that difference, your ad budget is split equally across all of them and impossible to optimize.
wall.click's traffic management module labels each incoming session with a 0-100 risk score. Low risk (real user) → medium risk (extra verification) → high risk (block): you can apply different policies per segment and route your campaign budget more intelligently.
What you gain
What you get with this solution
Behavior analysis
Distinguish real users from bots with 15+ signals: time on page, scroll depth, mouse movement, keyboard interaction.
Risk segmentation
Low / Medium / High risk groups; define different rules and actions per group.
Geo filtering
Automatically filter clicks from outside your target region (country, city, GPS radius).
Source-based rules
Tailored rules for traffic from specific referrers, campaigns or UTM parameters.
Multi-channel protection
Risk-score not only Google Ads, but Meta, TikTok and organic traffic too.
Real-time insights
Get alerts within minutes when abnormal traffic spikes are detected; respond fast under attack.
Problem
If you don't know your traffic, you can't defend it
Most advertisers know their visitors only through superficial Google Analytics metrics: session count, bounce rate, time on page. These metrics do not separate a bot from a real customer; a bot visiting 1,000 times is counted as 1,000 separate "sessions".
What does opaque traffic actually cost?
Every optimization made on opaque traffic sits on a flawed foundation. Because you don't know which ad group brings real customers, budget shifts, new campaign decisions and A/B test results all mislead you.
Geo-targeting isn't enough
Setting Google Ads to "Turkey only" does not stop proxy and VPN traffic with fuzzy IP geography. wall.click verifies the real geographic origin using extra signals like ASN, datacenter markers and language/location mismatches.
Be proactive about attacks, not reactive
Sudden traffic spikes (e.g. 10,000+ clicks/hour) usually mark the beginning of an organized attack. If you stay reactive, your budget burns out within half a day. wall.click alerts you in the first 5 minutes and can switch to aggressive mode automatically.
Method
30+ signals we collect
Any single-signal filter is easy to bypass. wall.click correlates dozens of signals:
- IP reputation: known bot networks, Tor exit nodes, datacenter ASN lists
- Geographic location: consistency between country, city, ASN and ISP
- Device fingerprint: User-Agent, screen resolution, browser plugins, GPU
- Session behaviour: mouse movement, scroll speed, interaction count
- Click pattern: per-IP frequency, time-of-day regularity
- Source validation: Referer, UTM, campaign consistency
- Conversion correlation: whether the same IP has converted previously
Segmentation
How risk scoring works
Every visitor is assigned a risk score from 0-100. It is a weighted sum of the signals above and is continuously updated.
- 1
0-30 — Low risk (real user)
Consistent geography, genuine behavioural signals, clean IP reputation. No intervention; flagged as "clean" in reporting. - 2
31-70 — Medium risk (suspicious)
Some signals are suspicious but not conclusive. Extra verification (CAPTCHA, silent challenge) is recommended; no block. - 3
71-100 — High risk (very likely invalid)
Multiple suspicious signals triggered together. Auto-block recommended; IP added to your Google Ads negative list.
Impact
Tangible effects of traffic management
52%
Faster attack detection
wall.click vs. manual monitoring
<5 min
Time to detect abnormal traffic
Deviation from the hourly baseline
38%
Invalid sessions filtered
Geographic + behavioural signals combined
Usage
Recommended actions per risk segment
Low risk → Pass-through
Medium risk → Verification
High risk → Block
Surging traffic → Alert
FAQ