Fake Click Detection for Paid Ads
Spot fake clicks across your paid campaigns using click-level signals, repeat-behavior analysis and per-campaign risk scoring.
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A fake click costs you the same as a real one, but it never had any chance of converting. Didva detects fake clicks by analyzing the signals behind each paid visit: who, from where, how and how often, and scoring the ones that don't add up before they distort your results.
Fake clicks come from many directions: bots, click farms, proxy networks, accidental taps and repeat offenders. Individually they look like ordinary clicks, so they pass straight into your reporting, spend budget, and quietly drag down your conversion rate and bidding accuracy.
Track → Score → Block → Report → Optimize
A closed loop that turns raw paid clicks into clean, defensible traffic data.
- 1
Capture
Log each paid click with its IP, device, timing, source and behavior.
- 2
Flag
Detect the signals of fake clicks: abnormal timing, repeats, proxies and weak engagement.
- 3
Exclude
Cut the sources behind fake clicks from your campaigns.
- 4
Report
Show which campaigns and keywords attract the most fake clicks, with evidence.
- 5
Clean up
Keep fake clicks out of conversion data so optimization stays accurate.
Everything you need to protect paid traffic
Detection, blocking, alerting and clean reporting in one place.
Repeat-behavior analysis
Repeated clicks, abnormal timing and session frequency get scored as suspicious.
Signal-based detection
Each click is checked against dozens of fake-click signals, not a single rule.
Clean conversion data
Separate fake clicks from genuine visits so your metrics and bidding stay honest.
Click-level evidence
Export IPs, timestamps, user agents and campaign context for every flagged click.
Source exclusions
The IPs and sources behind fake clicks get pushed into exclusion and blocking workflows.
See Didva in action
Real-time monitoring, risk scoring and one-click evidence — in a single dashboard.
What Didva tracks on every paid visit
Each click is scored against dozens of signals, then tied back to the campaign, keyword and conversion it belongs to.
- Campaign, ad group, keyword and landing page
- IP address, ISP/ASN, geo and device
- Browser, user agent and automation fingerprints
- Click timing, repeat clicks and session frequency
- Engagement depth, dwell time and navigation
- Conversions and lead quality
- Risk reason, confidence level and recommended action
What advertisers say
Real feedback from teams protecting their paid traffic with Didva.
Caught a click-farm pattern our previous tool missed and cut wasted spend within the first month.
Setup was a single snippet. The evidence export made our Google Ads refund request painless.
Clear per-IP reasons and a review queue so we are not blocking real customers. Exactly what we needed.
Datacenter and repeat-click detection paid for itself fast. Reporting is clear enough to share with clients.
We manage campaigns across several clients and the dashboard quickly highlighted traffic patterns we would have otherwise missed.
Simple setup, useful alerts, and enough detail to investigate suspicious visitors without involving developers.
The product delivered value quickly. I would like a few more filtering options, but the core detection features work well.
The manual review queue helped us avoid blocking legitimate visitors while still dealing with suspicious traffic.
The IP-level evidence makes client conversations much easier. Instead of assumptions, we can show actual data.
One of the cleaner interfaces we have used in the ad fraud space. Reports are easy to understand.
Within the first week we found a source of repeated clicks that had been consuming budget for months.
Useful notifications, clear reasoning, and very little noise. Most flagged visits deserved attention.
We mainly wanted better visibility into traffic quality. The platform delivered exactly that.
I like that every flag includes supporting details. It builds confidence in the decisions being made.
We tested several tools and this was the easiest one to explain to both clients and team members.
Good balance between automation and transparency. Nothing feels hidden behind a black box.
The repeat-click reports helped us identify unusual traffic spikes during a competitor campaign launch.
Client reporting became much easier once we started including the exported traffic quality reports.
Strong product overall. A few advanced reporting features would be nice, but detection accuracy has been solid.
The value was obvious after the first couple of weeks. We now review suspicious traffic as part of our regular workflow.
Ready to see which clicks are real? Start protecting your paid traffic in minutes.
Start Protecting Your AdsFrequently asked questions
What is a fake click?
A fake click is any paid click that doesn't come from a genuine prospect (generated by bots, click farms, proxies, repeat offenders or accidental activity) that spends budget with no real chance of converting.
How does Didva detect fake clicks?
Didva scores each click across many signals (IP and device, timing, repeat behavior, engagement and conversion outcome) rather than relying on a single rule, so it catches subtle fakes as well as obvious ones.
Can I see why a click was flagged?
Yes. Every flagged click comes with the reasons and a confidence level, plus exportable evidence, so you can review before taking action.
What happens after a fake click is detected?
The source can be excluded from your campaigns and added to blocking workflows, automatically for high-confidence cases and after review for borderline ones.
Does removing fake clicks improve my results?
Keeping fake clicks out of your conversion data gives you a more accurate conversion rate and helps automated bidding optimize toward real buyers.
See how much of your traffic is real
Tell us your site and we'll show you where invalid clicks are draining your budget.
Related solutions
Find the clicks that were never real.
Didva scores every paid click, flags the fakes and keeps them out of your budget and your data.