Are you proactively analyzing the ad traffic of your campaigns?
Is it really coming from genuine users or just being generated by bots?
Yes, a significant portion of traffic that makes your ad campaigns seem successful could be invalid traffic. According to mFilterIt’s analysis featured in FICCI Report 2025, invalid traffic contributes to as much as 30–50% of activity across digital channels, directly distorting performance metrics and draining ad budgets.
This means the performance you see on dashboards may not always reflect real user intent. Instead, it could be influenced by automated systems, proxies, or manipulated interactions that inflate impressions, clicks, and even conversions.
In this blog, we break down what invalid traffic really is, why it’s increasing, differences between general invalid traffic and sophisticated invalid traffic, and how you can identify and mitigate its impact to ensure your campaigns deliver genuine results.
What is Invalid Traffic? Why is it Increasing Rapidly?
Invalid traffic simply means ad activity that doesn’t come from real users but still shows up as genuine impressions, clicks, or visits. This happens when bots or automated systems interact with ads, making it look like people are engaging when they actually aren’t.
Over time, this traffic has become more advanced and harder to spot. Bots now easily mimic real user behaviour, such as browsing pages, scrolling, or clicking on ads. Moreover, developments in technology, AI usage, and advertising infrastructure also contribute to this. Here’s how:
AI is making bots smarter
Earlier, bots were easy to detect because they behaved like machines. Today, AI-powered bots can scroll, pause, click, and even mimic browsing patterns. Some can simulate entire user journeys, making fake engagement look real in analytics tools.
The ad ecosystem has become more complex
Modern advertising runs through multiple layers and channels, DSPs, SSPs, ad exchanges, networks, and resellers. This fragmentation creates blind spots, making it easier for low-quality or fraudulent traffic to enter without being noticed.
Cheap infrastructure fuels large-scale ad fraud
Server farms allow fraudsters to generate massive volumes of ad traffic at very low cost. What once required physical devices can now be scaled instantly using virtual environments.
Limited transparency and visibility
Limited transparency and visibility across the digital ecosystem make it harder for advertisers to verify traffic quality. With restricted access to detailed user-level data, identifying whether engagement is coming from real users or sophisticated invalid traffic becomes more challenging.
As long as advertisers pay based on clicks or impressions, there’s always a chance for misuse. Fraudsters take advantage of this by generating invalid clicks or views to earn money, especially when proper checks are not in place.
Therefore, detecting invalid traffic has become more important than ever. Invalid traffic is generally classified into two main types: General Invalid Traffic (GIVT) and Sophisticated Invalid Traffic (SIVT).
Two Major Types of Invalid Traffic
Invalid traffic is broadly classified into two categories based on how complex the fraud technique is.
What is General Invalid Traffic (GIVT)?
It refers to non‑human or automated interactions that inflate ad metrics, caused by easily identifiable bots, spiders, or crawlers. These bots typically do not attempt to mimic real human behavior. They’re not malicious in intent but can distort campaign reporting and waste ad spend due to their automated nature.
Because the patterns are predictable, platforms and verification tools can often identify and block this traffic using ad fraud detection techniques. Here’s what we observed in one of the campaigns .
VPN and proxy traffic contributed 12.4% of total activity, indicating that a significant portion of traffic was not genuinely coming from real users.
Several visits appeared to come from genuine mobile users but traced back to VPN and proxy networks, that were being used to hide the real user’s location. A deeper analysis showed that these IP addresses were linked to data center hosting providers (DCH) instead of real user networks.
What is Sophisticated Invalid Traffic (SIVT)?
Sophisticated Invalid Traffic (SIVT) refers to advanced forms of fraudulent or non-genuine traffic that are designed to look like real user activity. Unlike basic invalid traffic, these methods use automation, scripts, or manipulated devices to mimic real behavior, making them harder to detect with simple filters.
Here are some sophisticated invalid traffic techniques we have observed in various campaign analysis:
Sample Observation 1:
In this case, the sophisticated invalid traffic technique that is being used is pop-under activity. It occurs when a website opens in the background instead of the active browser tab, meaning the user does not actually see or interact with the page.
This is what we observed: the page loaded behind the main window and showed no real user interaction, indicating artificially generated visits. This type of activity is used to inflate traffic numbers without genuine engagement, and here, pop-under traffic contributed about 6.1% of the total traffic.
Sample Observation 2:
This shows a case of device spoofing, where traffic pretends to come from a real mobile device. Normally, smartphones support touch actions like tapping, scrolling, or pinch-zooming. However, in the above data, some devices marked as mobile showed “Not Standard” touch support, meaning these normal mobile features were missing.
This suggests that the devices were not real smartphones but simulated environments or automated systems pretending to be mobile users. In this analysis, device spoofing made up about 2.7% of the traffic, indicating automated activity trying to appear like real user interactions.
Sample Observation 3:
Server farm-driven activity contributed 3.2% of total traffic, highlighting the presence of sophisticated, non-human interactions.
In this case, traffic appeared to come from mobile devices across different sources. We noticed very high hardware concurrency values (192 and 96) from devices shown as mobile. Hardware concurrency simply means how many tasks a device can handle at the same time. Normal mobile phones can only run a limited number of tasks, so numbers this high are unusual for real users.
This suggests that the traffic is likely coming from multiple channels, like bot farms, proxy-based execution, and automated browsers instead of real mobile devices. These systems are often used to run automated bots that imitate user activity, which is a common sign of sophisticated invalid traffic (SIVT).
Sample Observation 4:
This sample shows a repeat user pattern, where a single device generated 69 repeated visits from the same IP address using the same system (Windows 10 and Chrome). These visits occurred within a very short time, often just minutes apart, which is unusual for a real user.
The graph also shows sharp spikes in activity instead of a normal browsing pattern. This clearly indicates that the repeat activity which is observed is not genuine and is likely driven by automated or bot traffic (SIVT).
How mFilterIt Helps Advertisers Identify & Prevent Invalid Traffic
While the bots have become more sophisticated than ever, here’s how mFilterIt’s ad fraud solution helps marketers identify, detect, and prevent invalid traffic to ensure their performance campaigns generate impactful results.
Detects Invalid Traffic in Real Time
Spots suspicious clicks, impressions, visits, and installs as campaigns run, so fraud can be identified before it wastes more spend.
Monitors Traffic Sources
Tracks publishers, placements, referral paths, and channel sources to identify where low-quality or suspicious traffic is coming from.
Separates Genuine Traffic from Fraud
Uses device signals, IP intelligence, and behavioral analysis to distinguish real users from bots, proxies, and manipulated environments.
Blocks GIVT and SIVT
Identifies both general invalid traffic and sophisticated invalid traffic, including bots, device spoofing, click injection, cookie stuffing, domain spoofing, and fake attribution.
Improves Campaign Quality
Blacklists unsafe placements, low-quality publishers, and fraudulent sources to improve traffic quality and campaign efficiency.
Protects Full-Funnel Performance
Validates traffic across impressions, clicks, visits, leads, and installs so performance is measured on genuine user activity, not artificial engagement.
Helps Make Smarter Media Decisions
Gives marketing teams clearer visibility into traffic sources and campaign quality, helping them optimize budgets, improve ROI, and reduce wastage.
Conclusion
Invalid traffic is a growing challenge that can quietly drain ad budgets and distort campaign performance. As fraud tactics become more advanced, advertisers need to actively monitor traffic quality and detect non-genuine activity early, which is a call for advanced ad fraud solution in today’s market.
Understanding GIVT and SIVT is the first step toward protecting your campaigns and ensuring your ads reach real users with genuine intent.
Want to know if your campaign traffic is genuine?
Connect with us to gain deeper visibility.
FAQs
What does invalid traffic mean?
Invalid Traffic (IVT) refers to any clicks, impressions, or visits that do not come from real users. This usually happens when bots, automated tools, or manipulated systems interact with ads. Even though this activity looks like normal engagement, it does not represent genuine user interest.
Why is invalid traffic a problem for advertisers?
Invalid traffic can waste a significant portion of advertising budgets by generating fake clicks and impressions. It also gives misleading campaign data, making it difficult for advertisers to understand what is actually working and where they should invest their budget.
What is the difference between GIVT and SIVT?
GIVT (General Invalid Traffic) includes basic forms of invalid traffic, such as known bots, crawlers, or traffic from data centers and proxies. It is usually easier to detect.
SIVT (Sophisticated Invalid Traffic), on the other hand, uses advanced methods to mimic real users, such as automated browsing behavior or device spoofing, making it much harder to identify.
What are common signs of invalid traffic?
Some common signs include unusually high clicks with low conversions, repeated visits from the same device, traffic from unknown locations, or very short session times. These patterns often indicate non-genuine activity.
