The digital world is evolving rapidly, and marketers are moving from traditional platforms to digital platforms. But in this growing digital ecosystem, someone is hiding behind the screens to disrupt your growth.
Behind all the pros of digital advertising, a manipulated truth is that marketers are unaware of who is coming to see their ad campaigns.
To throw light on this, ad fraud detection and prevention solution providers have come into the limelight to validate how much invalid traffic is coming to the ad campaigns.
However, just when the marketers were ready to combat ad fraud, cybercriminals expanded their fraud zone with sophisticated bots. Unlike the general bots, the sophisticated bots can replicate human behavior and hide easily behind the cloak of genuine traffic resulting in manipulated data. This again makes the marketer’s ad campaigns vulnerable to ad fraud.
What is the solution?
Advanced Problems Need Advanced Solutions
Once a sophisticated bot penetrates your digital ad campaign, it will not just impact one KPI but also manipulate your entire sales funnel and manipulate the data. For example, if you’re running an impressions campaign then first it will inflate the number of impressions with bot traffic. And once that is done, they will impact your hard KPIs like lead, conversion, or install.
The result is that you not only waste your ad spend on invalid traffic but also open the gateway to your brand assets for the sophisticated bot army to attack and destroy.
Thus, it is important to get a full-funnel ad fraud solution instead of a solution that covers just one KPI.
Know in detail about the different types of sophisticated bots that are hard to detect on the web and app. And for the advanced solution, stick with us till the end of this blog.
Sophisticated Web Fraud Techniques That Are Hard to Detect
To improve the CTR of the site, the fraudsters open the advertiser’s landing page to a zero-sized pixel. However, the end-user is unaware of this and when they visit the website it is registered as a click in google ads platform. The advertiser ends up paying for these clicks/visits which were not even seen by the user.
Example of Page View Fraud
In the above case, the user didn’t click on the advertisement, but a click has been registered. As the window size is imperceptible for the user, they are unaware of this case. Generally, it is difficult to detect these anomalies without the help of advanced data analytics capabilities.
Cookie stuffing is organic theft where a website drops one or more third-party cookies onto a user’s web browser. An Iframe of ‘0x0’ pixel is used to dropping a cookie to hijack the organic user. These malicious cookies thus incorrectly attribute the organic traffic to the fraudulent affiliate.
In the above example, we have incorporated a mFilterIt pixel which drops a randomly generated cookie whenever a user visits the advertiser’s website for the first time. Upon the return of that user, the same cookie value indicates the return of the same user. We also observed that despite faking or rotating the IP, the bot device is returning the same cookie within a gap of a few minutes.
Fake users or Bot emulated users usually don’t have any mouse movement or touch interactions. They are also programmed in a way where they don’t react to the advertiser’s landing page. In this case, where there is no user interaction, we use the capabilities of Machine learning algorithms combined with captured values like configurations, plugins, device settings, canvas fingerprinting, etc.
This helps to analyze the bot patterns and cases where the bot clicks are happening at a high probability.
With the help of AI, ML, and data science, we detected approximately 32k such cases just in the pilot phase.
Sophisticated App Fraud Techniques That Are Hard to Detect
Click spamming starts when a user downloads an infected app on their device – or visits an infected mobile website. These infected apps are usually downloaded outside the walled gardens of the Play Store and IOS app store.
The infected app has built-in code which is programmed to create clicks on ads or allow external devices to click within the app. The app works normally on the user’s device, except for the tiny code running click-spam activities in the background. This fraud technique generates clicks from the user’s device without their knowledge. And the advertisers are under an impression that the clicks are generated by real users.
Example of Click Spam
In this case, clicks and installs are high whereas the conversion rate is as low as 0.01%. This is a clear case of click spamming. These clicks were generated in a time period of 9 days from Thailand. Surprisingly, the total clicks are equivalent to the population of the country. This kind of CTIT curve is often overlooked by the attribution platforms due to the clicks being refreshed in the background. At mFilterIt, we track the click patterns in case of click generating from the same device ID.
Event spoofing is one of the advanced fraud techniques used by fraudsters to manipulate the install data of advertisers. In this case, the fraudsters programmed bots that can fire fake clicks in the background to capture the events. This eventually leads to an event being spoofed and attributed without a legitimate install.
This results in the advertiser believing that a legitimate install happened. However, in reality, no event has occurred. The events like bookings, purchases, signup, registration, etc. are required to be analyzed thoroughly to identify in-app fraud.
Example of Event Spoofing
In this case, the CTIT is distributed within a few minutes, which is unusual. The normal traffic pattern is spread over as the conversion time is usually not in the control of the publisher.
mFilterIt’s Full-Funnel Model – Our Advanced Solution
How We Protected a Global Pharma Player Across the Funnel
A premium pharma company noticed that their impressions were high, but the number of clicks was low. To curb the further wastage of ad spends, they partnered with us to attract cleaner traffic with the help of our Ad Traffic Validation Suite. With the help of our AI, ML, and data science capabilities we were able to detect 24% fraud in total impressions.
However, we further found 51% fraud on clicks. This happened due to some sophisticated bots which seeped through the fraud detection process at the impression level and reached the click stage.
Due to the down-the-funnel fraud approach in our fraud detection, we were able to bring down the ad fraud rate which further improved the impression quality and CTR.
Benefits of a mFilterIt Full-Funnel Ad Fraud Detection Model
- Helps to get a detailed summary of ad fraud
- Helps to evaluate every data set for taking better decisions
- Helps to map quality publishers across the funnel
- Helps to prioritize the audience that will convert
- Helps to detect sophisticated bots in advertising campaigns
Whether you’re running search campaigns or in-app campaigns, fraudsters are waiting for you to take a backseat and steal your money. So, in this digital era where bot traffic has covered more than a quarter of the internet traffic, you need a solution that can protect your ad campaigns from not just general bots but sophisticated bots which are known to imitate human behavior without any extra effort.
In this scenario, full-funnel coverage will protect your ad campaigns at all levels of a customer journey and help you ensure the result is – Fraud Free Traffic.
To know more about how we can protect your brand from sophisticated bots with our full-funnel approach, get in touch with our experts today!