Mobile ad fraud is an ever-growing challenge for businesses and advertisers worldwide. According to the Mobile Ad Fraud Report (2019), Android mobile traffic saw up to 31% fraudulent activity in Q2 2019, and iOS had 25%. This surge in fraudulent traffic results in wasted ad spend and lower traffic quality, making it imperative for businesses to implement effective fraud protection measures. As advertisers continue to focus on mobile marketing, it’s essential to stay ahead of these fraudsters by leveraging the right tools and strategies.
In this guide, we’ll take you through the common types of fraud, key metrics to monitor, and the steps you can take to protect your advertising budgets while ensuring the traffic you’re paying for is legitimate.
Understanding the different types of mobile ad fraud patterns
Before diving into how to detect fraudulent traffic, it’s important to know the different methods fraudsters use to deceive businesses. These types of fraud are on the rise, making it even more critical for businesses to have a deep understanding of them. The evolving nature of mobile ad fraud means that fraudsters are constantly refining their techniques, finding new ways to exploit weaknesses in ad networks and tracking systems. For instance, the use of advanced technology like automated bots and device farms allows fraudsters to simulate legitimate traffic at scale, making it more difficult for traditional detection methods to keep up.
As these methods become more sophisticated, businesses must be proactive in staying informed about the latest fraud tactics. This requires not only technical expertise but also an awareness of how these fraud schemes impact advertising budgets and campaign performance metrics. In addition, publishers and app developers must collaborate to enhance fraud prevention efforts, ensuring that their ad networks and platforms are equipped to handle the growing threat. By understanding these fraud patterns, businesses can better prepare themselves to identify and combat fraud before it leads to financial losses and wasted resources.
Click Spamming or Click fraud
Click Spamming occurs when fraudulent clicks are generated by applications running in the background of users’ devices. The fraudster makes it appear that a legitimate user clicked on an ad, but in reality, no user interaction actually took place. These fake clicks can be attributed to organic installs, thus skewing the data and causing advertisers to lose money on wasted ad spend.
Click Injection
Click Injection is a more advanced form of fraud. In this case, fraudsters use a malicious app that detects when a mobile app is installed and immediately triggers a click just before the installation finishes. As a result, this fraudulent click is falsely recorded as an organic install, and the fraudster gets paid. This method results in high fraudulent activity and undermines the integrity of mobile campaigns.
Device Farms
Device farms involve large numbers of real devices used to simulate installs. Fraudsters use hundreds or even thousands of mobile devices, all installed with the same app. These devices are used to generate fake installs, often with the help of VPNs to mask their real locations. This leads to non-human traffic and distorted metrics, making it more difficult for advertisers to identify legitimate installs. Device farms are a significant threat to the quality of traffic, as they generate a lot of fake traffic.
How to detect and block fraudulent traffic
Now that we understand the types of fraud, let’s talk about how to effectively detect and block it. The key to combating fraud lies in analyzing the right metrics and using advanced fraud detection tools that can identify suspicious activity in real-time.
Click to Install Time Interval (CTIT)
Monitoring the Click to Install Time Interval (CTIT) is one of the most effective ways to detect fraud. Normally, it should take around 30 seconds for a user to click on an ad and then install the app. If the CTIT is too short, this may indicate click injection, where fraudulent apps trigger clicks before the app installation completes. Conversely, if the CTIT is unusually long, it may suggest click spamming, where fraudsters use hidden techniques to simulate clicks.
If the time between a click and installation is under 5 seconds, it’s likely fraud, as the user didn’t have time to interact with the app. This could indicate click injection, where a fraudulent app triggers a click. To prevent this, set a minimum CTIT threshold based on typical user behavior—if the average time is 15-30 seconds, flag any installation under 10 seconds for review. This helps you block fraudulent traffic early and protect your campaign.
Geo-Location Tracking
Fraudsters often use VPNs to mask their true locations and make fraudulent installs appear legitimate. By analyzing the geo-location of clicks, installations, and in-app events, you can spot discrepancies that suggest fraudulent activity. For example, a click originating from one country but leading to an installation in another could be a sign of fraud.
Comparing geo-location data between clicks and in-app events is an effective way to expose fake traffic generated by device farms or bots. These mismatches can be an indicator that fraudulent traffic is inflating your installation numbers, and by tracking them carefully, you can ensure that only legitimate installs are counted.
Retention and Conversion Metrics
One of the most significant indicators of fraudulent traffic is low retention rates. If users quickly uninstall an app or fail to engage with it, it could mean the traffic was not real. Fraudulent installs, especially from device farms, tend to show very low retention rates as the apps are quickly removed.
To assess the quality of your traffic, monitor the conversion from installations to in-app events (e.g., registrations, purchases). If these conversions are unusually low, it may indicate that the traffic is not genuine.
Conversion from Click to Installation
Another essential metric is the conversion from clicks to installations. A too-high conversion rate may suggest that users are installing the app to receive rewards, such as virtual currency, rather than due to genuine interest. On the other hand, a too-low conversion rate may point to click spamming.
To protect your campaign, it’s essential to set hard KPIs for conversion rates, which will help you flag suspicious publishers. If a publisher’s conversion rate exceeds or falls below the established threshold, you can take appropriate action, ensuring that only legitimate traffic is included in your campaign.
The importance of real-time data analysis
With the rise of fraud, it’s more important than ever to monitor data in real-time. Fraudulent traffic can significantly affect your advertising budgets, causing you to pay for non-human traffic. Using machine learning and automated fraud detection systems can help you detect and block fraudulent activity instantly.
These tools analyze the key metrics we discussed, such as geo-location, conversion rates, and click injection, in real-time to give you a clearer picture of the quality of your traffic. With these fraud detection tools, businesses can identify fraudulent patterns early and take action before they waste any more ad spend.”
Protecting your advertising budgets
Every business needs to ensure that their advertising budgets are well protected from fraudsters, especially considering the significant portion of fraudulent traffic that can affect online campaigns. By investing in robust fraud prevention systems that focus on real-time data analysis, businesses can make sure that only high-quality traffic is counted toward their campaign goals.
By using comprehensive fraud detection tools, you can monitor key fraud indicators in your campaigns, such as automated bots, click spamming, and geo-location discrepancies. These tools help block fraudulent traffic and fake clicks, protecting your ad spend and ensuring that your focus stays on achieving genuine, measurable results. Whether you’re promoting a mobile app or managing online advertisements, taking steps to stop fraud ensures that your budget is spent effectively, even with different configurations in mobile applications.
Effective tools in ad campaigns
Effective fraud prevention tools can easily integrate with your existing ad campaigns, allowing you to:
- Set custom thresholds for click spamming and click injection
- Analyze geo-location discrepancies and retention rates in real-time
- Identify fraudulent patterns and block non-human traffic before it impacts your results
- Use machine learning to continuously improve fraud detection accuracy
By utilizing advanced fraud detection tools, you can protect your ad spend from fraudulent activity and ensure that your budget is allocated effectively to drive genuine results.
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Stay ahead of ad fraud and invalid traffic
Fighting mobile ad fraud requires vigilance and the right tools to identify suspicious activity. By focusing on key metrics such as CTIT, conversion rates, and geo-location tracking, you can protect your campaigns from fraud. Implementing a robust fraud detection system allows you to track fraudulent activity in real-time, ensuring you only pay for real users and high-quality traffic.
I hope this helps you stay ahead of fraud and protect your ad spend. In today’s digital world, staying ahead of fraud is no longer optional—it’s essential for the success of your mobile app campaigns.
[1] Interceptd, Q2 2019 Mobile Ad Fraud Report, https://interceptd.com/wp-content/uploads/2019/12/interceptd-q2-2019-mobile-ad-fraud-report.pdf
