With millions of active players across the globe, it’s no surprise that user acquisition has become a top priority for mobile game developers. However, with the rise of fraud in user acquisition, it has become increasingly difficult to navigate the mobile gaming industry. In this blog post, we will explore the issue of fraud in user acquisition and provide strategies to avoid fraud and maximize ROAS.
How does fraud happen in mobile gaming?
User acquisition fraud is any fraudulent activity that artificially inflates the number of installs, clicks, or views on a mobile game. Several common types of fraud in user acquisition include fake installs, click spamming, SDK spoofing, and bots and farms.
- Fake installs occur when a user is paid to download and install a mobile game without any intention of playing it.
- Click spamming is when a user clicks on an ad multiple times to inflate the click-through rate artificially.
- SDK spoofing is when fraudsters impersonate legitimate SDKs to steal attribution data.
- Bots and farms are automated programs or groups of people that artificially simulate user behavior to inflate metrics.
The impact of fraud on user acquisition and the gaming industry as a whole is significant. Fraudulent activity can lead to wasted ad spend, reduced engagement, and a negative impact on the user experience. Furthermore, it can harm the reputation of the mobile game and the developer, decreasing user acquisition and revenue.
Beware of these signs!
It is important to recognize the signs of fraudulent activity to avoid fraud in user acquisition. One way to identify fraudulent installs is to look for patterns of behavior that deviate from typical user behavior. For example, if many installs come from the same IP address or device, it may be a sign of fraud.
Multiple installs from the same IP address or device: If you notice a high volume of installs originating from the same IP address or device, it could indicate fraudulent activity. Legitimate users typically have unique IP addresses and use various devices, whereas fraudsters may attempt to generate multiple installations from a single source. Keep an eye out for disproportionate installs coming from a single IP address or device.
Click spamming: Analyzing click-through rates can help identify abnormal spikes that may be signs of click spamming. Observing a sudden and significant increase in clicks within a short period could indicate fraudulent activity. Fraudsters may employ techniques to artificially inflate click numbers, making it seem like there is a high level of user interest when, in reality, the clicks are generated through fraudulent means.
SDK spoofing: Monitoring attribution data can help uncover discrepancies that point to SDK spoofing. You should ook for inconsistencies between the attributed installs or actions and the expected distribution. If the data indicates unrealistic user behavior or if there are discrepancies between the reported data and actual user interactions, it may indicate that the attribution data has been manipulated.
Bot activity and farms: Detecting bot activity and farms involves analyzing user behavior for patterns that deviate from normal user behavior. Signs such as excessive app usage within a short period, consistent patterns of interaction, or similar behavior across multiple user accounts are what you don’t want to see. Bots often exhibit predictable and repetitive actions, lacking the natural variations observed in genuine users.
Also, here’re some metrics to look out for:
Install conversion rate
- Observe the average conversion rates of your competitors or similar brands.
- If CTIT shows hours or days, this might indicate that you are dealing with ad fraud. The expected turnaround time for most ads is seconds or a few minutes.
- If your app has funnel-down events such as sign-up or creating an account, and they are completed before the needed interaction happened, this might indicate fraud.
Here’re Some Best Practices to Avoid UA Fraud
Tips for Verifying Genuine Installs
Analyze IP Addresses and Devices:
- Look for various IP addresses and devices associated with the installs.
- Be cautious if a significant number of installs originate from the same IP address or device, as it may indicate fraudulent activity.
Monitor Install Patterns:
- Examine the timing and frequency of installs to identify any suspicious patterns.
- Large spikes in installations within a short period may indicate fraudulent behavior.
Validate User Engagement:
- Assess the level of user engagement, such as app usage, actions taken, or purchases made.
- Genuine users typically exhibit varied and meaningful engagement, while fraudulent installations may lack real user interactions.
Strategies to Detect and Prevent Click Spamming:
- Track Click-Through Rates (CTRs):
- Regularly monitor CTRs to establish baseline metrics.
- Look for sudden and significant spikes in CTRs, as it may indicate click spamming attempts.
- Set Realistic Expectations:
- Compare CTRs with industry benchmarks and historical data.
- Unusually high CTRs that deviate from expectations should be thoroughly investigated.
- Implement Fraud Detection Tools:
- Utilize specialized fraud detection tools and services to identify and filter out fraudulent clicks.
- These tools often employ advanced algorithms and machine learning techniques to detect patterns of click spamming.
Measures to Counter SDK Spoofing:
- Monitor Attribution Data:
- Regularly analyze attribution data to identify any inconsistencies or discrepancies.
- Look for discrepancies between reported installs or actions and the expected distribution.
- Validate User Behavior:
- Compare the attributed installs or actions with typical user behavior.
- Unrealistic user behavior or unexpected patterns may indicate SDK spoofing attempts.
- Establish Secure Attribution Frameworks:
- Implement secure attribution frameworks that leverage encryption and authentication mechanisms.
- This helps prevent unauthorized modifications or manipulations of attribution data.
Techniques to Identify and Block Bot Activity and Farms:
- Analyze User Behavior:
- Study user engagement patterns to identify behaviors that deviate from normal user activity.
- Look for excessive app usage within a short period, repetitive actions, or similar behavior across multiple user accounts.
- Employ CAPTCHAs and Human Verification:
- Implement CAPTCHAs and other human verification mechanisms during critical touchpoints.
- These measures can help distinguish human users from bots or automated scripts.
- Utilize Machine Learning and AI:
- Leverage machine learning and AI algorithms to detect and classify bot activity.
- Train models to identify bot signatures, anomalous behavior, and patterns associated with bot farms.
Tools and Technologies to Combat User Acquisition Fraud
What are some anti-fraud tools for user acquisition?
To identify and block fraudulent installation attempts, fraud detection software like Adjust, Kochava, or Singular, utilize sophisticated algorithms and machine learning. These tools analyze a wide array of parameters, such as IP addresses, device fingerprints, click patterns, and user behavior, to flag suspicious activity and prevent fraudulent installs.
Distributing analytics platforms like AppsFlyer, Branch, or Adjust can improve user acquisition campaigns. As users click on ads to install apps, they track their journey, helping to verify genuine installs. User acquisition managers can identify discrepancies and anomalies in attribution data with these tools, enabling them to validate attribution data and analyze user engagement.
DoubleVerify, MOAT, and IAS (Integral Ad Science) are a few examples of ad verification tools that play a crucial role in ensuring the authenticity of ad impressions and user interactions. The tools use sophisticated algorithms to detect and remove non-human traffic, such as bots or farms, from ad campaigns. In order to reduce the risk of ad fraud, ad verification tools monitor viewability and click-through rates.
Machine learning and AI in detecting fraud
Check out some case studies of combating ad fraud
AppsFlyer’s fraud prevention solutions helped the global mobile game publisher Genera to detect ad fraud and its source and take action to stop it. The AppsFlyer product Protect 360 detected that over 85% of unrated DeviceIDs installed many apps through different publishers. After more observation, the publisher stopped working with troubled SiteIDs, and boosted ROAS, organic growth and, ultimately revenue.
Adjust’s Fraud Prevention Suite assisted the app albo in their UA efforts and increased their conversion rate by 600%.
What to Do If You Encounter User Acquisition Fraud?
If you suspect fraudulent activity, it is important to take immediate action in order to mitigate the damage. Here are some steps you can take:
Immediate steps to take if you suspect fraudulent activity
- Conduct an audit of your user acquisition campaigns. This will help you identify any fraudulent activity and determine how it impacts your campaigns.
- Block suspicious IP addresses and devices. This will prevent fraudulent activity from continuing and help protect your campaigns from further harm.
- Contact your ad network or platform to report the fraud. They may be able to help you identify the source of the fraud and take action to prevent it from happening again.
Reporting fraud to relevant authorities and platforms is crucial in preventing it from spreading. It is important to report any instances of fraud to the appropriate authorities and platforms. This can help identify and prosecute the individuals or organizations responsible for the fraud.
Legal avenues and protections for user acquisition managers
If you encounter fraud, you may have legal avenues and protections available to you. For example, you may be able to file a lawsuit against the fraudsters or seek damages from ad networks or platforms that facilitated the fraud. Understanding your legal options and seeking appropriate legal advice if necessary is important.
Collaboration Makes Impact
Industry-wide collaboration is crucial
Preventing and combating user acquisition fraud requires collaboration. Having a cooperative relationship among user acquisition managers is beneficial to identifying and preventing fraudulent behavior. Furthermore, collaboration can promote industry-wide efforts to combat fraud and raise awareness of it.
To combat fraud, user acquisition managers must foster open dialogue and learn from each other. It is crucial for user acquisition managers to build a culture of transparency and collaboration in order to identify fraud, prevent it, and stay up-to-date on fraud prevention tools.
It is possible to accomplish this by holding regular meetings or webinars where user acquisition managers can share their insights and experiences. In addition, they can create online communities for exchanging information and discussing best practices.
Mobile gaming is plagued by user acquisition fraud. A user acquisition manager must understand the different types of fraud, recognize the signs of fraudulent activity, and implement best practices to avoid fraud and maximize ROI. A positive user experience and maximum revenue potential can be achieved by following these strategies by mobile game developers.
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Let us know what your thoughts, experiences, or tips to overcome user acquisition fraud!