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How Adjust is staying ahead of mobile ad fraud in 2023

Ad fraud is a growing concern for mobile advertisers and marketers. As technology continues to evolve, so do the methods of ad fraud. In 2022, ad fraud cost advertisers over $80 billion globally, which is expected to surpass $100 billion by the end of 2023. Given the economic downturn and potential of an impending global recession, it is more crucial than ever to take proactive measures to safeguard your marketing budget and ensure that every dollar is wisely spent.

Collaborating with a mobile measurement partner (MMP) such as Adjust is one way to combat ad fraud. Even without the Fraud Prevention Suite (FPS), clients can prevent fraudulent activities with Adjust. We offer a variety of tools that can help detect and reject fraudulent installs, ensuring that your data sets remain clean and accurate for reliable analysis, and they’re available to all clients automatically. In this article, we share best practices for optimizing campaigns affected by click spam using Adjust's analytics solutions.

What is click spam?

Click spam occurs when fraudsters generate fake clicks on behalf of a user, without their knowledge or consent, to poach and steal attribution. When click spam is left unchecked and continues to occur within a campaign, it can lead to the misallocation of marketing budgets. This is because the campaign's budget will be reinvested into fraudulent sources that appear to be delivering positive results. Failure to act against click spam can also hamper your ability to monitor and optimize affected campaigns efficiently. That's why taking preventive measures against click spam is vital to guarantee that your campaigns remain effective and scalable.

How Adjust protects your data

Click spamming leads to skewed data and wasted resources. To combat this issue, Adjust has developed a range of powerful tools and techniques that all clients can automatically utilize. Our advanced reporting and analytics dashboard provides real-time monitoring of your campaigns, allowing you to quickly identify suspicious activity and take corrective action as needed.

With Adjust's newly developed campaign blocking feature from March 2023, you can easily detect and block campaigns frequently associated with fraudulent activity based on click volume and conversion rate. Click spamming campaigns generate large volumes of fake clicks within a short period, often within a few hours. This can damage your data before our FPS kick in and affect your key performance indicators (KPIs). Adjust has implemented more aggressive measures to stop spamming traffic as soon as it is detected. This prevents fraudulent activity from distorting your data while maintaining existing engagements and attribution associated with the blocked campaign. To fight click spamming, we strongly suggest monitoring your traffic closely and implementing the suggestions below in collaboration with Adjust.

How to improve campaigns affected by click spam?

You can improve affected campaigns with the following best practices:

Optimize campaign structures and Tracker Limit

Automatically creating granular levels in the campaign structure (campaign/ad group/creative) and filling them with networks' corresponding macros via Adjust Tracking URLs may seem like a time-saving solution. However, this kind of structure does not allow for true insight into traffic sources and should be avoided. Fragmented setups like these may affect the functionality of our fraud filters.

To tackle this challenge, you can collaborate with affected network partners to establish a 'Tracker Limit.' This limit is added to the Adjust tracking URL and can be customized for each tracker to detect any excessive creation of trackers. Once the limit is surpassed, all traffic will be automatically credited to an "Unknown" tracker. This will serve as a warning to investigate particular sources during ongoing fraud prevention monitoring.

Conversations to have with networks

Gathering as much evidence as possible before addressing suspected fraudulent behavior with networks is crucial. Use concrete examples to start an open-ended discussion about abnormal traffic patterns. Developing automated strategies to remove publishers who continue to provide suspicious traffic is also imperative. To begin a dialogue with networks about click spam, you can use the following indicators:

  • Extremely low conversion rates
  • The volume of clicks exceeding the target market's population
  • A large number of non-converting clicks outside the targeted region
  • Excessive and even daily tracker creation
  • Sub-sources generating almost identical numbers of non-converting clicks
  • High reattribution rates on campaigns that are strictly user acquisition (UA) campaigns

Bonus: How Adjust’s FPS prevents click spam

Distribution Modeling is a powerful tool in Adjust's Fraud Prevention Suite. It helps eliminate click spam and ensures accurate attribution of installs. By using the hyper-engagement and distribution-outlier methods, Adjust identifies and rejects fraudulent clicks. This makes it easier for advertisers to reach their target audience and measure the effectiveness of their campaigns.

The first method, hyper-engagement, eliminates high-frequency clicks that occur too frequently or have too many duplicates. Fraudsters often send clicks on behalf of users in recurring intervals to produce a "last click" close to the install. After an install occurs, Adjust examines all eligible clicks within the appropriate attribution window. When we notice high-frequency click patterns, we exclude them from being considered for attribution. This ensures the install is correctly attributed to the next legitimate click as organic traffic and helps eliminate click spam.

The second method, distribution outlier, is a real-time filtering method that rejects attributions based on their click-to-install-time distribution. Adjust developed this method by reviewing statistical data and analyzing legitimate and fraudulent activity. This research showed that over 85% of installs from legitimate traffic occur within the first hour after the ad click. This strong correlation between ad click time and install time for legitimate traffic is used to identify fraudulent activity. Click spam poaches organic users or steals attribution from legitimate sources, resulting in a click-to-install-time (CTIT) distribution spread out across the entire attribution window. That’s why Adjust prioritizes engagements that demonstrate strong user intent. We reject attribution to clicks if most conversions occur 60 minutes or more after the click time. Adjust reports these as distribution outliers, and the installs are attributed to the next eligible tracked source or as organic traffic.

But that's not all. If you notice trackers from inactive or paused campaigns generating significant traffic, you can add them to a blocklist to halt campaign measurement. And while any current engagements and attributions associated with the tracker will remain the same, no further tracking will occur. You can also choose to hide the tracker from the dashboard. It's important to remember, however, that blocking live trackers is not a substitute for fraud prevention filtering and may only be a temporary solution. That's why it's crucial to ensure your partners understand your expectations when addressing click spam indicators and establishing a specific and transparent campaign structure. By combining Adjust's proactive measures with your vigilance, you can successfully combat click spamming and ensure your data is accurate and reliable.

At Adjust, we're dedicated to fighting ad fraud. Check out our Guide to mobile ad fraud to learn more about how we're continuing to offer clients next-generation solutions. And if you're ready for a mobile analytics suite that's got your back against fraud, get in touch with us!

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