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DataVisor Reports on Ways to Tackle UA Fraud

App Annie

When new installs seem too good to be true, it could be user acquisition fraud. DataVisor explains how to fight back.

Imagine thousands of installs from residential networks all over the United States, and all of the new users actively used the mobile gaming app for several days after downloading. Seems legitimate and great for business, right?

You would think so, except all subsequent user activity came from one IP subnet in Southeast Asia. The fraudulent ad channel was still able to charge user acquisition fees, however, since the fake users seemed legitimate at the time.

This is a real case of fraud we observed at DataVisor, and it is a real threat to user acquisition.

The mobile app landscape is a battlefield and new apps are fighting everyday to make it to the top of the charts. (For an overview of the entire user acquisition (UA) lifecycle, download App Annie’s UA Playbook.) That’s why we’re seeing more cases of UA, or install, fraud.

The Evolution of Install Fraud

In the US alone, mobile app install ad spending is projected to grow to $9 billion by 2018 — a 438% increase in only four years. Install ad campaigns have become a necessity for success, and app marketers are willing to pay significantly more per install than for clicks or impressions. How much more? The average payoff for an install can be 430x more than an impression.

Installs and active users are more desirable measurements for ad success because models based on impressions or clicks are now easily manipulated by criminals spoofing traffic. By only paying when an app is installed or when a newly registered user launches the app multiple times, it becomes much more difficult to mimic the actions of a real user. Difficult, but not impossible. Because fraudsters have figured out how to do it.

Four Ways to Combat Install Fraud

So what can you do to protect yourself against fraud? Follow these four best practices:

  1. Focus on the right metrics.
    When it comes to UA metrics, focus on user retention and other post-install activities that are not as easily faked. Measuring activity that a normal user would participate in, beyond installing and opening the app, is helpful. Look for metrics such as day-one and day-seven retention to help weed out fake installs.
  2. Understand where installs are coming from.
    Affiliate networks can be viewed as a bit of a black box — it can be difficult to see inside. Do your homework and understand the inventory of these affiliate networks. For example, it may be good to avoid affiliate networks where your traffic may be rebrokered, or where the network works through third parties without your permission. Working with reputable affiliates and partners gives you more control and a better chance of acquiring real users.
  3. Be skeptical of numbers that seem too positive.
    As in most things in life, things that seem too good to be true usually are. It’s your job to dig in and figure out what happened. It can be hard to admit that a spike in users was fraudulent, but it’s better to clean things up as they happen.
  4. Don’t go it alone.
    Fraudsters aren’t working alone so you shouldn’t either. These are highly organized, and often well-funded, attack campaigns. Seek out technology partners who can help you distinguish between legitimate and fraudulent traffic and users.

More New Users, Less Fraud

While it may be true that there is a lot of money being spent, and stolen, in the app industry by fraudsters, efforts to detect them are continuing to evolve. The best way to beat them? Stay one step ahead.

To discover new ways to boost your user acquisition efforts, download App Annie’s UA Playbook.

 

datavisor-team-photos-julian-wong

Julian Wong, architect, DataVisor

Julian is a fraud and security detection industry veteran. As Head of Trust & Safety at Indiegogo and Etsy, and Risk Management leader at Upwork, he developed scalable systems and teams for mitigating fraud and risks. Prior to that, Julian led Google’s engineering team responsible for building algorithms to prevent fraud on its ad platform. Julian holds a Bachelor’s Degree in Engineering from the University of California, Berkeley and an MBA from NYU Stern School of Business.

December 1, 2016

Mobile App User Acquisition

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