How Mobile Fraud Is Stealing a Large Portion of Your Ad Spend

Many marketers likely don't even realize this is happening

A burglar running through a small lit window.
It's the quietest ad budget heist.
Mark Airs/Getty Images

Mobile fraudsters are impressively stealing your ad budget, and you likely don’t even know it.

These grifters have evolved their trade faster than prevention capabilities can keep up and have turned ad tech into their unwitting accomplices. Ad buyers are losing this arms race, and the bigger your budget, the bigger a target you are. The potential heist, according to Forrester’s projections: $20 billion of budgets this year alone.

These nefarious groups know the soft spots to exploit in the revenue chains, invent new methods to cloak their activities at scale and understand how to use your individual campaign requirements against you. The 2019 mobile fraudsters are now well-organized companies that flood your data feeds with garbage that looks great, which in turn keeps even advanced buyers incorrectly yearning for more. That’s some remarkable trickery.

Let’s illuminate several critical types of mobile fraud and discuss actionable tactics to protect your budget, data and business. This will equip you with strategic understanding, in plain English, to address the theft and damage that is likely being perpetrated on your advertising programs—right this minute. Pulling back this fraud curtain may reveal some scary realities. However, this article will arm you to begin your battle, stop the theft of your budgets and restore the integrity of your core advertising and consumer data.

Understanding the fight

Your best mechanism to fight mobile fraud starts with knowing and using your own data. Although there are plenty of external, third-party tools built into the different tech platforms you use, their purpose is to broadly defend against ad fraud for every client. You need to solve fraud for your specific company, and that requires a unique strategy and approach altogether.

Further, those same ad-tech prevention tactics are known by the very companies you are fighting against. This keeps the fraudsters smarter and faster. They are essentially using your technology against you.

To clearly illustrate how these frauds are perpetrated and how to address them, Iet’s use a sample campaign designed to drive paid customers of our new app and funded out of the advertising budget on a cost-per-install (CPI) basis. (Comparable circumstances affect all types of mobile campaigns.) To become a new customer, each needs to complete three key stages: installation, registration and purchase.

On the other side of the battle are the well-organized fraudsters. These companies have legitimate apps which serve our ads and are used by real, potentially valuable users. However, they also generate activity with subsequent revenue for themselves via bots and warehouses of staff who click, install and act inside our app. Their sophisticated tactics enable them to target our campaign specifically and exploit ad exchanges to steal our ad budgets at scale—all in plain sight.

A chart

Addressing table stakes

Our starting point is to discover and acknowledge “empty installs” and “fake registered users.” Empty installs are when fraudsters click and install our app, but with no further activity, and gets the CPI revenue in the process. This is the easiest fraud to address.

The marketing team just needs to get granular with the mobile measurement platform (MMP) campaign tracking data. With a little know-how, the marketing team can identify the partners, apps and sites that have been delivering large and small amounts of wasted budget. We can then cut zero post-install activity sources. But these fraudsters remain impressively clever, which necessitates a deep examination of the data based on understanding their nefarious strategies.

The next level of fraud has fake registered users, who create false accounts which pollute the data. These need to set off alarms. This scenario indicates that the fraudsters know and are using our marketing expectations against us. To identify this, the team needs to scrutinize its data for:

Below-target expectations

Symptom: few post-install events to prevent zero-activity warnings from being tripped

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