#mobileadfrauddetection

Advertising platforms optimize for signals—not intent.  

In mobile marketing, the most important signal is the install. More installs usually mean a campaign is working. Platforms see this, assume success, and push more budget in the same direction.  

This is where install fraud begins.  

Fake installs are easier and cheaper to generate than real users. Fraudsters use bots, device farms, or incentivized tactics to create large volumes of installs that look genuine on the surface. Since the numbers look good, platforms assume the campaign is performing well. Budgets increase. The same sources get more spend.

You launch a referral program with the intention to acquire new users to your app. When analysing your campaign progress, you see that your referral champion is a single user who somehow ‘invited 200 people overnight’.   

You feel confident to spend more on these campaigns.

On your dashboard there are 200 people, but upon deeper analysis you see that only a few retain as users. That’s a sign that something is not right. It’s not the usual invalid traffic, but a more advanced and difficult version of ad fraud. Referral and coupon fraud are advanced types of mobile ad fraud which impacts the action driven KPI’s and can skew your data

Every performance marketer running a user acquisition campaign has the same goal – to increase the number of app installs and lower CPI. But often, the post-install metrics don’t match what campaign dashboards show.

Despite high marketing spends, performance looks inflated and unpredictable. The numbers eventually stop making sense due to low engagement and poor retention. And this usually means one thing: you’re acquiring installs, but not real users.

This gap between installs and engagement clearly indicates mobile ad fraud – deceptive tactics used to manipulate mobile advertising campaigns and post-install metrics. A threat that eats into budgets even before marketers notice.

That is why, while chasing installs, it is also important for marketers to ensure those installs are not the work of bots, click farms, or devices mimicking real behaviour, but real active users