AdTech industry is vast and ever-changing. It might be hard to keep up with all the new slang, but worry not - our glossary will keep you properly updated!
Unnecessarily serving mobile ads to customers that are close to conversion. As a result, credit for conversions and app installs is being misattributed. Here, the perpetrators benefit both from app-install income, and increased mobile ad spend. This typical form of fraud impacts a considerable portion of mobile ad pays. As a result, credit for conversions and app installs is being misattributed. Here, the perpetrators benefit both from app-install income, and increased mobile ad spend. This is a widespread form of mobile ad fraud, and it wastes a large amount of money.
The "last-click-attribution" approach often used by attribution providers is manipulated by attribution fraud, which tricks attribution platforms into associating an organic install or an install from another source with the fraudster. Click spamming exploits the last touch attribution model to "steal the credit" for an installation. With this methodology, the most recent Universal Affiliate (UA) partner who was previously associated with a click on an advertisement preceding the installation will be linked to it, provided that the window is still open. This is how many marketers attribute installs today. To summarize, the last ad click before the install will be credited with the install. Advertising impressions are when Mobile Attribution Manipulation takes place.
In-app banner ads or website pixel "ads" are both acceptable. As soon as a user sees an ad, fraudsters start triggering a series of clicks (20 or more), as if many ads were being displayed to the same user and all of them were clicked on. It's a technique known as ad stacking. A new window for the app store will open as a result of this following step. There's no install yet, but all of these clicks are noted for future attribution purposes because the user didn't click on the ad initially.
Mobile Attribution Manipulation is based on assumptions and aims clicks at apps that are likely to be installed organically by large groups of users (apps that have a buzz around them, new services, apps that new devices tend to install, and more). The result is that consumers install the software after the ad is 'clicked,' and the spammer is given credit for the installation. It's only a guess, but consider the likelihood of getting 20 to 30 separate clicks (for popular apps) from a single impression. You'll inevitably 'win' some installs.
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