Distribution modeling
Adjust’s distribution modeling protects you against click spam. We calculate the statistical likelihood of each install and reattribution being the result of click spamming and flag any that don’t meet our standards. Our analysis ensures that you are aware of illegitimate installs and reattributions, so you can effectively plan and execute your marketing campaigns.

Activate distribution modeling

If you want to enable Adjust’s distribution modeling, you will need to sign up for our Fraud Prevention Suite. Speak to your AM or contact support@adjust.com for more information.

Instructions

In the Adjust dashboard
  1. Navigate to your app and select your app options caret (^)
  2. Select All Settings > Fraud Prevention
  3. Slide the DISTRIBUTION MODELING toggle to ON

The LEVEL option allows you to set a much stricter distribution modeling threshold. Only change this if you are running a campaign where you expect almost immediate click-to-install times. This option should only be changed if you are intimately familiar with distribution modeling. If you are unsure, leave it on Standard.

View your distribution modeling statistics

Instructions

In the Adjust dashboard
  1. Navigate to your app and select your app options caret (^)
  2. Select Statistics
  3. Select the Fraud Prevention tab
Installs rejected for click spamming will appear in one of the following columns:
  • Rejected installs Too Many Engagements
  • Rejected Installs Distribution Outlier
Reattributions rejected for click spamming will appear in one of the following columns:
  • Rejected Reattributions Too Many Engagements
  • Rejected Reattributions Distribution Outlier
Note: Installs that are rejected for click spamming will either be attributed to an authentic source found through Adjust’s attribution methodology, or, if no other source is found, to your Organic tracker.

Understand your distribution modeling statistics

For information on the KPIs, filters, and features of the fraud prevention statistics view, see our fraud prevention reporting pages.

Distributing modeling FAQs

What is click spam?

At Adjust, we define click spam as all illegitimate click activity. For fraudsters, the goal of click spamming is to poach attributions from your organic users—i.e., to have a certain number of your organic installs falsely attributed to a network. This way, it appears that their campaigns generate high volumes of valuable users. Ultimately, not all click spam is premeditated fraud. It can range from networks that send views as clicks to servers that send catalogs of artificial clicks. Another common example is when an app invisibly loads and clicks ads in the background.

How does Adjust identify click spam?

Adjust’s method for rejecting attribution from click spam is based off of the click-to-install-time distribution. The first step is to disqualify high-frequency clicks that try to manipulate the click-to-install distribution. The second step is to reject attribution using distribution modeling.
Hyper engagement
In order to mimic realistic click-to-install-time distributions, fraudsters will repeatedly send the same click in recurring intervals. In doing so, they produce a “last click” that is always relatively close to the install.

When an install occurs, Adjust checks all eligible clicks within the relevant attribution window. If we recognize any high-volume click patterns, we remove the clicks from consideration. This allows us to correctly attribute the install to the next legitimate click or as an organic user.

Once we have eliminated all attempts to manipulate the click-to-install-time distribution we can apply distribution modeling to detect the remaining click spam.
Distribution modeling
We developed our method of distribution modeling by reviewing statistical data and analyzing actual fraudulent activity. Based on this research, we determined that 90% of installs were recorded within the first hour of click time. This behavior indicates a strong correlation between click and install.

Fraud, however, shows no such correlation between click and install. Since the user never actually clicked, and was never redirected to the store, their install will be independent of the click time. Therefore, when organic users are randomly poached by click spam, the click-to-install-time distribution will be evenly spread out across the entire attribution window.

Knowing this, we defined a lower threshold for installs recorded within the first hour of clicking. If the number of installs made after the first hour of click time exceeds a certain percentage of installs made within the first hour of clicking, Adjust will begin to disqualify clicks from attribution. Therefore, the install will be attributed to the next eligible tracked source or as organic traffic.

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