Introducing Fraud Scores

A scoring system that determines the level of threat for every IP that clicks on your ad campaigns. This will help to differentiate between general fraud and extreme offenders.

Scoring Breakdown

Each fraud offense will generate a score that will add to the total score for that click. All ad clicks are given a grade from 0-15. The higher the score, the more likely the click is automated and malicious in nature.

Genuine Clicks: 0
Over threshold: 1
Range Blocking: 1
Aggressive Blocking: 1
VPN: 2
Bounced: 3
Fraudulent Device: 3
Out of Region: 4
Javascript Disabled: Max of 15

For example: A bot that is using a fraudulent device (3), behind a proxy wall (2), within a fraudulent range (1) and clicking from outside of your targeted country (4) - Will receive a total score of 10.

Scoring Categories

An IP that is behaving in a genuine way and not using any type of software will be given a score of 0 and will be represented as the color blue. 

An IP with a score of 1-3 will be represented with the color yellow. These are fraudulent clicks that have committed a singular type of offense, such as clicking over the threshold or using a VPN software. We often see competitors using this type of behavior.

Scores outlined in red are the most fraudulent type of click, scored from 4 to a maximum of 15. These are offenders who are committing multiple fraudulent offenses or clicking outside of your targeted country. The higher the score the more severe the threat. Clicks with a red fraud score have a much higher likelihood of being automated.

How can this help my ad performance?

Not all levels of fraud are equal and this will allow you to better understand where your most dangerous attacks are coming from and how often they are occurring. 

It will be easy to identify keywords and campaigns that are heavily affected by high danger offenders. This will help you to customize your campaigns to avoid automated activity. This will keep your ads safe from attacks made by bots and click farms.

Fraud Scores are available within the Fraud Analytics section. 

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