Click Detection Using AI and ML to Spot Fraudulent Clicks

fraud click detection

Fraud click detection  can harm almost any ad campaign. When Google flags a click as suspicious, it can hurt your business by blocking real customers and potential buyers from interacting with your ads. Standard methods like IP blocking or micro-blacklisting can stop bots, but they can also stop legitimate users from clicking on your ads.

Using AI and ML to spot fraud

Clicks that aren’t valid can be detected by analyzing cursor movement patterns. Real users move their cursors in a natural way, and bots move it in a smooth manner. Using AI, these patterns are recorded and analyzed to mark them as invalid.

Identifying fraudulent clicks is easy with a few tools. For example, Improvely can automatically download a report of every suspicious click on your ads. This report will contain the date and time of the suspicious click, the IP address, what ad was clicked, the clicker’s location, and the referring URL.

Use this information to block IP addresses that are attempting to fraud your campaigns. By identifying and eliminating fraudulent IP addresses, you can save money on advertising costs while ensuring that your ads are delivered to legitimate customers.

Click Fraud 101: Understanding the Problem and Implementing Solutions to Protect Your Business

Preventing fraudulent clicks is easy with a little help from AI and ML. For example, Improvely can analyze cursor movements to detect fake clicks by tracking how a user’s cursor moves as it clicks on different links and buttons.

A variety of artificial intelligence (AI) and machine learning (ML) algorithms can be used to develop effective click detection models. These algorithms include support vector machines (SVM), k-nearest neighbors (KNN), deep learning, and gradient boosting generative adversarial networks (GBDT).