User behavior on the Web: prediction of retention

Predicting customer behavior represents a significant role in the dynamic web environment. Knowing customer satisfaction with services, content or goods is a good way for merchants to respond and take action to increase customer satisfaction. Conversely, if we know that the customer is definitely leaving, we do not need to spend more money on his conviction or providing services.

Through web applications, we can record user activity with a variety of information that can be used to predict their behavior in a variety of ranges – whether at the user’s loss level, subscription to the service, or the purchase of additional goods.

Analyze machine learning approaches that can be used to predict customer behavior with an emphasis on the use of web application data. Explore the features that influence customer decision-making and maintain interest in the content offered in the selected application domain. Identify significant characteristics that influence customer decision- making and/or content analysis of the elements with which they interact. Design a prediction method based on identified attributes. Verify the suggested solution in the selected domain on a non-trivial sample of data (e-commerce, etc.).