User Behavior Analytics, Artificial Intelligence, Algorithm
Abstract— AI-driven user behavior analysis is redefining how companies identify and engage with target audiences by using advanced machine learning algorithms to sift through vast amounts of user-generated content information. These systems allow companies to adapt strategies and deliver personalized experiences by taking into account subtle signals embedded in interactions with digital platforms. Through statistical models and flaw detection techniques, they deliver intelligence that not only engages the target audience but also neutralizes threats emerging in the digital environment. This change not only improves understanding, but also enhances cyber security measures to ensure consistency and digital security for users. AI-based user behavior analytics lies in their ability to identify subtle signals embedded in user interactions with platforms. Every click, swipe, or toggle has an important behavioral value waiting to be determined. Through a combination of statistical models, predictive analytics, and flaw detection techniques, these systems generate intelligence through the noise and allow businesses to customize their ideas and deliver personalized experiences that will resonate with their audience. Additionally, intelligence-driven user behavior analysis is an important defense against threats emerging in the digital environment. By constantly monitoring users, these systems can detect changes in design and indicate possible security breaches, fraud or crime. This approach allows organizations to strengthen their cyber security defences, reduce risks and protect valuable assets from danger. Therefore, AI-driven user behavior analysis not only provides strategic insights for growth, but is also an important factor in managing the security and integrity of the digital ecosystem.
Article Details
Unique Paper ID: 162906

Publication Volume & Issue: Volume 10, Issue 11

Page(s): 380 - 385
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