Faster, Smoother, More Engaging: Personalized Content Pagination
Abstract
Traditional pagination techniques of loading content in fixed pages or blocks often lead to slow loading times, disruptive transitions and a frustrating user experience especially on devices with poor internet connectivity. We could leverage AI to move beyond static pagination by analyzing individual user engagement behaviour and network conditions to dynamically adjust how and what content is loaded.
In this article, we discuss two primary AI techniques to understand user engagement: Firstly we discuss scroll depth and speed tracking that predicts user interest based on scrolling behavior. Secondly we discuss dwell time analysis that identifies engaging content by tracking time spent on page sections. User behavior data such as scroll events and visibility changes are typically collected on the client side using JavaScript. This data is then sent to the server where machine learning (ML) models such as regression or decision trees are used to analyze and predict consumption patterns thereby informing content loading strategy. There are lots of benefits of using AI-enabled personalized content loading. This use of AI leads to faster content loading, smoother user interactions, and better user engagement and retention. Technical infrastructure costs are also reduced by optimizing data transfer and server side resources.
In this article, we discuss two primary AI techniques to understand user engagement: Firstly we discuss scroll depth and speed tracking that predicts user interest based on scrolling behavior. Secondly we discuss dwell time analysis that identifies engaging content by tracking time spent on page sections. User behavior data such as scroll events and visibility changes are typically collected on the client side using JavaScript. This data is then sent to the server where machine learning (ML) models such as regression or decision trees are used to analyze and predict consumption patterns thereby informing content loading strategy. There are lots of benefits of using AI-enabled personalized content loading. This use of AI leads to faster content loading, smoother user interactions, and better user engagement and retention. Technical infrastructure costs are also reduced by optimizing data transfer and server side resources.
