The article presents a new model for predicting what users will buy based on their online behavior. By analyzing how users browse items, the researchers discovered patterns that reveal their preferences. They found that users who spend more time looking at a certain item are more likely to buy it. This insight led them to include browsing behavior and item categories in their prediction model. Testing their model on real data from a Chinese shopping site showed that it accurately predicts what users will purchase. This means that by looking at how users browse online, we can better understand what they want to buy.