Design and Application of a Prediction Model for User Purchase Intention Based on Big Data Analysis

Abstract

With the proliferation of information technology, precision marketing has emerged as an important strategy to increase the return rate. To improve the effect of precision marketing, the traditional manual survey should be replaced with big data analysis to disclose user demand and understand user purchase behaviors. For accurate forecast of user purchase behaviors, this paper firstly analyzes the quality and features of the historical data on user purchases, and preprocesses the data by a self-designed procedure. Then, the various features of user purchase behaviors were summarized and optimized, and the features of user purchase intentions for products were extracted. On this basis, a DenseNet purchase intention prediction model was established on Bagging strategy. The effectiveness of the proposed model was proved through experiments. Our model enables enterprises to quickly identify potential sales targets.