Customer Behaviour Prediction Using Web Usage Mining

Customer Behaviour Prediction Using Web Usage Mining

Abstract:

E-commerce depends on web usage mining to predict customer behavior. Businesses can learn customer preferences and patterns by analyzing customer behavior and website traffic data. This article discusses the Customer Behaviour Prediction Using Web Usage Mining project’s significance, goals, details, and pros and cons.

Introduction:

Web usage mining helps understand customer behavior and improve website performance. E-commerce sites can improve performance, customer experience, and product recommendations by capturing and analyzing user behavior data. Customer Behaviour Prediction Using Web Usage Mining uses this data to predict customer behavior and optimize business strategies.

Objective:

The Customer Behaviour Prediction Using Web Usage Mining project helps e-commerce websites analyze and mine web traffic data. The system predicts future customer behavior by identifying patterns in analytics data and providing decision-making statistics. Continuous optimization improves customer acquisition, profitability, and website performance.

Project Details:

1. Technology Stack: a. Programming Language: Java b. Database: MySQL c. Data Mining Techniques: Association Rule Mining, Sequential Pattern Mining
2. System Functionality: a. Web Traffic Data Recording: The system records and captures the flow of customer behavior on a website. It collects data such as web shopping/buying patterns, user budget tracking, user bounce rates, and other site usage factors.b. Data Mining and Pattern Analysis: Using data mining techniques such as association rule mining and sequential pattern mining, the system analyzes the recorded data to identify behavioral patterns and trends. This analysis helps in predicting future customer behavior and preferences.c. Performance Optimization: The system provides insights into website performance based on customer behavior data. By understanding user preferences and needs, site owners can make appropriate changes and optimize the website to improve customer satisfaction and acquisition.d. Future Planning: The Customer Behaviour Prediction Using Web Usage Mining project enables business proprietors to develop future plans based on the study of customer behavior. By understanding customer preferences and predicting their actions, businesses can align their strategies to meet customer needs effectively.

Conclusion:

Customer Behavior Prediction Web Use Mining helps e-commerce websites analyze customer behavior, predict trends, and optimize performance. Data mining can improve customer acquisition, profitability, and user preferences. The system can plan future actions and is easy to install, but it uses a lot of memory and may be inaccurate. However, the project offers e-commerce businesses a valuable solution for understanding and leveraging customer behavior to succeed in the competitive online market.