Business Analytics for Used Car Price Prediction with Statistical Models

Abstract

With the development of the used car market, the demand for a more accurate and scientific price prediction model of used cars becomes urgent. This paper uses multiple linear regression，decision tree and random forest to build up the automobile price forecasting model. We use means to cluster cars and find out that some factors like power, kilometers, gearbox have an influence on the price. According to the analysis, we find out that random forest has the best prediction performance，make sure R2 reaches 0.92 will be enough. 1. BIG DATA AND ITS USE In essence, the value of big data for commercial projects is to organize the circulation of better products or services, solve most people's needs in the fastest and most efficient way, and achieve stable income. In fact, big data has already provided practical applications for the development of business. Here is the summary of the five fundamental values and application scenarios of big data commercial applications. To begin with the tagging management. Big data can achieve a relatively fine division of users. [1]For example, the current SCRM system can automatically label different groups of people, continuously operate and calibrate user labels, which realizes the enrichment and improvement of each user's portrait, and finally realizes the accurate push and personalized service of the brand to different users.[2] Next is the ARVR big data commercial advertising scene enhancement and simulation. Deeply integrate "big data" and analytical technologies for business marketing to successfully transform consumer operations and business models. Enabling brands to access more effective information in more interactive ways and store and model user behavior information and transaction information anytime, anywhere [3]. Any transaction process, product usage scenario and consumption behavior can all be managed by data and visualization. Furthermore is the improvement on the return of sales investment[4]. Improving the return on investment of the whole marketing management and customer acquisition transformation based on the existing operation mode. With the help of big data capabilities, a company or brand customer can perform a comprehensive analysis of information from the cloud, the Internet, and local databases to form a good operational climate for the entire enterprise, ultimately outputting customer conversion and business profits [5]. Then is the interactive customer management. It can be understood as social CRM or interactive CRM management. According to different scenarios of users, basic information and behavioral catches of users are collected, and users are analyzed from different dimensions to comprehensively understand the preferences, habits, consumption tendencies, and consumption-ability of each user. And new customers are made through digital operation to enhance the attention of brand users, improve customer loyalty, and stimulate sustainable consumption of users[6]. Moreover, deliver personalized and accurate information. This is an open access article distributed under the CC BY-NC 4.0 license-http://creativecommons.org/licenses/by-nc/4.0/. 542