C4.5 Algorithm Optimization And Its Application In The Sales Of Industrial Products

The production and sale of industrial products is an indispensable and important factor in real life.It has affected all aspects of society and plays an important role in many areas of society.At the current stage,there are many types of industrial products,the process of decision-making procurement is cumbersome,the amount of transactions involved is large,and the requirements for professionalism are strong.The traditional way of purchasing depends on customer relationship purchasing,channel purchasing or choosing to purchase on the sales platform,which leads to customers need to spend a lot of time and energy.For the company's sales platform,it is able to analyze the intentions of customers shopping,achieve accurate marketing,and predict the sales of industrial products,only to occupy a place in the fierce competition in today's society,but also the only way to win the sales platform system operation.In order to achieve accurate marketing to customers and forecast sales of industrial products,an industrial product sales forecasting system was established.Sales forecasting system helps sales staff solve the problem of accurate marketing to customers and helps platform managers predict the sales of industrial products.Therefore,the system has the following functions:1)Data preprocessing function.Extract all data tables from the e-commerce platform database,combined with sales data record tables to complete the system's data acquisition;the acquired data needs to be pre-processed to eliminate the existing "dirty" data;due to the different sources of data,the need to complete the data Format conversion.2)Predictive model function.For accurate marketing,it is necessary to analyze different types of customers,different types of industrial products,and related influencing factors;to realize the forecasted sales of industrial products,it is necessary to analyze different types of industrial products and factors that affect their sales.In order to accurately predict the analysis results,the C4.5 decision tree algorithm was chosen to build the prediction model,and the Gini index was introduced to improve the accuracy of the system in predicting sales of industrial products.The improved model is not only fast in modeling,but also simple in processing classification and improves the accuracy of system prediction.For accurate marketing,the relevant influencing factor data is imported into the forecasting model.The forecasting model gives the type of customer preference for industrial products;for forecasting the sales of industrial products,different types of industrial products and influencing factors are introduced into the system and forecasted.The sales of this type of industrial products.3)Adjust the marketing strategy function.Sales personnel can achieve accurate sales for users based on the results of the forecast model,and provide benefits for the company to improve performance for the company.Platform managers can adjust platform marketing strategies and also facilitate the company's warehouse storage.Combining with the actual situation of the e-commerce sales platform,through the research on users and industrial products on the e-commerce sales platform,find out the industrial products that the user will purchase in the future and predict the sales of industrial products.By formulating appropriate sales strategies,it will bring positive meaning to the platform's sales and long-term business planning.