Research On Precision Marketing Of A Enterprise Based On Data-Driven

During the years from 1979 to 2019,China’s economic growth was much higher than that of the world economy during the same period.In the past 40 years of rapid economic growth in our country,the use of steel products has been huge.However,with the changes in the steel structure in recent years,there has been an overcapacity of steel production,and the relationship between steel supply and steel demand is obvious.Some steel enterprises themselves are looking for market breakthroughs,They no longer place high hopes on agents and set up their own direct sales departments.Products and services are extending downward,which makes the steel trade enterprise’s living space further shrinks.It is urgent for steel trade enterprises to change from the traditional marketing mode focusing on steel products to the precise marketing mode focusing on developing customers of steel demand.The first part of this paper introduces the background and purpose of the research,and the second part introduces the related theories of precision marketing.After the introduction of A Steel Trading e-commerce Company,problems in the product-centered marketing model of A Steel Trading ecommerce Company were found out through questionnaire survey.Through interviews with steel industry experts,company executives and company staff to analyze the reasons for marketing problems of A Steel Trading e-commerce Company;Finally,this study believes that A Steel Trading e-commerce Company uses a large amount of data collected,through the data of these multidimensional in-depth analysis,make labels for users,put forward the use of user labels,the implementation of customer-centered marketing model to solve the marketing problems of A Steel Trading e-commerce Company.Based on the current situation of A Steel Trading e-commerce Company,this research proposes to solve the actual marketing problems in the company through data-driven precision marketing,so as to save the company’s marketing costs and improve user stickiness.And hope to take this as a typical case to provide reference for other enterprises to implement data-driven precision marketing.