Enterprise Customer Value Analysis For Precision Marketing

Nowadays,the Internet is developing rapidly.Internet technology has been widely used in various industries,and the demand for mobile working is rising sharply.Under the influence of the information coordination mechanism,part of the work of the enterprise has realized mobile office,which has solved various restrictions on information dissemination.With the gradually intensified competition in the mobile office industry,mobile office manufacturers need to accurately monitor and insight into customer value,in order to tap the consumption power and purchasing power of potential customers,avoid the loss of high-quality customer resources,and improve the competitiveness of enterprises in the fierce market environment.Based on the theory of customer value,using the method of user portrait corporate customers with the technology of mobile industry companies to portrait,,to forecast the customer value,for the mobile industry manufacturers to carry out accurate marketing activities provide guidance.Improve enterprise customers’ satisfaction,consumption stickiness and loyalty to mobile office products.Firstly,based on the value of enterprise customers in the mobile office industry,the index system of customer portrait data is designed.The soft evaluation index is introduced to build an index system of customer potential value with different collection time and frequency,which integrates the consumption ability,loyalty and economic benefit of enterprise customers.Secondly,based on the data space grid,it provides efficient and high-precision algorithm support for mobile office industry manufacturers to dynamically update existing enterprise customer group portrait and value prediction.Then,mobile office industry manufacturer W was taken as empirical research object,through a third party web site and mobile office industry manufacturers internal financial system,integrated service system,customer relationship management system,product use the feedback module,collection and enterprise customers scale strength,asset structure,operation ability,profit ability,for the product evaluation and related data.The improved CFSFDP clustering algorithm proposed in this study was used to carry out clustering analysis and value prediction on customer portrait data.The existing customers of W Company were divided into five cluster clusters and mapped into four customer value classification systems: "Gold Customer","Risk Customer","Marginal Customer" and "No Investment Value".And put forward the corresponding marketing strategies and customer value improvement measures,guide W company to carry out precision marketing activities.