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Optimizing The Precision Marketing Strategy Of Company X By The User Portrait

Posted on:2024-08-01Degree:MasterType:Thesis
Country:ChinaCandidate:Z Q ZhangFull Text:PDF
GTID:2531307121484904Subject:(professional degree in business administration)
Abstract/Summary:PDF Full Text Request
In recent years,with the popularization of the Internet and the digital transformation of traditional industries,garment washing and care industry is also showing a trend of information,digital and intelligent.Company X has created an intelligent community laundry platform,which integrates intelligent cabinets receiving and dispatching,logistics distribution and central laundry factory.However,due to the inaccuracy of target customer identification,customer conversion efficiency is not high,how to optimize its precise marketing strategy has become an imminent challenge to X company.Firstly,the problem of precision marketing in X company is analyzed by statistical analysis and interview survey.Secondly,the user tag is extracted based on the extensive collection of user data on the platform.Finally,based on the user portrait label model,this paper puts forward precision marketing optimization strategy from three aspects:target market selection,user life cycle precision marketing and precision marketing platform digitization.Based on the user portrait model,the target market of X Company’s intelligent community laundry platform is divided into 3 categories: high value users,loyal users and ordinary consumers.At the same time,in each stage of user’s life cycle,find out the Aha time of user’s key behavior transformation,combine user portrait,complete marketing closed-loop accurately,promote the conversion rate of every link of user’s life cycle,improve the efficiency of X company’s precision marketing.The strategy and solution of improving marketing precision based on user portrait presented in this study has certain reference value for small and medium-sized service enterprises.
Keywords/Search Tags:precision marketing, User portrait, User life cycle, K-means clusterin
PDF Full Text Request
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