With　the　development　of　e-commerce,　more　and　more　enterprises　attach　importance　to　precision　marketing　for　network　channels.　This　study　adopted　the　decision　tree　algorithm　in　data　mining　to　achieve　precision　marketing.　Firstly,　precision　marketing　and　C4.5　decision　tree　algorithm　were　briefly　introduced.　Then　e-commerce　enterprise　A　was　taken　as　an　example.　The　data　from　January　to　June　2018　were　collected.　Four　attributes　including　age,　income,　occupation　and　educational　background　were　selected　for　calculation　and　decision　tree　was　established　to　extract　classification　rules.The　results　showed　that　the　consumers　of　the　products　of　the　company　were　high-income　young　and　middle-aged　people,　middle-income　young　people,　middle-income　middle-aged　and　elderly　people　with　a　college　degree　or　above,　low-income　middle-aged　people　with　a　college　degree　or　above　and　low-income　elderly　people　with　a　state-owned　enterprise.　After　precision　marketing　to　these　customers,　it　was　found　that　the　monthly　sales　volume　of　the　enterprise　increased　by　22.82%　and　the　marketing　cost　decreased　by　28.21　%,　which　verified　the　effectiveness　and　application　value　of　precision　marketing　and　showed　that　the　decision　tree　algorithm　could　provide　enterprises　with　decision　support　in　precision　marketing.