With　the　development　and　popularity　of　mobile　networks,　online　shopping　has　gradually　become　a　trend.　For　enterprises,　the　traditional　marketing　mode　has　been　difficult　to　play　an　effective　role　when　facing　the　emerging　online　shopping　mode.　This　study　aims　to　improve　the　revenue　benefits　of　online　shopping.　This　paper　first　introduces　the　traditional　marketing　mode　and　then　selects　the　data　mining　model　used　for　consumption　preference　segmentation　to　build　an　online　marketing　mode.　An　example　analysis　was　conducted　on　a　book　sales　company　and　a　real　estate　company.　The　results　showed　that　more　users　in　this　community　preferred　five　types　of　books,　and　the　percentages　from　high　to　low　were　teaching　and　learning　materials,　modern　novels,　popular　science　books,　historical　literature,　and　classical　novels;　more　customers　preferred　online　platforms　among　the　channels　for　collecting　information　on　home　purchase.　No　matter　it　was　the　book　sales　company　or　the　real　estate　company,　compared　with　no　fluctuation　in　the　company＇s　turnover　under　the　traditional　marketing　mode,　the　turnover　of　the　company　increased　month　by　month　after　adopting　the　online　marketing　mode.　©　2022　-　IOS　Press.　All　rights　reserved.