{"title":"基于用户行为模式智能分析改进客户关系管理","authors":"Maria M. Monastyrskaya, V. Soloviev","doi":"10.1109/MLSD49919.2020.9247718","DOIUrl":null,"url":null,"abstract":"A set of regression, cluster analysis, and association rule mining models, is proposed to search for patterns in user behavior regarding marketing campaigns taking into account user characteristics and financially significant metrics. Using the example of two organizations, it was possible to accurately predict the cost of customer acquisition (CPA, cost-per-action). The use of the models proposed allows organizations to improve advertisement settings to increase online advertising efficiency.","PeriodicalId":103344,"journal":{"name":"2020 13th International Conference \"Management of large-scale system development\" (MLSD)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Improving Customer Relationship Management based on Intelligent Analysis of User Behavior Patterns\",\"authors\":\"Maria M. Monastyrskaya, V. Soloviev\",\"doi\":\"10.1109/MLSD49919.2020.9247718\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A set of regression, cluster analysis, and association rule mining models, is proposed to search for patterns in user behavior regarding marketing campaigns taking into account user characteristics and financially significant metrics. Using the example of two organizations, it was possible to accurately predict the cost of customer acquisition (CPA, cost-per-action). The use of the models proposed allows organizations to improve advertisement settings to increase online advertising efficiency.\",\"PeriodicalId\":103344,\"journal\":{\"name\":\"2020 13th International Conference \\\"Management of large-scale system development\\\" (MLSD)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 13th International Conference \\\"Management of large-scale system development\\\" (MLSD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MLSD49919.2020.9247718\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 13th International Conference \"Management of large-scale system development\" (MLSD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MLSD49919.2020.9247718","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improving Customer Relationship Management based on Intelligent Analysis of User Behavior Patterns
A set of regression, cluster analysis, and association rule mining models, is proposed to search for patterns in user behavior regarding marketing campaigns taking into account user characteristics and financially significant metrics. Using the example of two organizations, it was possible to accurately predict the cost of customer acquisition (CPA, cost-per-action). The use of the models proposed allows organizations to improve advertisement settings to increase online advertising efficiency.
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