{"title":"Multi-Agent Aspect Level Sentiment Analysis in CRM Systems","authors":"Doru Rotovei","doi":"10.1109/SYNASC.2016.068","DOIUrl":null,"url":null,"abstract":"Customer Relationship Management (CRM) becamethe best practice for any business that wishes to create, develop and enhance the customer value and implicitly thebusiness shareholders value. Businesses became more aware that in the long term beyondthe first sale customer retention is of crucial importance. However, in most cases, the first sale creates the first impressionof the business. Being able to manage the customer expectationsthrough aspect level sentiment analysis and proper guidancetowards the first purchase, can make the difference between astrong retention rate and a weak retention rate. In this paper we present an approach for designing amulti-agent expert system using product aspect level sentimentanalysis. The goal is to ease the conversion of a prospect toa customer by giving proper recommendations to acceleratethe sale. Aspect level sentiment analysis takes into accountnot only the overall sentiment of the interaction but also thegranular sentiment on the feature level of the products to be soldlike for example price or quality. The multi-agent technologyextends the CRM Systems and provides scalability, robustnessand simplicity of design. Furthermore a prototype was developed and its design andresults are presented and discussed.","PeriodicalId":268635,"journal":{"name":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"17 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2016.068","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Customer Relationship Management (CRM) becamethe best practice for any business that wishes to create, develop and enhance the customer value and implicitly thebusiness shareholders value. Businesses became more aware that in the long term beyondthe first sale customer retention is of crucial importance. However, in most cases, the first sale creates the first impressionof the business. Being able to manage the customer expectationsthrough aspect level sentiment analysis and proper guidancetowards the first purchase, can make the difference between astrong retention rate and a weak retention rate. In this paper we present an approach for designing amulti-agent expert system using product aspect level sentimentanalysis. The goal is to ease the conversion of a prospect toa customer by giving proper recommendations to acceleratethe sale. Aspect level sentiment analysis takes into accountnot only the overall sentiment of the interaction but also thegranular sentiment on the feature level of the products to be soldlike for example price or quality. The multi-agent technologyextends the CRM Systems and provides scalability, robustnessand simplicity of design. Furthermore a prototype was developed and its design andresults are presented and discussed.