{"title":"开发协作式客户关系管理系统中自动化客户支持服务的实施框架","authors":"R. Li, M. Tee","doi":"10.1109/IEEM50564.2021.9672894","DOIUrl":null,"url":null,"abstract":"Collaborative Customer Relationship Management (CCRM) has developed Automated Customer Support Services (ACSS), where it focuses on providing more efficient and immediate customer service. Through chatbots, virtual customers, internet routing, and automated responses, technology has evolved to aid the customer support sector through automations trained by Artificial Intelligence (AI), Machine Learning (ML), and other advancements in technology. However, ACSS is relatively new with various implementation frameworks in choosing ACSS platforms developed by CRM experts for organizations. The study aims to cover the research gaps of integrating the customer perspective in terms of behavioral trends, data security issues, engagement and responses, and proper maintenance and evaluation of the ACSS performance based on the customer relationships and experience, through the development of a new implementation framework for ACSS in an organization. Through a rating-questionnaire answered by CRM experts on three (3) different ACSS based on different frameworks and the developed one by the study, the findings show that the developed framework enhances customer relationships and experiences more than the existing frameworks, thereby validating the effectiveness of the implementation framework in the study.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"1 1","pages":"1092-1096"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Developing an Implementation Framework for Automated Customer Support Service in Collaborative Customer Relationship Management Systems\",\"authors\":\"R. Li, M. Tee\",\"doi\":\"10.1109/IEEM50564.2021.9672894\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Collaborative Customer Relationship Management (CCRM) has developed Automated Customer Support Services (ACSS), where it focuses on providing more efficient and immediate customer service. Through chatbots, virtual customers, internet routing, and automated responses, technology has evolved to aid the customer support sector through automations trained by Artificial Intelligence (AI), Machine Learning (ML), and other advancements in technology. However, ACSS is relatively new with various implementation frameworks in choosing ACSS platforms developed by CRM experts for organizations. The study aims to cover the research gaps of integrating the customer perspective in terms of behavioral trends, data security issues, engagement and responses, and proper maintenance and evaluation of the ACSS performance based on the customer relationships and experience, through the development of a new implementation framework for ACSS in an organization. Through a rating-questionnaire answered by CRM experts on three (3) different ACSS based on different frameworks and the developed one by the study, the findings show that the developed framework enhances customer relationships and experiences more than the existing frameworks, thereby validating the effectiveness of the implementation framework in the study.\",\"PeriodicalId\":6818,\"journal\":{\"name\":\"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"volume\":\"1 1\",\"pages\":\"1092-1096\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEM50564.2021.9672894\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM50564.2021.9672894","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Developing an Implementation Framework for Automated Customer Support Service in Collaborative Customer Relationship Management Systems
Collaborative Customer Relationship Management (CCRM) has developed Automated Customer Support Services (ACSS), where it focuses on providing more efficient and immediate customer service. Through chatbots, virtual customers, internet routing, and automated responses, technology has evolved to aid the customer support sector through automations trained by Artificial Intelligence (AI), Machine Learning (ML), and other advancements in technology. However, ACSS is relatively new with various implementation frameworks in choosing ACSS platforms developed by CRM experts for organizations. The study aims to cover the research gaps of integrating the customer perspective in terms of behavioral trends, data security issues, engagement and responses, and proper maintenance and evaluation of the ACSS performance based on the customer relationships and experience, through the development of a new implementation framework for ACSS in an organization. Through a rating-questionnaire answered by CRM experts on three (3) different ACSS based on different frameworks and the developed one by the study, the findings show that the developed framework enhances customer relationships and experiences more than the existing frameworks, thereby validating the effectiveness of the implementation framework in the study.