E-commerce customer service satisfaction survey and intelligent customer service development suggestion research
DOI:
https://doi.org/10.54097/ehss.v2i.837Keywords:
e-commerce shopping guide, e-commerce customer service, intelligent shopping guide.Abstract
In recent years, with the rapid development of e-commerce technology, the scale and number of e-commerce platforms with online retail business as the core are increasing day by day.In the service system, because the content of customer requirements is inconsistent, the answer of customer service is also different, and the question service is easy to answer the question, thus reducing customer satisfaction.Therefore, the optimization of customer service system is worthy of our in-depth study, but also worthy of great attention.In this paper, through cluster sampling and convenient sampling survey method, questionnaire survey, combined with relevant secondary data, in various areas of the country to collect customer demand and evaluation of e-commerce platform intelligent customer service.To understand the development status of e-commerce intelligent customer service, and then through the analysis of the use of e-commerce platform intelligent customer service and influencing factors, for the development of e-commerce industry intelligent customer service to find the corresponding countermeasures.
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GUO Xiaozhe, PENG Dunlu, ZHANG Yatong, et al. GRS: A Generation-retrieval Dialogue Model for Intelligent Customer Service in e-commerce Field [J]. Journal of East China Normal University: Natural Science, 2020(5):11.
Pang Xiaomei. J company customer relationship management problems and countermeasures research [D]. Yangzhou university, 2020. The DOI: 10.27441 /, dc nki. Gyzdu. 2020.002483.
Ren Hongjie. Analysis of operating difficulties and Exploration of Lean Management of DOMESTIC E-commerce platform of YB Company [D]. East China University of Science and Technology,2018.
Zhang Dongzhe, Lin Yechuan. Science and Technology for Development, 201,17(03):558-564.]
Fang lee. E-commerce customer service processing communication skills analysis [J]. Modern marketing (management), 2020 (10) : 152-153. The DOI: 10.19921 / j.carol carroll nki. 1009-2994.2020.10.071.
Wang S J. Research on e-commerce recommendation system based on Spark platform [D]. China mining university, 2021. DOI: 10.27623 /, dc nki. Gzkyu. 2021.001152.
Wang L N. Research on cognitive oriented chatbot experience design for B2C e-commerce shopping guide [D]. Jiangnan university, 2020. DOI: 10.27169 /, dc nki. Gwqgu. 2020.000473.
Liang Jingyun. Online customer service system of the micro modeling and management optimization [D]. Shanghai jiaotong university, 2018. The DOI: 10.27307 /, dc nki. Gsjtu. 2018.001004.
Chen Yin-lei. Research on customer Service Quality Improvement of Small and medium-sized E-commerce Enterprises -- Taking Suzhou E-COMMERCE R Company as an example [J]. Modern marketing (management), 2020 (10) : 154-155. The DOI: 10.19921 / j.carol carroll nki. 1009-2994.2020.10.072.
Sun Jiexian. Intelligent customer service becomes the breakthrough of enterprise digital transformation [J]. China Informatization,2022(02):35.
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