Research And Example Implementation Of SCRM System Based On Twitter

Nowadays,the growing interaction between social media and CRM(Customer Relationship Management)drives companies to transform and develop SCRM(Social Customer Relationship Management).SCRM has become a research focus in the fields of management science,marketing,customer relationship management,etc.However,SCRM-related research is still in the exploratory stage,and there are few theoretical and empirical studies.Macro research is relatively scattered.Few studies have focused on specific SCRM system construction,and no scholars have used new methods such as machine learning to implement SCRM system functions.They cannot provide better and more specific guidance for corporate SCRM strategies.Therefore,it is necessary to clear the definition and characteristics of SCRM and construct an SCRM system to answer how enterprises should use social media data to upgrade the CRM management paradigm.In order to answer the above questions,the following studies were carried out: 1)The definition of SCRM was summarized and refined based on the literature review,and the characteristics and connotation of SCRM were explained from four aspects: communication mode and customer relationship,customer portrait and customer management,data knowledge and management process,technical tools and value creation.2)Based on this macro theory,this thesis proposes an exemplary SCRM system framework based on Twitter to form a specific SCRM closed-loop structure.3)Based on Twitter's SCRM exemplary system framework,empirical research on Twitter dialogue data for customer support purpose was conducted in perspective of products and services.The specific contents include: First,this thesis uses the research method of the topic model to mine and extract topics related to the company's products from the data,and sort the importance of the topics to get the product improvement direction.Secondly,this thesis uses the research method of sentiment analysis to confirm the positive relationship between rapid response and customer satisfaction,and uses the Seq2Seq(Sequence to Sequence)deep learning algorithm to develop an automatic question-answering model,demonstrating the effectiveness of the model.This thesis expands SCRM theory and methodology,and is the first research to construct and propose an exemplary system framework for Twitter-based SCRM.This thesis makes up for the research gap in SCRM system architecture,and provides guidance for enterprises to implement SCRM.In addition,this thesis is the first empirical research from the perspective of SCRM products and services.It is also the first domestic study to apply artificial intelligence related research methods to analyze how companies can better implement SCRM.The results can be integrated into the enterprise's CRM system to promote the automation of products and services,the implementation of SCRM,and improve the effectiveness and timeliness of SCRM systems.