Research On User Requirements Analysis Based On Virtual Brand Community

R&D is an important part of an enterprise's product strategy.From the perspective of R&D management,companies will conduct a related market demand survey in the early stage of product R&D.It can be seen that analysis of user demand has always been necessary and critical.Virtual brand community has become a new channel for acquiring user demand.Users can feedback product experiences and opinions and express their hopes for product improvement in the community.These feedbacks and expressions imply user demand and users' satisfaction with the demand,which can provide companies with targeted product development strategies.Because of the openness and sharing characteristics of virtual brand communities,the online commentary information posted by community members is usually complicated and hidden,and there may even be false commentary information and useless information.How to ensure the authenticity and validity of data sources,and which method is used to analyze user demand will be the main issues in this study.First of all,the article identifies the leading users in the virtual brand community.The sources of users in the virtual brand community are different,and the reliability and reference value of the published comments are also different.Leading users can discover product defects earlier and express future market demands.Leading users' online commentary information can better reflect product issues and the direction of product innovation.Therefore,identifying leading users in virtual brand communities can ensure the quality of information from the source of demand information.This paper uses dynamic network analysis methods to identify six types of leading users in virtual brand communities.: focus,characters,active characters,potentially active characters,discussion monopoly,and knowledge monopoly,which are the foundations for the following evaluation based on leading users' online reviews to tap user satisfaction and fulfillment demand.Then,the second part of the article obtains the user's demand from the online review information published by the leading users.The paper uses the method of text mining to process the online comments published by leading users,and uses the improved keyword determination method to obtain user demand keywords.Through word shows,demand point distribution and demand clustering to visualize demand,further identify different product attributes and the user demand to be urgently addressed.Finally,the third part of the article evaluates the satisfaction of the acquired user demand,and the evaluation of the degree of satisfaction of the demand can effectively grasp the direction of product development and improvement.Based on the Kano model user demand are divided into basic demand,expected demand and charm demand,and calculate the degree of fulfillment of the demand using sentiment analysis,the combination of those two builds a demand-satisfaction evaluation model.The model quantitatively evaluates the degree of user satisfaction based on the perspective of the type of user demand,and determines the priority of product development and improvement based on the characteristics of different types of demand and the degree of user satisfaction.