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Customer Satisfaction Analysis Of Wearable Device

Posted on:2020-10-16Degree:MasterType:Thesis
Country:ChinaCandidate:S Y LiFull Text:PDF
GTID:2427330596481740Subject:Master of Applied Statistics
Abstract/Summary:PDF Full Text Request
With the development of Internet of things and the increasing demand for diversified service applications,domestic technology companies are actively responding to the call of the state to implement the "Internet +" and enter the wearable device market.Wearable devices are positioned in smart phone services,which can achieve powerful intelligent services by combining with the network and big data technology,and bring people an intelligent life experience.Data show that China is the world's largest market,with nearly 33% of the world's wearable equipment purchases in 2015.However,at present,domestic consumers do not have a high awareness of wearable devices.73% of the respondents have heard about wearable devices,but they do not know about them very well.Only 4% of the respondents have a good understanding of wearable smart devices.In addition,most consumers are initially attracted by the novelty and gorgeous appearance of wearable devices,which are regarded as fashion products rather than functional devices,and they give up using them after a period of time.It can be seen that wearable equipment has the problems of high abandonment rate and low penetration rate.The domestic market is still in the early stage of development,and has great development potential.To tap the greater potential of wearable equipment market,we need to have a deep understanding of the market.Enterprises need to timely understand the current use of wearable equipment by customers,to obtain factors affecting satisfaction,and on this basis,to optimize the functions and improve the quality of products,so as to solve existing problems and promote market development.Therefore,it is necessary to study what factors consumers pay attention to when purchasing wearable equipment and what are the main factors affecting customer satisfaction,and to build an evaluation index system for customer satisfaction of wearable equipment.In different stages of social development,consumers have different needs for the functions of products,and for different consumers,they have different concerns about products.In addition,the study found that 37.5% of online shopping users consider the user evaluation of goods when making shopping decisions.Therefore,it is more timely and advantageous to study user satisfaction through online reviews than market field research.This paper studies the satisfaction of wearable equipment customers in Jingdong Mall by grabbing comments as sample data,and uses text mining method to analyze the comprehensive impact of various factors on satisfaction,and puts forward suggestions.Firstly,Python web crawler is designed to capture the commodity information and specific comments of wearable equipment in Jingdong Mall,carry out data cleaning and remove stop words,then comment word segmentation and word frequency calculation;secondly,word cloud analysis and correlation analysis are carried out to get the characteristic factors and semantic network that customers pay attention to;secondly,emotion word list,degree adverb word list and negative word list are established and counted.Finally,a multi-factor and multi-level satisfaction calculation model is constructed,and the relative importance of each factor is judged according to the results of the decision tree,and a judgment matrix is constructed based on the network data,and the weights of single-ranking index and total-ranking index are calculated to comprehensively analyze customer satisfaction.At the end,based on the above analysis results,the existing problems of wearable equipment are summarized and reasonable suggestions are given.structure model is constructed,which consists of six criterion layers and four scheme layers under the general target layer.The relative importance of each factor is judged according to the results of decision tree,and the judgment matrix is constructed with network data.The weights of single-ranking index and total-ranking index are calculated to comprehensively analyze customer satisfaction.Degree.At the end,based on the above analysis results,the existing problems of wearable equipment are summarized and reasonable suggestions are given.
Keywords/Search Tags:wearable devices, satisfaction degree, Text mining, decision tree, Analytic hierarchy process
PDF Full Text Request
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