Research On Hotel Customer Demand Analysis Based On Online Reviews

The company’s cost budget and resources are limited.In order to remain competitive in the market,companies must effectively tap the customer needs of their products or services,prioritize customer needs,and allocate resources appropriately to improve customer satisfaction.Traditionally,companies obtain analytical data of customers through the methods of questionnaires or interviews.However,these methods are time-consuming and laborious in obtaining data.In addition,the quality of the data obtained from the survey depends on the complexity or length of the questionnaire^[3].Furthermore,the data obtained from the survey may soon become obsolete^[4].Therefore,this study attempts to use other data sources to mine customer needs.With the development of information technology and the Internet,more and more users are posting online reviews about products or services on the Internet.These online reviews contain a wealth of valuable information including emotions and opinions of customers about products or services.Compared to the questionnaire,online reviews are publicly available and can be collected at low cost and on a large scale.In addition,the comments are published by users spontaneously,which can better reflect the real needs of consumers.Furthermore,online reviews are updated in real time,and real-time analysis can be used to keep abreast of changes in consumer demand.But there are three main problems First,the review data is mixed,and how to extract useful comments from online reviews from a product or service design perspective.In addition,online reviews are unstructured data,so how to process the online review data into useful structured data.Finally,how to apply the processed comment data to the customer demand mining model to analyze customer needs.In response to the above problems,this study proposes a method for extracting usefulness comments from the perspective of product or service design and improvement,and applies it to the usefulness comment extraction of Chinese hotel online reviews.Then,this study uses the word2Vec method to train the word vector model to extracts the attribute characteristics of the hotel service from the online reviews,constructs the sentiment dictionary and uses the sentiment dictionary matching method to analyze the sentiment of the hotel service attributes.Finally,this study presents a IPA-KANO customer demand analysis model based on online reviews to analyze customer needs for the first time.A conjoint analysis method is used to determine the importance of customer needs,and a mapping rule is designed to map customer needs into different KANO categories.Taking the importance of customer demand as the horizontal axis,the satisfaction of customer demand as the vertical axis,and the KANO category as the marker point to construct the IPA-KANO model based on online comment.At the same time,the customer needs are analyzed from the perspective of enterprise competition and time change in customer demand.Taking Qingdao hotel economy chain hotel and luxury hotel as an example,the validity of the IPA-KANO customer demand analysis model based on online review is verified.