Factors Affecting Consumer Behavior Based On Big Data Analysis

At present,the Big Data has penetrated into every corner of the work life.In the area of marketing,Big Data on the area of precision marketing play an important role.Based on the data analysis of scenic areas of consumer behavior factors,the Darning Mountain Scenic Area of Nanning,the real situation as an example,the scenic area of the ticket consumption behavior and scenic areas of secondary consumption characteristics of consumer behavior for the future precision marketing proposed priactical advice,which for the current state to develop tourism economy in the context of the rational choice of marketing strategies to achieve sustainable and healthy development of scenic areas,has important practical significance.In this paper,we focus on the Big Data related to the scenic area,and explore the relationship between the Big Data and the number of tourists.The aim is to explore the deep-seated reasons for the number of tourists in various situations,to study the different types of tourists in the area of secondary consumption of consumer behavior differences and effects,looking for business growth potential of Scenic areas,so as to promote scenic sales,tourism,sustained and stable economic growth.In this paper,we use the related theories and methods of consumption behavior,Big Data,tourism consumption behavior,etc.The content mainly focuses on the establishment of the network sales analysis model,the data collection,the estimation of the model parameters,the data in the big data The type data to the scenic area network sales contribution rate computation several aspects.The main research results are:1.Based on the econometric theory,the multi-objective analysis model is established.After the multicollinearity diagnosis of the model,the optimal scheme is proposed.The model contains the data of the tourists' historical network purchase,the large data of the tourists visiting the official website,the massive search behavior of the search engine,the local PM2.5 data of the whole year,the five major factors of the local historical and weather data,The choice of factors should not only conform to the empirical formula,but also take into account the actual situation of the area,can reflect the reality of large data of the consumption behavior factors on scenic sales.2.DEA model is established to study the difference and influence of different kinds of tourists' consumption behavior in the scenic area,and to study the consumption behavior characteristics of the secondary consumption items in different scenic spots.3.Using the econometric model to analyze the Big Data,adjust the linear relationship of some variables,and then use the method of gradual introduction of variables with consumer theory,to determine the number of visitors per day as an explanatory variable,IP number,Baidu Index,weekend virtual Variables,bounce rates and dummy variables of air pollution as explanatory variables.According to the results,we can draw the following conclusions:(1)The increasing of the visitors can increase the number of tourists in Daming Mountain Scenic Area of Nanning;(2)The increase of search engine can improve the scenery of Daming Mountain The number of tourists;(3)tourists are more popular in the weekend to visit Nanning Daming Mountain Scenic Area;(4)the official website to increase customer interest content can significantly improve the number of tourists in Darning Mountain Scenic Area in Nanning;(5)the current quality of the weather in Nanning,the impact of small tourists.(6)the types of tourists in the area of secondary consumption impact.4.According to the results of the model interpretation,the author puts forward the optimization after the evaluation,and puts forward nine suggestions about the scenic spot from the reality:(1)Customer segments;(2)Accurate positioning market;(3)The official website set parent-child interest column;(4)The official website set limit snapping marketing activities;(5)To improve the rank of keywords of scenic spots on the search engine;(6)To enhance the winter season off-season turnover;(7)to enhance the secondary consumption of the project area turnover;(8)To enhance the scenic area in the climate marketing capabilities;(9)The use of Big Data analysis methods continue to optimize the operating efficiency of scenic spots.5.The innovation of this paper is as follows:(1)The model can still pass the significance test,that is,the model has stability,considering all the errors of the explanatory variables and the possible missing important variables.All of our suggestions and inferences Have credibility.(2)This paper aims to study the impact of various factors on the number of tourists and the consumption of the second consumption items in Darning Mountain Scenic Area in Nanning.The traditional econometric model is improved and the linear correlation of some variables is adjusted.Optimization,adopting the method of introducing variables step by step and combining with consumer theory to determine the explanatory variables and constructing a more stable measurement model.