The Chinese Consumers’Service Quality Satisfaction Differences of Cruise Tourism and Precision Marketing Strategy

The paper selected Chinese Cruise Line as the case study. Having based on the survey data of Chinese cruise tourism consumers, the factor analysis method, one-way analysis of variances method, cluster analysis method, and other quantitative and qualitative methods were taken to analyze Chinese consumers’ satisfaction differences of cruise tourism service quality with different segmentation markets and clusters markets, and the reasons of satisfaction differences were also explored. Then precision marketing strategy of Chinese cruise tourism with different segmentation markets and clusters markets from the supply-side reform perspective was discussed. The purpose of current research was to provide suggestions of precision management and precision marketing of Chinese cruise tourism for relevant enterprises and government departments.

Design and Implementation of Novel Precision Internet Marketing Patterns under the Big Data and Cloud Environment

Nowadays most of the cloud applications process large amount of data to provide the desired results. The Internet environment, the enterprise network advertising, network marketing plan, need partner sites selected as carrier and publishers. Website through static pages, dynamic pages, floating window, AD links, take the initiative to push a variety of ways to show the user enterprise marketing solutions, when the user access to web pages, use eye effect and concentration effect, attract users through reading web pages or click the page again, let the user detailed comprehensive understanding of the marketing plan, which affects the user＇ s real purchase decisions. Therefore, we combine the cloud environment with search engine optimization technique, the result shows that our method outperforms compared with other approaches.

A Big Data Based Dynamic Weight Approach for RFM Segmentation

Using the RFM(Recency,Frequency,Monetary value)model can provide valuable insights about customer clusterswhich is the core of customer relationship management.Due to accurate customer segment coming from dynamic weighted applications,in-depth targeted marketing may also use type of dynamic weight of R,F and M as factors.In this paper,we present our dynamic weighted RFM approach which is intended to improve the performance of customer segmentation by using the factors and variations to attain dynamic weights.Our dynamic weight approach is a kind of Custom method in essential which roots in the understanding of the data set.Firstly,Analytic Hierarchy Process is used to calculate the subjective weight,then the entropy method is applied to calculate the objective weight.Finally,we use comprehensive integration weighting method to combine the subjective and objective weight to obtain the final weight of the index to calculate the individual user value and quantify the user value difference.The experiment shows that the dynamic weight we used in RFM model is vital,affects the customer segmentation performance positively.Also,this study indicates that customer segments containing dynamic weighted RFM scores bring about stronger and more accurate association rules for the understanding of customer behavior.At last,we discuss the limitations of RFM analysis.