Tourism product consumers clustering for developing the tailored marketing mix

Marketing mix appeared to be one of the most influential approaches on the marketing plans in the organizations. The current study seeks to examine the influence of marketing mix (4Ps – promotion, price, place and product) on the efficiency of CRM (responsiveness, empathy, customer relations, assurance and reliability) within the organic products market in Jordan. The researcher employed the quantitative approach through distributing a questionnaire on total of 37 individuals who were involved in the marketing field of organic products. The results of the study indicated that marketing mix appeared to have an influence of the efficiency of CRM practices within the marketing of organic goods in Jordan. The most influential variable appeared to be the price, which is considered to be high for organic product in Jordan, and that is why customer tend to avoid such product. Following the price came the variable of product, which was important as customers tend to give much emphasis on the specifications of the product and the fact that it is healthy and organic tends to appeal them regardless of the price. The study recommended increasing the level of awareness regarding organic products marketing strategies among the marketing managers in Jordan.

Successful companies do not only pursue sale, but they are looking for satisfactions of customers and their loyalty. This study aims to rank effect of services marketing mix elements on the customers’ loyalty in the City Bank. Method of this research is survey and causal-comparative and domesticated questionnaire was used for gathering data which its validity was confirmed by experts and its reliability with Cronbach alpha 0.908. Statistical sample size was 384 loyal customers of City Bank in Tehran based on Cochrane formula and simple random sampling was used as sampling method. Findings showed that there is significant relationship in average level between physical factors and environmental factors including distribution of physical facilities and customer loyalty and the relationship between competence related factors including promotion of employees or customers’ loyalty is strongly significant. Besides, there is significant relationship between services related factors including product, price, operation management and quality of services or customers’ loyalty in moderate level. It is suggested that for attracting loyal customers, more attention should be paid to promotion which has very strong relationship with customers’ loyalty. It is suggested that City Bank increases the motivation of employers in providing careful and rapid services for improving productivity and services quality by suitable incentives.

To improve the marketing activity and brand management and justify the most effective marketing decisions, organizations should implement different information technologies, mathematical methods and models into the marketing decision support system (MDSS). The goal of this paper is to form an architecture of an MDSS, the model base of which is developed on Data Science tools, in particular regression analysis and machine learning methods. The proposed MDSS is a multi-agent information system comprising nine intellectual agents (market environment monitoring, data processing, marketing mix modeling, price policy support, portfolio management, strategic analysis, forecasting, customer segmentation, and customer classification). The functionality of these agents is realized through Data Science, which allows for the optimization of marketing activities (e.g., an effective brand management strategy and its elements (portfolio strategy, price policy, and media strategy) or solving the problems of attracting new and retaining current customers with the maximal return on marketing investments). The MDSS analyzes the marketing environment, media activity, and business indicators by constructing different models and forecasting various combinations of marketing factors to select the best one. The joint work of MDSS agents provides decision-makers with interactive reports. The research findings offer a scientific basis for making effective marketing decisions based on data, and the proposed MDSS can become part of an intelligent system for planning marketing activities.