Linking Customer Retention to Intelligent Technology: An Optimization Approach

Marketing managers in the telecommunication sectors are confronted with considerable complexity. They have to make decisions about the optimum combination of products or offerings, customer groups and the means of interacting with potential customers. Further, in saturated markets such as mobile telephony, it is increasingly important to retain customers potentially to churn. On the optimal campaign planning, this research describes how the customer survey was conducted for those potentially churning customers based on which an optimal campaign planning was followed. This research engages with the subjects of customer retention from the perspective of a major mobile operator in Taiwan. Customers’ preferences with C&C (campaign offer and communication channel) were predicted and input for further analysis for target selection optimization. These models was proved novel in an organizational prototype project suggesting that the use of the hybrid of data mining and optimization approaches can be effective for target selection

A new model to support the personalised management of a quality e-commerce service

The paper presents an aiding model to support the management of a high quality e-commerce service. The approach focuses on the service quality aspects related to customer relationship management (CRM). Knowing the individual characteristics of a customer, it is possible to supply a personalised and high quality service. A segmentation model, based on the "relationship evolution" between users and Web site, is developed. The method permits the provision of a specific service management for each user segment. Finally, some preliminary experimental results for a sport-clothing industry application are described

What attracts vehicle consumers’ buying:A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?

Purpose: The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint. Design/methodology/approach: A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint. Findings: The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior. Research limitations/implications: The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation. Originality/value: Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective

Integrating IoT Analytics into Marketing Decision Making: A Smart Data-Driven Approach

With the advent of the Internet of Things (IoT), businesses have gained access to vast amounts of data generated by interconnected devices. Leveraging IoT analytics and marketing intelligence, organizations can extract valuable insights from this data to enhance decision-making processes. This paper presents a comprehensive methodology for data-driven decision-making in the context of IoT analytics and marketing intelligence. A real-time example is used to illustrate the application of this methodology, followed by an inference and discussion of the results. The rise of IoT has enabled real-time data collection from a wide array of interconnected devices, offering unprecedented opportunities for businesses to gain actionable insights. This paper focuses on the intersection of IoT analytics and marketing intelligence, exploring how data-driven decision-making can empower organizations to optimize their marketing strategies, customer experiences, and overall business performance

Using GIS and CRM to Develop Intermediary Portal E-Business Model: The Case of Automobile Industry

As Internet-based and other virtual technologies are being used more and more for procurement, supply chain management, product development, customer relations, and other business functions, and as they are proving to be efficacious, e-business has undoubtedly become an integral element in the business and engineering strategies of many automakers and suppliers. What e-business can provide to an automotive cooperation has been well stated for improving product quality, reducing costs, and shortening time-to-market cycles. In this paper, Renault Australia is used as an example of where the automobile industry is currently positioned in relation to E-Business. Online WebGIS-based Marketing Support System, developed as a portal e-business model, is designed to assistant information and knowledge exchange between the market analysis business and decision makers (and sales people) in auto industry. Incorporating marketing information gives rise to a better understanding of the potential of particular market areas or target markets, and helps identify the strengths and weaknesses of the competition in particular market areas or among particular target market segments. Such market analysis strategies obviously provide competitive advantages. Sharing information and obtaining market analysis outcomes through the Web will provide business decision makers with up to date information and knowledge. This solution will not only reduce costs for business planning, but also help to avoid the cost of wrong decisions