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Constructing the sustainable Online Social Network Marketing Community (OSNMC) is a particularly effective approach to trumpet the products and enhance the customer experience. Super users are considered as opinion leaders, high influence users, and other active users who play a crucial role in enhancing the sustainability of OSNMC. Recruiting sust...
Citations
... Online communities have become important platforms for online marketing by virtue of their large numbers of active users and fast information dissemination [6,40]. With the rapid increase in the number of community users, population heterogeneity also increases. ...
... Using qualitative research methods [40], 121 text topics were extracted, of which 4/5 were selected for experiment and 1/5 texts for saturation test. Group discussion is adopted to reduce the influence of personal bias on the results in the process of topic extraction. ...
In precision marketing for online communities, the existing text-based methods of user positioning cannot position new users rapidly, and they have low positioning efficiency when there is a large number of users. This research proposes a systematic method for the positioning of online community users. In this method, text mining and clustering algorithms are combined to cluster users, and then the user clusters are effectively matched with users' basic attributes through a multinomial logistic regression model. By this means, efficient positioning under the circumstances of a rapid increase in new users and a large number of users can be achieved. Calculation results from a real world example show that this method can effectively solve the problems found in traditional user positioning methods and provides a productive new approach to community user positioning. The study also offers suggestions for user classification management from the perspective of precision marketing.
... Network marketing [1,2] is a unique marketing mode accompanied by the Internet era. It is a point-to-point marketing that promotes products and brands to customers with the support of network platform. ...
In the era of rapid development of information, network marketing has gradually become one of the most popular marketing methods. But there are also some inevitable problems. The current network marketing is so aimless that people are bored with it and then marketing to the enterprise’s own brand, which makes the enterprise have to change the existing network marketing mode. Therefore, this paper takes big data as the background to study the innovation strategy of network marketing. This paper uses the form of questionnaire survey to investigate some consumers’ views and suggestions on online marketing in their daily life. According to the survey, big data can help marketers analyze consumer behavior preferences and market trends. In addition, this paper analyzes and introduces some problems existing in the traditional network marketing mode, and gives the network marketing strategy under the background of big data.
Purpose
The aim of this work is to provide a theoretical model that can help companies to develop a unique approach to achieve both corporate environmental sustainability (CES) and successful customer experience management (CEM).
Design/methodology/approach
A two-phase study achieved the research aim. The first phase consisted of the analysis of contemporary theoretical contributions with a focus on CES and CEM. In the second phase, taking a qualitative approach, the key dimensions identified in the initial analysis were investigated to explore the dominant perceptions of practitioners and to hone the theoretical categories.
Findings
Five innovative pathways emerged from the study to inform decision-making while maintaining the dual objectives of CES and successful CEM. These pathways are combined to offer a strategic tool for managers and for research advances. This original integrated model also offers six novel theoretical propositions that describe how to shape corporate decisions to achieve environmental sustainability in CEM.
Research limitations/implications
Firms can benefit from an approach that integrates CES and CEM to develop a new mindset for an innovative and valuable decision-making process and to design more captivating experiences for customers. Nevertheless, the efficacy and generalizability of the theoretical framework and propositions require empirical testing.
Originality/value
This paper makes an original contribution to the environmental sustainability and marketing literature by bringing together all elements in these fields of research in a conceptual model. Moreover, this paper proposes theoretical propositions that advance knowledge of the subject and offer ideas for future research and managers.
Effective mining of social media, which consists of a large number of users is a challenging task. Traditional approaches rely on the analysis of text data related to users to accomplish this task. However, text data lacks significant information about the social users and their associated groups. In this paper, we propose CommuNety, a deep learning system for the prediction of cohesive networks using face images from photo albums. The proposed deep learning model consists of hierarchical CNN architecture to learn descriptive features related to each cohesive network. The paper also proposes a novel Face Co-occurrence Frequency algorithm to quantify existence of people in images, and a novel photo ranking method to analyze the strength of relationship between different individuals in a predicted social network. We extensively evaluate the proposed technique on PIPA dataset and compare with state-of-the-art methods. Our experimental results demonstrate the superior performance of the proposed technique for the prediction of relationship between different individuals and the cohesiveness of communities.
