This study uses a fuzzy analytical technique to give a thorough evaluation of how well social media platforms reach various customer segments. Initially the classification of consumers into five groups according to their job status: employed in the private sector, employed in the public sector, homemakers who are unemployed, self-employed/entrepreneurs, and students. Each section has a unique weight that reflects its relative importance during the review process. After that, using a fuzzy scale to capture the range of replies, a decision matrix is generated. By using the Fuzzy TOPSIS approach, calculate a proximity coefficient and rank the social media platforms according to how well they can reach different consumer segments.
TopIntroduction
In the contemporary landscape of marketing and consumer engagement, social media platforms have emerged as formidable tools for connecting with diverse audiences. These platforms have revolutionized the way businesses communicate, market their products, and build relationships with consumers. As consumers increasingly turn to social media for information, entertainment, and social interaction, it has become essential for organizations to not only maintain a presence but also to strategically tailor their approach to suit various consumer segments.
The proliferation of social media platforms offers marketers an array of choices, each with its unique features, strengths, and limitations. However, the effectiveness of these platforms varies considerably depending on the nature of the target audience. Engaging with a heterogeneous consumer base, characterised by distinct demographics, behaviours, and preferences, demands a nuanced and data-driven approach.
Social commerce is the term used to describe the growing use of social networking sites (SNSs) like Facebook for business purposes. Using Facebook's group function is one way to carry out these commercial activities. Since these activities will probably involve one user acting as a seller and another user acting as a consumer, the group is thought to be carrying out consumer-to-consumer (C2C) commercial activities (Abaid Ullah Zafar 2021). The lack of research on reliable and efficient methods for assessing the security and reliability of different social media tools, platforms, and applications has an impact on how these tools and applications continue to develop and improve (Zhiyong Zhang 2018). Businesses can gain insight into consumer preferences and needs through social media data analysis. This can lead to better customer service, social network marketing analytics, and more informed decisions about product development and marketing (Honglei Zhang 2022). An AI-based social media marketing tool must be able to deliver on its promises of performance in order to be considered successful (Alexandru Capatina 2020).
This research endeavours to address this critical issue by introducing a comprehensive assessment framework that leverages the power of fuzzy analysis to evaluate the effectiveness of social media platforms across varied consumer segments. Fuzzy analysis provides a valuable mechanism for handling imprecise and uncertain data, which is inherent in the domain of consumer behaviour and social media engagement. It allows for a more nuanced evaluation that accounts for the multifaceted nature of consumer preferences and platform dynamics.
To achieve this objective, we begin by delineating five distinct consumer segments based on their employment status: Employed - Private, Employed - Govt Sector, Homemaker / Unemployed, Self-employed/ Entrepreneur, and Student. These segments encompass a broad spectrum of demographics and behaviours, and as such, necessitate a tailored approach to social media engagement.
The research methodology involves the creation of a decision matrix that captures the preferences and responses of each consumer segment toward various social media platforms. This matrix is further processed using a fuzzy scale to accommodate the inherent vagueness and uncertainty in consumer preferences. The subsequent steps involve the normalization of data, the derivation of weighted normalized matrices, and the calculation of distances from ideal solutions, all within the framework of fuzzy analysis.
By applying the Fuzzy TOPSIS method, we ascertain a closeness coefficient and establish a ranking system for social media platforms. This ranking offers invaluable insights into which platforms are most effective in reaching specific consumer segments. Such insights are poised to empower marketers and businesses to refine their social media strategies, tailor content, and optimize engagement efforts based on the distinct characteristics and preferences of their target audiences.