Using Social Media Analysis to Improve E-commerce Marketing Strategies

Olha Semenda, Yuliia Sokolova, Olena Korovina, Oleksandra Bratko, Iryna Polishchuk
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Abstract

This study investigates the application of game theory and matrix-based analysis in enhancing social media marketing strategies for e-commerce businesses. By integrating these mathematical models with social media analytics, aim to provide a comprehensive framework that can predict consumer behavior, optimize competitive strategies, and improve engagement on digital platforms. This study's application of a game theory matrix model on social media marketing strategies showcased clear benefits for e-commerce entities, with aggressive marketing tactics boosting market share by 30% against passive competitors and achieving a 20% increase even when competitors also adopted aggressive approaches. The Nash Equilibrium emphasize the balanced market share gains when both firms engaged in aggressive strategies. Statistical analysis reinforced the efficacy of these strategies, with a chi-square test yielding a significant value of 13.4, suggesting a strong link between aggressive marketing and enhanced engagement metrics. Regression analysis further validated the impact of engagement on sales, indicating that a 1% increase in likes, comments, and shares corresponded to a 0.75% uplift in sales, evidenced by significant predictors with β values of 0.25, 0.35, and 0.40 for likes, comments, and shares respectively. Content analysis and consumer surveys highlighted a preference for authentic, value-aligned content, with aggressive strategies leading to a 50% higher engagement rate and a 60% consumer preference for such content, emphasizing the critical role of strategic alignment with consumer expectations. Incorporating game theory and matrix-based analysis into e-commerce social media strategies offers a novel approach to understanding and leveraging the complex interplay of consumer interactions and competitive dynamics. This methodology enables marketers to devise more targeted, adaptive, and effective marketing campaigns, driving growth and enhancing consumer satisfaction in the competitive digital marketplace.
利用社交媒体分析改进电子商务营销策略
本研究探讨了博弈论和矩阵分析在加强电子商务企业社交媒体营销策略中的应用。通过将这些数学模型与社交媒体分析相结合,旨在提供一个能够预测消费者行为、优化竞争策略和提高数字平台参与度的综合框架。本研究将博弈论矩阵模型应用于社交媒体营销策略,为电子商务实体带来了明显的好处,积极的营销策略使市场份额在被动的竞争对手面前提高了 30%,即使在竞争对手也采取积极策略的情况下,市场份额也提高了 20%。纳什均衡强调了当两家公司都采取激进策略时市场份额的均衡增长。统计分析证实了这些策略的有效性,卡方检验得出的显著值为 13.4,表明积极营销与提高参与度指标之间存在紧密联系。回归分析进一步验证了参与度对销售额的影响,表明点赞、评论和分享每增加 1%,销售额就会增加 0.75%,点赞、评论和分享的 β 值分别为 0.25、0.35 和 0.40 的显著预测因子证明了这一点。内容分析和消费者调查强调了消费者对真实的、价值一致的内容的偏好,积极的战略使参与率提高了 50%,60% 的消费者偏好此类内容,这强调了战略与消费者期望相一致的关键作用。将博弈论和基于矩阵的分析纳入电子商务社交媒体战略,为理解和利用消费者互动和竞争动态的复杂相互作用提供了一种新方法。这种方法使营销人员能够设计出更具针对性、适应性和有效性的营销活动,在竞争激烈的数字市场中推动增长并提高消费者满意度。
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来源期刊
CiteScore
1.50
自引率
0.00%
发文量
21
审稿时长
12 weeks
期刊介绍: International Review of Management and Marketing (IRMM) is the international academic journal, and is a double-blind, peer-reviewed academic journal publishing high quality conceptual and measure development articles in the areas of management, marketing, business and related disciplines.
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