社会化媒体营销策略的有效性:来自促销活动的证据

Panagiotis Adamopoulos, Vilma Todri
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引用次数: 26

摘要

本文研究了一个新颖的社交媒体企业,并试图通过评估其对参与品牌和组织的影响来了解社交媒体平台营销策略的有效性。我们使用真实世界的数据集,并采用一种有前途的研究方法,将计量经济学与预测建模技术结合在因果估计框架中,允许更准确的反事实。基于所提出的分析结果,并关注社交媒体营销策略的长期商业价值,我们发现,在社交媒体平台上利用隐性或显性倡导的促销活动,在扩大公司的社交媒体粉丝基础方面,会给参与品牌带来显著的异常回报。这种效应在经济上也很重要,因为对于一个中等规模的品牌来说,它相当于每天增加数千名新粉丝。我们还精确量化了各种促销特征的影响,并展示了哪种类型的促销更有效,针对哪些品牌,同时提出了具体的战术策略。例如,尽管消费者的注意力存在竞争,但品牌和营销人员应该在使用高峰期在社交网络上播放营销信息,以获得最大的回报。总体而言,我们为公司和社交媒体平台提供具有重大意义的可操作见解,并为相关文献做出贡献,因为我们发现了由所采用的因果估计框架实现的新的丰富发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Effectiveness of Marketing Strategies in Social Media: Evidence from Promotional Events
This paper studies a novel social media venture and seeks to understand the effectiveness of marketing strategies in social media platforms by evaluating their impact on participating brands and organizations. We use a real-world data set and employ a promising research approach combining econometric with predictive modeling techniques in a causal estimation framework that allows for more accurate counterfactuals. Based on the results of the presented analysis and focusing on the long-term business value of marketing strategies in social media, we find that promotional events leveraging implicit or explicit advocacy in social media platforms result in significant abnormal returns for the participating brand, in terms of expanding the social media fan base of the firm. The effect is also economically significant as it corresponds to an increase of several thousand additional new followers per day for an average size brand. We also precisely quantify the impact of various promotion characteristics and demonstrate what types of promotions are more effective and for which brands, while suggesting specific tactical strategies. For instance, despite the competition for consumers' attention, brands and marketers should broadcast marketing messages on social networks during the time of peak usage in order to maximize their returns. Overall, we provide actionable insights with major implications for firms and social media platforms and contribute to the related literature as we discover new rich findings enabled by the employed causal estimation framework.
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