Beyond impressions: A multi-platform analysis of social media advertising effectiveness in driving sales and engagement
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https://doi.org/10.71350/30624533122Keywords:
Social media advertising, advertising effectiveness, platform differentiation, engagement metrics, sales conversion, algorithmic fatigueAbstract
Navigating the multibillion-dollar environment of social media advertising (SMA) is a constant struggle. Despite projections that worldwide expenditure would exceed $600 billion by 2025, adequately evaluating the genuine effect on concrete sales and meaningful involvement remains challenging and contentious. This study tackles this complexity directly by systematically assessing the differential success of SMA across prominent platforms—Meta, TikTok, X, and LinkedIn—in terms of tangible sales and various engagement indicators, while taking crucial moderating variables into account. The research employs a strong multi-method approach, combining large-scale longitudinal analysis of over 500 sponsored ads over 12 months, a thorough consumer survey (n=1,200) monitoring attitudinal alterations and behavioral intentions, and an experimental vignette study to determine causal linkages. Results demonstrate significant platform differences: TikTok succeeds in terms of engagement and lower-funnel conversions, particularly among Gen Z users, but LinkedIn thrives in generating high-value B2B prospects. Importantly, creative authenticity typically beats more polished commercials in terms of engagement, while targeted, value-driven call-to-actions (CTAs) are the most successful at generating sales. The report also identifies algorithmic fatigue as a significant negative factor influencing engagement and conversion across platforms. This study provides extensive, practical data for marketers seeking to maximize large SMA expenditures. It offers a data-driven framework for effectively allocating expenditures and tailoring creative tactics depending on campaign objectives—whether to increase brand engagement, boost sales, or produce qualified leads—as well as the individual characteristics of the target demographic. Overall, it advances from general best practices to precision marketing in the age of algorithms.
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