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<p>Social commerce is rapidly gaining importance and fundamentally transforming how companies generate attention and influence purchasing decisions. Unlike traditional electronic commerce, purchase impulses do not arise through targeted product searches but through the automatic selection and display of content in users’ social media feeds. This selection is controlled by platform algorithms, whose inner workings remain largely opaque to companies. The central question, therefore, is how organizations can increase their visibility and effectively reach users despite this lack of transparency.</p><p>This article develops an&#xa0;Alogrithm-Stimulus Model (ASM) that illustrates how algorithms operate across the key stages of social commerce—from initial content visibility to user interaction, trust formation, purchase decisions, and long-term customer retention. Based on a&#xa0;systematic literature analysis and an expert survey, the study identifies the most relevant algorithmic drivers in each phase and outlines practical measures companies can use to positively influence algorithmic outcomes.</p><p>The findings show that well-targeted actions can significantly shape reach, engagement, and purchase impulses. The model provides companies with a&#xa0;clear, practice-oriented framework for designing effective social commerce strategies, particularly when resources are limited.</p>

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Erfolgreich verkaufen über Social Media

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月4日

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  • Dennis Jahnecke,
  • Manuel Kern,
  • Sven Dittes

摘要

Social commerce is rapidly gaining importance and fundamentally transforming how companies generate attention and influence purchasing decisions. Unlike traditional electronic commerce, purchase impulses do not arise through targeted product searches but through the automatic selection and display of content in users’ social media feeds. This selection is controlled by platform algorithms, whose inner workings remain largely opaque to companies. The central question, therefore, is how organizations can increase their visibility and effectively reach users despite this lack of transparency.

This article develops an Alogrithm-Stimulus Model (ASM) that illustrates how algorithms operate across the key stages of social commerce—from initial content visibility to user interaction, trust formation, purchase decisions, and long-term customer retention. Based on a systematic literature analysis and an expert survey, the study identifies the most relevant algorithmic drivers in each phase and outlines practical measures companies can use to positively influence algorithmic outcomes.

The findings show that well-targeted actions can significantly shape reach, engagement, and purchase impulses. The model provides companies with a clear, practice-oriented framework for designing effective social commerce strategies, particularly when resources are limited.