Percorrer por autor "Commentz, Daniel Friedrich"
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- Bridging the AI adoption gap with Microsoft Copilot : a comparative experiment of AI-generated SEO textPublication . Commentz, Daniel Friedrich; König, MichaelSmall and medium-sized enterprises (SMEs) face persistent challenges in adopting artificial intelligence (AI) due to limited resources, technical know-how, and data privacy concerns. On the contrary, especially within the intersect of AI and search engine optimization (SEO), while the literature is still in an embryonic phase, existing research has already acknowledged the potential of large language models (LLMs) for SEO purposes. While most studies focus on freely accessible tools like ChatGPT, other enterprise-grade solutions like MS Copilot are mostly overlooked. To address this gap, this study evaluates whether Copilot-generated search engine optimized product texts can enhance product page performance across three dimensions: Algorithmic relevance (H1), user engagement (H2), and commercial impact (H3). For this purpose, a controlled online field experiment was conducted within a German SME in the beauty and healthcare sector. From a sample of 20 product pages, half of the product texts were exchanged with Copilot-generated content, while the other half served as a control group and tracked eight weeks before and after the intervention. While statistical significance remained limited, descriptive patterns cautiously indicate that Copilot-generated content may improve search visibility and, in isolated cases, positively affect sales outcomes. Importantly, no evidence was found that such AI-generated content harms visibility or user experience. In doing so, this study contributes to the emerging embryonic research of applied AI in the field of SEO, offering an explorative foundation for future research. Furthermore, it offers first practical hints for SME practitioners evaluating the integration of AI-driven tools like MS Copilot.