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        <datestamp>2026-09-28T06:38:29Z</datestamp>
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          <dc:title>GEO/AIO query-level observations: BMW, Mercedes-Benz and Audi across three generative platforms, August 2026</dc:title>
          <dc:creator>Alexandre Silva (25120476)</dc:creator>
          <dc:subject>Marketing technology</dc:subject>
          <dc:subject>generative engine optimization</dc:subject>
          <dc:subject>search engine optimization</dc:subject>
          <dc:subject>AI-driven search</dc:subject>
          <dc:subject>brand visibility</dc:subject>
          <dc:subject>digital marketing strategy</dc:subject>
          <dc:subject>citation authority</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;Master in Business Administration: Strategic Integration of Generative Engine Optimization with SEO to Maximize Brands' Digital Effectiveness: This dissertation investigates how brands can strategically integrate Artificial Intelligence Optimization (AIO) and Generative Engine Optimization (GEO) with established Search Engine Optimization (SEO) practices to protect and enhance their digital presence in an AI-driven search landscape. Positioned within marketing rather than technology, it focuses on how generative AI systems such as ChatGPT, Google Gemini and Perplexity are reshaping consumer discovery, brand visibility and competitive dynamics, and asks three core questions: which strategies best integrate SEO and GEO, how brands can build citation authority within AI-generated responses, and what hybrid content approaches can simultaneously satisfy traditional ranking criteria and new generative engine demands. Methodologically, the research adopts an exploratory multiple case study design of three directly competing premium automotive brands, BMW, Mercedes-Benz and Audi, examined through their international flagship websites (bmw.com, mercedes-benz.com, audi.com) across three complementary dimensions: a comparative SEO audit, a systematic GEO visibility assessment on three leading AI platforms using a scientifically grounded eighteen-query framework, and a seven-criterion GEO-readiness content and structure analysis, supported by within-case and cross-case synthesis and framework development. The findings show that off-site brand authority signals (such as branded web mentions and external media coverage) remain the primary drivers of visibility in AI-generated results, while on-site GEO-readiness (conversational content, schema, E-E-A-T) functions as a necessary but insufficient condition, creating a “GEO-readiness paradox” in which Audi’s superior content architecture does not translate into superior AI visibility. On this basis, the dissertation proposes a dual-layer marketing framework that distinguishes an authority foundation, built through public relations and brand equity investments, from a citability infrastructure, built through AI-oriented content and structural optimization, and derives brand-specific strategic roadmaps that illustrate how marketers can orchestrate SEO, GEO and AIO as an integrated system to sustain brand salience and preference in AI-mediated customer journeys.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-28T06:38:29Z</dc:date>
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          <dc:rights>CC BY 4.0</dc:rights>
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