Generative Engine Optimisation (GEO) and AI Search Visibility in Digital Media: A Case Study of RTV Bangladesh

Abstract

RTV is one of Bangladesh's most-followed multi-platform media brands, with a combined social media following in the tens of millions across Facebook, YouTube, and emerging platforms such as TikTok and LinkedIn. As global information-seeking behaviour shifts away from clicking links and toward receiving direct answers from generative artificial intelligence (AI) systems such as ChatGPT, Gemini, and Google's AI Overview, RTV has begun adapting its digital content strategy from conventional Search Engine Optimisation (SEO) toward the emerging discipline of Generative Engine Optimisation (GEO). Drawing on an interview with Md Ariful Islam, Manager of Digital and Social Media at RTV, this case study documents how the organisation first noticed declining Google search volume for evergreen keywords, began restructuring titles and meta descriptions for machine readability, and sought to position RTV as a citable, authentic reference within AI-generated answers. The case is analysed through Rogers' (2003) Diffusion of Innovation Theory, using the innovation-decision process and the five perceived attributes of an innovation to explain why RTV has adopted some GEO practices quickly, while others remain underdeveloped. The case offers a grounded, practitioner-level and theory-informed account of how a legacy broadcaster in an emerging South Asian market is navigating the transition from a link-based to an answer-based information economy, and closes with discussion questions suited to postgraduate marketing and media management courses.