How AI Chatbots Drive Web Traffic to Academic Journals: A Web Analytics Perspective

What is it about?

This paper examines the role of generative AI chatbots in driving web traffic to academic journals. Using web analytics data from the RACO journal portal, it assesses how chatbots like ChatGPT, Perplexity, and Gemini contribute to referral traffic. The study explores factors limiting chatbot-driven visits, discusses strategies like Generative Engine Optimization (GEO), and raises questions about the future of academic journal visibility.

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Photo by Niko Vassios on Unsplash

Photo by Niko Vassios on Unsplash

Why is it important?

It sheds light on how generative AI chatbots, such as ChatGPT and Perplexity, influence academic journal visibility and web traffic. As AI-driven search tools reshape how users access information, understanding their impact on scholarly content is crucial. The study highlights the low referral traffic from chatbots, raising concerns about the discoverability of open-access research. It also introduces Generative Engine Optimization (GEO) as a potential strategy to adapt to AI-driven search environments, complementing traditional SEO and Academic Search Engine Optimization (ASEO). By addressing these issues, the paper contributes to ongoing discussions on how academic publishers can navigate the evolving digital landscape and ensure sustained visibility in AI-powered search ecosystems.