A recent study by Turkish AI firm Citelens has uncovered notable differences in the sources utilized by Google’s AI Overviews when addressing the same business-related inquiries in Turkish versus English. This discovery underscores the necessity for brands to develop language-specific AI visibility strategies. The research scrutinized 444 business questions posed in both languages, revealing that a mere 22% of the cited domains were common to both the Turkish and English AI responses. This suggests that brands recognized in one language may not necessarily achieve similar visibility when operating in another.
The study further discovered that AI Overviews were generated for 96% of English language queries, in comparison to 94% for those in Turkish. While the discrepancy in response generation was minimal, the AI systems showed significant variation in the sources selected, which largely depended on the language and the specific market context. This finding highlights the challenge businesses face when attempting to maintain visibility across different language platforms.
For businesses targeting the Turkish market, the research implies that relying solely on an English-language digital presence is insufficient. To secure visibility in Turkish AI results, it is increasingly crucial to focus on local content and leverage regional authority sources, alongside implementing language-specific optimization strategies. Such tactics are important as AI platforms continue to evolve in determining which information to recommend to users.
Citelens advises that brands should treat Generative Engine Optimization (GEO) as a distinct process for each language and market. For tracking AI visibility within the Turkish context, businesses should measure performance directly within Turkish search environments rather than relying on English results as a standard. As AI visibility becomes a more localized challenge, businesses must adopt tailored strategies to enhance their presence across different languages and regions.
The research employed a methodology that involved comparing AI-generated answers by using various country and language settings, and analyzing source domains from numerous queries. These findings highlight the increasing importance of developing bespoke strategies to address AI visibility challenges, emphasizing that businesses must adapt to the localized nature of AI platforms to thrive in diverse linguistic and regional markets.
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