GEO Case for Great Health Brands | AI Recommendation Rate Increased from 3% to 60%, Top 3 Exposure on Mainstream Platforms
Challenge
Nowadays, the decision-making path for users to purchase health products and learn about health brands is gradually shifting from traditional search engines and e-commerce platforms to AI Q&A channels.When users consult about health brand recommendations, health product selection and other issues on platforms such as Doubao, DeepSeek and Tongyi Qianwen, the recommendation results output by AI will directly affect users' brand choices and consumption decisions.As a brand in the great health track, it has product advantages in offline and its own channels, but its brand exposure in mainstream AI Q&A scenarios is extremely low, making it difficult to reach precise users who actively search for health needs.
Solution
Building a Content Matrix on High-Authority Platforms Expand high-authority information and health vertical platforms that are frequently crawled by large language models, build a brand-exclusive content distribution matrix, increase the probability of brand content being indexed by LLMs, and make up for the shortage of original AI platform coverage. Optimization of Standardized Publishing Templates Optimize the content output template based on the logic of AI semantic retrieval, organize content in accordance with the structured logic of "user health questions - brand product answers", strengthen the weight of core tags such as brand product advantages and health value, and improve the accuracy of AI matching recommendations. Targeted Incremental Distribution on Channels Add multiple high-authority publishing channels, output professional brand content adapted to great health scenarios on a large scale, cover more sources of AI training corpus, and consolidate the foundation of the brand's content weight in the great health track.