Great Health Brand GEO Optimization Case | Practical Review: Brand Mention Rate on AI Platforms Increased from 16% to 60%
Challenge
The client is a well-known great health brand in China, focusing on health food products, with formal direct selling business qualifications and a complete brand qualification system. As users in the health consumption field shift their information acquisition habits to AI Q&A platforms, decision-making links such as brand research and horizontal comparison are increasingly completed through AI. However, the brand has a weak overall voice in AI search scenarios and is completely absent in core high-frequency scenarios, failing to effectively undertake natural traffic from AI terminals. Core Challenges： 1.Brand silence in core search scenarios: In high-frequency user search scenarios such as "great health brand recommendation" and "inventory of formal direct selling enterprises", the brand has a 0% mention rate on mainstream AI platforms such as Doubao and DeepSeek. It has never been included in the platform recommendation list, resulting in a complete lack of AI natural traffic channels. 2.Insufficient structured content supply: There is a lack of systematic structured content such as product introduction, qualification certification and brand strength across the network. Large models have no valid materials to retrieve. When users compare health category brands horizontally, the brand will be directly ignored and cannot enter the user's decision-making alternative pool.
Solution
1.Build a vertical category keyword matrix: Build a keyword matrix around the three core directions of great health, health food and formal direct selling, adapt to the semantic search logic of large models, broaden the brand's search access channels in AI scenarios, and cover the entire decision-making chain from category cognition to brand screening. 2.Supplement authoritative structured Q&A materials: Sort out authoritative content in dimensions such as brand qualifications, product information and enterprise strength, output them as structured Q&A materials that can be directly captured and cited by large models, supplement the information sources of large models, and solve the core problem that AI has no valid information to recommend.