NARS Cosmetics
NARS
NARS Cosmetics is the makeup artist brand founded by François Nars, famous for its Orgasm blush, Radiant Creamy Concealer, and bold color philosophy. The brand has built a dedicated Chinese following, particularly strong on Xiaohongshu where beauty enthusiasts share NARS color stories. Despite genuine brand love, NARS scores zero across all six Chinese AI models. The zero GEO score reflects a familiar pattern: makeup brands that live primarily in social media visual content struggle to generate AI-indexable authority. NARS's strongest China presence is on Xiaohongshu and Douyin — platforms where visual makeup tutorials, shade comparisons, and application videos dominate. This content, while driving strong social engagement, generates less text-based training data for AI models compared to skincare brands whose products are discussed in more analytical, text-rich formats. The brand also faces a category challenge. Color cosmetics recommendations in Chinese AI are dominated by either luxury fashion-house brands (Chanel Beauty, Dior Beauty) or affordable mass-market staples. NARS occupies a mid-premium makeup artist tier that doesn't appear prominently as a default AI recommendation in either direction. To improve its China GEO position, NARS should invest in Mandarin text content that builds category authority: "best foundations for Chinese skin tones," "makeup artist techniques for Asian eye shapes," and "professional quality vs. department store brands" comparisons. This analytical content would generate AI citations that NARS's current visual-only strategy cannot produce.
最近更新:2026年6月4日
豆包 (Doubao)
字节跳动旗下 AI 模型,中国月活最高
低能见度 — 较少被该模型主动提及
Kimi
月之暗面,以长上下文和搜索能力著称
低能见度 — 较少被该模型主动提及
DeepSeek
深度求索,开源模型代表,全球关注度极高
低能见度 — 较少被该模型主动提及
通义千问 (Qwen)
阿里巴巴旗下 AI 模型,深度整合电商生态
低能见度 — 较少被该模型主动提及
文心一言 (Wenxin)
百度旗下 AI 模型,搜索入口级流量背书
低能见度 — 较少被该模型主动提及
混元 (Hunyuan)
腾讯自研 AI 模型,深度整合微信、QQ、元宝生态
低能见度 — 较少被该模型主动提及
📊 分数解读
60–100
高能见度
该 AI 模型在对应品类查询中频繁主动提及此品牌
35–59
中等能见度
该 AI 模型偶尔提及,通常出现在竞争较大的品类中
0–34
低能见度
该 AI 模型较少在相关品类推荐中提到此品牌
每个分数基于每月多轮标准化查询的统计结果。我们向每个 AI 模型询问 “美妆行业值得关注的品牌有哪些?” 等标准问题, 记录该品牌被主动提及的频率,转化为 0–100 分数。