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Brand Mention Scanner Skill

品牌提及扫描工具

Core Insight

核心洞察

Brand mentions correlate approximately 3x more strongly with AI visibility than traditional backlinks. An Ahrefs study published in December 2025, analyzing 75,000 brands across AI search platforms, found that unlinked brand mentions -- references to a brand name without a hyperlink -- are a stronger predictor of whether AI systems cite and recommend a brand than Domain Rating or backlink count.
The critical finding: the platform where the mention appears matters enormously. Not all mentions are equal. A mention on YouTube or Reddit carries far more weight for AI citation than a mention on a low-authority blog, because AI training data and retrieval systems disproportionately index high-engagement platforms.
This inverts a core assumption of traditional SEO. In traditional SEO, a backlink from a high-DR site is the gold standard. In GEO, an unlinked mention on Reddit or a YouTube video description may be more valuable than a dofollow backlink from a DR 70 blog.
品牌提及与AI可见性的相关性约为传统反向链接的3倍。Ahrefs在2025年12月发布的一项研究中，分析了AI搜索平台上的75000个品牌，发现无链接品牌提及——即不带超链接的品牌名称引用——比域名评级（Domain Rating）或反向链接数量更能预测AI系统是否会引用并推荐该品牌。
关键发现：品牌提及所在的平台至关重要。并非所有提及的价值都相同。YouTube或Reddit上的提及对AI引用的权重远高于低权威博客上的提及，因为AI训练数据和检索系统会优先索引高互动性平台。
这颠覆了传统SEO的核心假设。在传统SEO中，来自高DR（Domain Rating）网站的反向链接是黄金标准。而在GEO（AI可见性优化）中，Reddit或YouTube视频描述中的无链接提及可能比来自DR70博客的dofollow反向链接更有价值。

Platform Importance Ranking for AI Citations

AI引用的平台重要性排名

Based on the Ahrefs December 2025 study and corroborating research from Profound (2025) and Terakeet (2025):
基于Ahrefs 2025年12月的研究，以及Profound（2025）和Terakeet（2025）的佐证研究：

1. YouTube Mentions -- Correlation ~0.737 (STRONGEST)

1. YouTube提及 — 相关性~0.737（最强）

Why YouTube matters most:
  • YouTube is the second-largest search engine and the largest video platform globally (2.5B+ monthly users).
  • AI training datasets heavily incorporate YouTube transcripts, descriptions, and metadata.
  • Google's Gemini and AI Overviews directly reference YouTube content.
  • Perplexity and ChatGPT both index and cite YouTube video content.
  • YouTube transcripts are particularly valuable because they contain natural language mentions in conversational context, which aligns with how AI models process and generate text.
What to check:
  • Brand YouTube channel: Does the brand have an active YouTube channel? How many subscribers? Video count? Upload frequency?
  • Third-party video mentions: Are other YouTubers or channels mentioning the brand? In what context (reviews, tutorials, comparisons)?
  • Video descriptions: Does the brand name appear in video descriptions of industry-relevant content?
  • Video transcripts: Is the brand mentioned in spoken content of relevant videos? (AI models index transcripts)
  • YouTube search presence: When searching "[brand name]" on YouTube, do results appear? Are they positive?
  • Comment mentions: Is the brand mentioned in comments on relevant industry videos?
Scoring for YouTube (0-100):
ScoreCriteria
90-100Active channel with 10K+ subscribers, regular uploads, brand mentioned in 20+ third-party videos, appears in YouTube search results for industry terms
70-89Active channel with 1K+ subscribers, brand mentioned in 10-19 third-party videos, some YouTube search presence
50-69Channel exists with some content, brand mentioned in 5-9 third-party videos, limited YouTube search presence
30-49Channel exists but inactive, brand mentioned in 1-4 third-party videos
10-29No channel or empty channel, brand mentioned in 1-2 videos only
0-9No YouTube presence whatsoever
YouTube为何最重要：
  • YouTube是全球第二大搜索引擎和最大的视频平台（月活跃用户超25亿）。
  • AI训练数据集大量整合了YouTube的字幕、描述和元数据。
  • Google的Gemini和AI概览会直接引用YouTube内容。
  • Perplexity和ChatGPT都会索引并引用YouTube视频内容。
  • YouTube字幕的价值尤其突出，因为它们包含对话语境中的自然语言提及，与AI模型处理和生成文本的方式一致。
需要检查的内容：
  • 品牌YouTube频道： 品牌是否有活跃的YouTube频道？订阅数多少？视频数量？上传频率？
  • 第三方视频提及： 其他YouTuber或频道是否提及该品牌？提及语境是什么（评测、教程、对比）？
  • 视频描述： 品牌名称是否出现在行业相关内容的视频描述中？
  • 视频字幕： 相关视频的口语内容中是否提及品牌？（AI模型会索引字幕）
  • YouTube搜索曝光： 在YouTube上搜索“[品牌名称]”时，是否有结果？结果是否正面？
  • 评论提及： 相关行业视频的评论中是否提及该品牌？
YouTube评分标准（0-100）：
分数评判标准
90-100活跃频道，订阅数1万+，定期更新，20+第三方视频提及品牌，在行业术语的YouTube搜索结果中出现
70-89活跃频道，订阅数1千+，10-19个第三方视频提及品牌，有一定YouTube搜索曝光
50-69频道存在且有部分内容，5-9个第三方视频提及品牌，YouTube搜索曝光有限
30-49频道存在但不活跃，1-4个第三方视频提及品牌
10-29无频道或频道为空，仅1-2个视频提及品牌
0-9完全无YouTube曝光

2. Reddit Mentions -- High Correlation

2. Reddit提及 — 高相关性

Why Reddit matters:
  • Reddit is one of the most heavily indexed platforms in AI training data (confirmed in Google's $60M/year Reddit licensing deal, 2024).
  • AI systems heavily weight Reddit for product recommendations, comparisons, and user sentiment.
  • "Reddit" is now appended to an estimated 10-15% of Google searches by users seeking authentic opinions.
  • Perplexity frequently cites Reddit threads as sources.
  • ChatGPT and Claude both reference Reddit discussions when answering product/service questions.
What to check:
  • Subreddit presence: Is the brand discussed in relevant subreddits? Which ones?
  • Mention volume: How many Reddit threads mention the brand? What is the trend (increasing/decreasing)?
  • Sentiment: Are mentions mostly positive, negative, or neutral? What are common praise points and complaints?
  • Official presence: Does the brand have an official Reddit account? Do they participate in discussions? Have they done AMAs?
  • Recommendation threads: Does the brand appear in "What do you recommend for X?" threads? Is it the top recommendation or an also-ran?
  • Subreddit community: Does the brand have its own subreddit? How active is it?
Scoring for Reddit (0-100):
ScoreCriteria
90-100Frequently recommended in relevant subreddits, predominantly positive sentiment, active official presence, own subreddit with 5K+ members, appears in top recommendations for industry queries
70-89Regularly mentioned in relevant subreddits, mostly positive sentiment, some official presence, appears in multiple recommendation threads
50-69Mentioned in several relevant threads, mixed sentiment, brand name is recognized by community members
30-49Occasional mentions, limited to 1-2 subreddits, no official presence
10-29Rare mentions, brand largely unknown on Reddit
0-9No Reddit presence
Reddit为何重要：
  • Reddit是AI训练数据中被索引最多的平台之一（已被Google 2024年6000万美元的Reddit授权协议证实）。
  • AI系统在产品推荐、对比和用户情感分析中高度依赖Reddit。
  • 估计有10-15%的Google搜索会附加“Reddit”，用户以此寻求真实意见。
  • Perplexity经常引用Reddit帖子作为来源。
  • ChatGPT和Claude在回答产品/服务问题时都会参考Reddit讨论内容。
需要检查的内容：
  • Subreddit曝光： 品牌是否在相关Subreddit中被讨论？具体是哪些？
  • 提及量： 有多少Reddit帖子提及该品牌？趋势如何（增长/下降）？
  • 情感倾向： 提及以正面、负面还是中性为主？常见的赞扬点和投诉点是什么？
  • 官方账号： 品牌是否有官方Reddit账号？是否参与讨论？是否举办过AMA（Ask Me Anything）？
  • 推荐帖子： 品牌是否出现在“X产品有什么推荐？”类帖子中？是首推还是备选？
  • 专属Subreddit： 品牌是否有自己的Subreddit？活跃度如何？
Reddit评分标准（0-100）：
分数评判标准
90-100在相关Subreddit中常被推荐，以正面情感为主，有活跃的官方账号，拥有5千+成员的专属Subreddit，在行业查询的首推结果中出现
70-89在相关Subreddit中被定期提及，以正面情感为主，有一定官方账号活跃度，在多个推荐帖子中出现
50-69在多个相关帖子中被提及，情感混合，社区成员知晓该品牌
30-49偶尔被提及，仅在1-2个Subreddit中出现，无官方账号
10-29极少被提及，Reddit用户基本不了解该品牌
0-9完全无Reddit曝光

3. Wikipedia Presence -- High Correlation

3. Wikipedia存在 — 高相关性

Why Wikipedia matters:
  • Wikipedia is one of the highest-authority sources in AI training data. All major AI models have been trained on Wikipedia dumps.
  • AI systems use Wikipedia as a primary source for entity recognition -- determining whether a brand is a "real" entity worth knowing about.
  • Wikidata (Wikipedia's structured data sibling) provides machine-readable facts that AI models use for knowledge graph construction.
  • Having a Wikipedia page is a strong signal of notability, which correlates with AI systems treating the brand as an authoritative entity.
What to check:
  • Wikipedia page: Does the brand or company have its own Wikipedia article? Is it marked for deletion or quality issues?
  • Founder page: Does the founder/CEO have a Wikipedia page? (Strong authority signal)
  • Wikipedia citations: Is the brand's website cited as a reference in any Wikipedia articles?
  • Wikidata entry: Does the brand have a Wikidata item (Q-number)? How complete is it?
  • Wikipedia mentions: Is the brand mentioned in other Wikipedia articles (industry articles, competitor pages, category pages)?
  • Article quality: If a Wikipedia page exists, is it a stub, start-class, or higher quality?
Scoring for Wikipedia (0-100):
ScoreCriteria
90-100Detailed Wikipedia article (B-class or higher), Wikidata entry with complete properties, brand cited as reference in multiple articles, founder has Wikipedia page
70-89Wikipedia article exists (start-class or higher), Wikidata entry exists, brand mentioned in 2+ other Wikipedia articles
50-69Wikipedia article exists (stub or start), basic Wikidata entry, limited mentions in other articles
30-49No Wikipedia article but brand is mentioned in other articles or cited as reference; Wikidata entry may exist
10-29Brand mentioned in 1-2 Wikipedia articles as a passing reference only
0-9No Wikipedia or Wikidata presence of any kind
Wikipedia为何重要：
  • Wikipedia是AI训练数据中权威度最高的来源之一。所有主流AI模型都接受过Wikipedia数据 Dump的训练。
  • AI系统将Wikipedia作为实体识别的主要来源——判断品牌是否是值得关注的“真实”实体。
  • Wikidata（Wikipedia的结构化数据姊妹项目）提供机器可读的事实，AI模型用于构建知识图谱。
  • 拥有Wikipedia页面是品牌显著性的强烈信号，与AI系统将品牌视为权威实体的倾向高度相关。
需要检查的内容：
  • Wikipedia页面： 品牌或公司是否有自己的Wikipedia条目？是否被标记为待删除或存在质量问题？
  • 创始人页面： 创始人/CEO是否有Wikipedia页面？（强烈的权威信号）
  • Wikipedia引用： 品牌官网是否被作为参考资料引用在任何Wikipedia条目中？
  • Wikidata条目： 品牌是否有Wikidata条目（Q编号）？条目完整性如何？
  • Wikipedia提及： 品牌是否在其他Wikipedia条目（行业条目、竞品页面、分类页面）中被提及？
  • 条目质量： 若存在Wikipedia页面，是 stub、start-class还是更高质量？
Wikipedia评分标准（0-100）：
分数评判标准
90-100详细的Wikipedia条目（B类或更高），属性完整的Wikidata条目，品牌被多篇条目引用为参考资料，创始人有Wikipedia页面
70-89存在Wikipedia条目（start-class或更高），有Wikidata条目，品牌在2+其他Wikipedia条目中被提及
50-69存在Wikipedia条目（stub或start-class），基础Wikidata条目，在其他条目中提及有限
30-49无Wikipedia条目，但品牌在其他条目中被提及或引用；可能存在Wikidata条目
10-29品牌仅在1-2个Wikipedia条目中被一笔带过
0-9完全无Wikipedia或Wikidata曝光

4. LinkedIn Presence -- Moderate Correlation

4. LinkedIn存在 — 中等相关性

Why LinkedIn matters:
  • LinkedIn content is increasingly indexed by AI systems for professional and B2B context.
  • Company LinkedIn pages and employee thought leadership posts build brand entity signals.
  • AI models reference LinkedIn for company information, team credentials, and professional authority.
  • LinkedIn articles and posts are indexed by search engines and AI crawlers.
What to check:
  • Company page: Does the brand have a LinkedIn company page? Follower count? Post frequency?
  • Employee thought leadership: Are employees (especially leadership) posting thought leadership content that mentions the brand?
  • Company mentions: Is the brand mentioned in LinkedIn posts by non-employees? Industry analysts? Customers?
  • LinkedIn articles: Are there long-form LinkedIn articles about or mentioning the brand?
  • Employee profiles: Do employees list the company with detailed descriptions? Do they have strong professional profiles?
  • Engagement metrics: What is the typical engagement (likes, comments, shares) on company posts?
Scoring for LinkedIn (0-100):
ScoreCriteria
90-100Active company page with 10K+ followers, leadership regularly posts thought leadership, brand frequently mentioned by industry professionals, strong employee profiles
70-89Active company page with 5K+ followers, some employee thought leadership, occasional third-party mentions
50-69Company page exists with 1K+ followers, irregular posting, limited third-party mentions
30-49Company page exists but is sparse or inactive, few followers, no third-party mentions
10-29Basic company page with minimal information
0-9No LinkedIn company page
LinkedIn为何重要：
  • LinkedIn内容正越来越多地被AI系统索引，用于专业和B2B场景。
  • 公司LinkedIn主页和员工的思想领导力帖子能强化品牌实体信号。
  • AI模型参考LinkedIn获取公司信息、团队资质和专业权威度。
  • LinkedIn文章和帖子会被搜索引擎和AI爬虫索引。
需要检查的内容：
  • 公司主页： 品牌是否有LinkedIn公司主页？粉丝数？发帖频率？
  • 员工思想领导力： 员工（尤其是管理层）是否发布提及品牌的思想领导力内容？
  • 第三方提及： 非员工、行业分析师、客户是否在LinkedIn帖子中提及该品牌？
  • LinkedIn文章： 是否有关于或提及品牌的长文LinkedIn文章？
  • 员工档案： 员工是否在档案中详细列出公司信息？是否有优质的专业档案？
  • 互动指标： 公司帖子的典型互动量（点赞、评论、分享）是多少？
LinkedIn评分标准（0-100）：
分数评判标准
90-100活跃的公司主页，粉丝1万+，管理层定期发布思想领导力内容，品牌常被行业专业人士提及，员工档案优质
70-89活跃的公司主页，粉丝5千+，有部分员工思想领导力内容，偶尔有第三方提及
50-69存在公司主页，粉丝1千+，发帖不规律，第三方提及有限
30-49存在公司主页但内容稀疏或不活跃，粉丝少，无第三方提及
10-29基础公司主页，信息极少
0-9完全无LinkedIn公司主页

5. Other Platform Presence -- Supplementary

5. 其他平台存在 — 补充性

These platforms have lower but still meaningful correlation with AI visibility:
这些平台与AI可见性的相关性较低，但仍有一定意义：

Quora

Quora

  • Relevance: Quora answers are frequently included in AI training data and cited by Perplexity.
  • What to check: Is the brand mentioned in Quora answers to industry-relevant questions? Does the brand have an official Quora presence?
  • Signal strength: Moderate for B2C, lower for B2B.
  • 相关性： Quora回答常被纳入AI训练数据，且被Perplexity引用。
  • 检查内容： 品牌是否在Quora的行业相关问题回答中被提及？品牌是否有官方Quora账号？
  • 信号强度： B2C场景中等，B2B场景较低。

Stack Overflow / Stack Exchange

Stack Overflow / Stack Exchange

  • Relevance: Critical for developer-facing brands (SaaS, dev tools, APIs).
  • What to check: Is the brand's product discussed in Stack Overflow questions/answers? Does the brand have a tag? Do they have an official account answering questions?
  • Signal strength: High for technical products, irrelevant for most B2C.
  • 相关性： 对面向开发者的品牌（SaaS、开发工具、API）至关重要。
  • 检查内容： 品牌产品是否在Stack Overflow的问题/回答中被讨论？是否有专属标签？是否有官方账号解答问题？
  • 信号强度： 对技术产品高，对多数B2C品牌无关。

GitHub

GitHub

  • Relevance: Critical for open-source and developer-focused brands.
  • What to check: Does the brand have a GitHub organization? Stars on repositories? Mentions in other repos' documentation or discussions?
  • Signal strength: High for dev tools and open-source, low for non-technical brands.
  • 相关性： 对开源和面向开发者的品牌至关重要。
  • 检查内容： 品牌是否有GitHub组织？仓库星数？是否在其他仓库的文档或讨论中被提及？
  • 信号强度： 对开发工具和开源品牌高，对非技术品牌低。

Industry Forums and Communities

行业论坛与社区

  • Relevance: Niche authority signals that AI models pick up from domain-specific training data.
  • What to check: Is the brand discussed in industry-specific forums (e.g., Hacker News for tech, ProductHunt for startups, industry-specific Slack communities)?
  • Signal strength: Moderate, but valuable for establishing niche authority.
  • 相关性： 利基权威信号，AI模型会从特定领域的训练数据中捕捉到。
  • 检查内容： 品牌是否在行业专属论坛中被讨论（如科技领域的Hacker News、初创公司领域的ProductHunt、行业专属Slack社区）？
  • 信号强度： 中等，但对建立利基权威有价值。

News and Press

新闻与媒体

  • Relevance: News mentions build entity authority and recency signals.
  • What to check: Has the brand been covered by major news outlets or industry publications? How recently? What was the context?
  • Signal strength: Moderate. Recency matters -- a mention in the last 6 months is far more valuable than one from 3 years ago.
  • 相关性： 新闻提及能强化实体权威度和时效性信号。
  • 检查内容： 品牌是否被主流媒体或行业刊物报道？报道时间？报道语境？
  • 信号强度： 中等。时效性很重要——近6个月的提及比3年前的提及价值高得多。

Podcasts

播客

  • Relevance: Growing AI training data source. Transcripts are increasingly indexed.
  • What to check: Has the brand or its leadership appeared on podcasts? Are podcast transcripts mentioning the brand indexed by search engines?
  • Signal strength: Moderate and growing.
  • 相关性： 日益增长的AI训练数据来源，字幕正被越来越多地索引。
  • 检查内容： 品牌或其管理层是否出现在播客中？提及品牌的播客字幕是否被搜索引擎索引？
  • 信号强度： 中等且持续增长。

Composite Brand Authority Score

综合品牌权威度评分

Scoring Formula

评分公式

PlatformWeightRationale
YouTube Presence25%Strongest correlation with AI citation (0.737)
Reddit Presence25%Second strongest correlation; critical for product recommendations
Wikipedia / Wikidata20%Entity recognition foundation; AI training data cornerstone
LinkedIn Authority15%Professional authority signals; B2B relevance
Other Platforms15%Supplementary signals from Quora, GitHub, news, forums, podcasts
Formula:
Brand_Authority_Score = (YouTube * 0.25) + (Reddit * 0.25) + (Wikipedia * 0.20) + (LinkedIn * 0.15) + (Other * 0.15)
平台权重依据
YouTube曝光25%与AI引用的相关性最强（0.737）
Reddit曝光25%相关性第二高；对产品推荐至关重要
Wikipedia / Wikidata20%实体识别的基础；AI训练数据的核心
LinkedIn权威度15%专业权威信号；B2B场景相关
其他平台15%来自Quora、GitHub、新闻、论坛、播客的补充信号
公式：
Brand_Authority_Score = (YouTube * 0.25) + (Reddit * 0.25) + (Wikipedia * 0.20) + (LinkedIn * 0.15) + (Other * 0.15)

Score Interpretation

分数解读

Score RangeRatingInterpretation
85-100DominantBrand is a well-recognized entity across AI platforms. Highly likely to be cited and recommended by AI systems.
70-84StrongBrand has solid cross-platform presence. AI systems likely recognize and cite it for relevant queries.
50-69ModerateBrand has presence on some platforms but gaps exist. AI citation is inconsistent.
30-49WeakBrand has limited platform presence. AI systems may not recognize it as a distinct entity.
0-29MinimalBrand has negligible platform presence. AI systems are unlikely to cite or recommend it.
分数区间评级解读
85-100主导级品牌在各AI平台均为知名实体，极有可能被AI系统引用和推荐
70-84强劲级品牌拥有扎实的跨平台曝光，AI系统可能会在相关查询中识别并引用
50-69中等品牌在部分平台有曝光，但存在缺口，AI引用情况不稳定
30-49薄弱品牌平台曝光有限，AI系统可能不会将其视为独立实体
0-29极低品牌平台曝光可忽略，AI系统几乎不会引用或推荐

Analysis Procedure

分析流程

Step 1: Identify Brand Information

步骤1：收集品牌信息

Gather the following from the user or from the website:
  • Brand name (exact spelling, including any official variants)
  • Founder/CEO name(s)
  • Domain URL
  • Industry/category
  • Key products or services (top 3)
  • Key competitors (for comparison context)
从用户或网站收集以下信息：
  • 品牌名称（准确拼写，包括官方变体）
  • 创始人/CEO姓名
  • 域名URL
  • 行业/类别
  • 核心产品或服务（前3个）
  • 主要竞品（用于对比参考）

Step 2: Platform Scanning

步骤2：平台扫描

For each platform, use WebFetch to search and assess presence:
YouTube Check:
  1. Search: 
    [brand name] site:youtube.com
  2. Check: 
    youtube.com/@[brand-name]
    or 
    youtube.com/c/[brand-name]
    for official channel
  3. Search: 
    "[brand name]" site:youtube.com
    (exact match for mentions in descriptions)
  4. Note: Channel subscriber count, video count, latest upload date, third-party mention count
Reddit Check:
  1. Search: 
    [brand name] site:reddit.com
  2. Search: 
    "[brand name]" site:reddit.com
    (exact match)
  3. Check: 
    reddit.com/r/[brand-name]
    for official subreddit
  4. Check: 
    reddit.com/user/[brand-name]
    for official account
  5. Note: Thread count, dominant subreddits, sentiment (positive/negative/neutral), recommendation frequency
Wikipedia Check (IMPORTANT — use BOTH methods to avoid false negatives):
Method 1 — Python API check (MOST RELIABLE, do this FIRST):
bash
python3 -c "
import requests, json
from urllib.parse import quote_plus
brand = '[Brand_Name]'
针对每个平台，使用WebFetch进行搜索和评估：
YouTube检查：
  1. 搜索：
    [brand name] site:youtube.com
  2. 检查：
    youtube.com/@[brand-name]
    或 
    youtube.com/c/[brand-name]
    是否存在官方频道
  3. 搜索：
    "[brand name]" site:youtube.com
    （精确匹配描述中的提及）
  4. 记录：频道订阅数、视频数量、最新上传日期、第三方提及数量
Reddit检查：
  1. 搜索：
    [brand name] site:reddit.com
  2. 搜索：
    "[brand name]" site:reddit.com
    （精确匹配）
  3. 检查：
    reddit.com/r/[brand-name]
    是否存在官方Subreddit
  4. 检查：
    reddit.com/user/[brand-name]
    是否存在官方账号
  5. 记录：帖子数量、主要Subreddit、情感倾向（正面/负面/中性）、推荐频率
Wikipedia检查（重要 — 同时使用两种方法避免假阴性）：
方法1 — Python API检查（最可靠，优先执行）：
bash
python3 -c "
import requests, json
from urllib.parse import quote_plus
brand = '[Brand_Name]'

Check Wikipedia API directly

直接调用Wikipedia API

api_url = f'https://en.wikipedia.org/w/api.php?action=query&list=search&srsearch={quote_plus(brand)}&format=json' r = requests.get(api_url, headers={'User-Agent': 'GEO-Audit/1.0'}, timeout=15) data = r.json() results = data.get('query', {}).get('search', []) if results and brand.lower() in results[0].get('title', '').lower(): print(f'WIKIPEDIA PAGE EXISTS: {results[0]["title"]}') print(f'URL: https://en.wikipedia.org/wiki/{results[0]["title"].replace(" ", "_")}') else: print('No direct Wikipedia page found')
api_url = f'https://en.wikipedia.org/w/api.php?action=query&list=search&srsearch={quote_plus(brand)}&format=json' r = requests.get(api_url, headers={'User-Agent': 'GEO-Audit/1.0'}, timeout=15) data = r.json() results = data.get('query', {}).get('search', []) if results and brand.lower() in results[0].get('title', '').lower(): print(f'WIKIPEDIA PAGE EXISTS: {results[0]["title"]}') print(f'URL: https://en.wikipedia.org/wiki/{results[0]["title"].replace(" ", "_")}') else: print('No direct Wikipedia page found')

Check Wikidata

检查Wikidata

wd_url = f'https://www.wikidata.org/w/api.php?action=wbsearchentities&search={quote_plus(brand)}&language=en&format=json' r2 = requests.get(wd_url, headers={'User-Agent': 'GEO-Audit/1.0'}, timeout=15) wd = r2.json() entities = wd.get('search', []) if entities: print(f'WIKIDATA ENTRY: {entities[0].get("id", "")} — {entities[0].get("description", "")}') "

**Method 2 — Direct URL check (backup verification):**
1. WebFetch: `https://en.wikipedia.org/wiki/[Brand_Name]` — check if the page loads (not a redirect to search)
2. WebFetch: `https://en.wikipedia.org/wiki/[Founder_Name]` for founder article

**Method 3 — Search (least reliable, use only for supplemental info):**
1. Search: `[brand name] site:wikipedia.org`
2. Search: `[brand name] site:wikidata.org`

**CRITICAL:** Web search alone is NOT reliable for determining Wikipedia presence. ALWAYS run the Python API check first. If the API says a page exists, it exists — do not override this with a search result that fails to find it.

5. Note: Article existence, quality, edit history, Wikidata completeness

**LinkedIn Check:**
1. Search: `[brand name] site:linkedin.com`
2. Check: `linkedin.com/company/[brand-name]` for company page
3. Note: Follower count, post frequency, employee count listed, engagement levels

**Other Platforms:**
1. Search: `[brand name] site:quora.com`
2. Search: `[brand name] site:stackoverflow.com` (if technical brand)
3. Search: `[brand name] site:github.com` (if technical brand)
4. Search: `[brand name] site:news.ycombinator.com` (Hacker News)
5. Search: `"[brand name]"` broadly for news mentions (filter to last 6 months)
6. Note: Presence/absence and quality of mentions on each platform
wd_url = f'https://www.wikidata.org/w/api.php?action=wbsearchentities&search={quote_plus(brand)}&language=en&format=json' r2 = requests.get(wd_url, headers={'User-Agent': 'GEO-Audit/1.0'}, timeout=15) wd = r2.json() entities = wd.get('search', []) if entities: print(f'WIKIDATA ENTRY: {entities[0].get("id", "")} — {entities[0].get("description", "")}') "

**方法2 — 直接URL检查（备份验证）：**
1. WebFetch：`https://en.wikipedia.org/wiki/[Brand_Name]` — 检查页面是否可访问（不是跳转到搜索页）
2. WebFetch：`https://en.wikipedia.org/wiki/[Founder_Name]` 检查创始人条目

**方法3 — 搜索（可靠性最低，仅用于补充信息）：**
1. 搜索：`[brand name] site:wikipedia.org`
2. 搜索：`[brand name] site:wikidata.org`

**关键提示：** 仅网页搜索不足以确定Wikipedia存在情况。务必优先运行Python API检查。如果API显示页面存在，则页面确实存在——不要因搜索结果未找到而推翻该结论。

5. 记录：条目存在性、质量、编辑历史、Wikidata完整性

**LinkedIn检查：**
1. 搜索：`[brand name] site:linkedin.com`
2. 检查：`linkedin.com/company/[brand-name]` 是否存在公司主页
3. 记录：粉丝数、发帖频率、列出的员工数、互动水平

**其他平台检查：**
1. 搜索：`[brand name] site:quora.com`
2. 搜索：`[brand name] site:stackoverflow.com`（若为技术品牌）
3. 搜索：`[brand name] site:github.com`（若为技术品牌）
4. 搜索：`[brand name] site:news.ycombinator.com`（Hacker News）
5. 广泛搜索`"[brand name]"`获取新闻提及（筛选近6个月内容）
6. 记录：各平台的提及存在性和质量

Step 3: Sentiment Assessment

步骤3：情感评估

For Reddit and other discussion platforms, assess sentiment by analyzing the most recent and most prominent mentions:
SentimentIndicators
PositiveRecommendations ("I love [brand]," "We switched to [brand] and...", "Highly recommend"), upvoted mentions, positive comparison against competitors
NeutralFactual mentions ("We use [brand] for...", "[Brand] offers..."), questions about the brand, balanced comparisons
NegativeComplaints ("Avoid [brand]", "[Brand] has terrible support"), downvoted recommendations, negative comparisons
MixedCombination of positive and negative. Note the ratio and primary themes.
针对Reddit和其他讨论平台，通过分析最新和最显眼的提及内容评估情感倾向：
情感倾向判断指标
正面推荐内容（"我喜欢[品牌]"、"我们切换到[品牌]后..."、"强烈推荐"），获赞的提及，与竞品的正面对比
中性事实性提及（"我们使用[品牌]做..."、"[品牌]提供..."），关于品牌的问题，平衡的对比
负面投诉内容（"避开[品牌]"、"[品牌]的支持服务极差"），被踩的推荐，与竞品的负面对比
混合正面和负面内容并存，记录比例和主要主题

Step 4: Competitive Comparison (Optional)

步骤4：竞品对比（可选）

If competitors are identified, do a quick scan of their platform presence for context. This helps calibrate the score -- a brand with "moderate" Reddit presence in an industry where competitors have zero Reddit presence is relatively strong.
若已确定竞品，快速扫描其平台曝光情况作为参考。这有助于校准评分——若某品牌在竞品全无Reddit曝光的行业中拥有“中等”Reddit曝光，其相对表现实则强劲。

Step 5: Score Calculation

步骤5：分数计算

  1. Score each platform (0-100) using the rubrics above.
  2. Apply weights to calculate the composite Brand Authority Score.
  3. Identify the strongest and weakest platforms.
  4. Generate specific, actionable recommendations for the weakest platforms.
  1. 使用上述评分标准为每个平台打分（0-100）。
  2. 应用权重计算综合品牌权威度评分。
  3. 识别表现最强和最弱的平台。
  4. 针对最弱平台生成具体、可执行的优化建议。

Output Format

输出格式

Generate a file called 
GEO-BRAND-MENTIONS.md
:
markdown
undefined
生成名为
GEO-BRAND-MENTIONS.md
的文件：
markdown
undefined

Brand Authority Report: [Brand Name]

品牌权威度报告: [品牌名称]

Analysis Date: [Date] Brand: [Brand Name] Domain: [URL] Industry: [Industry]
分析日期: [日期] 品牌: [品牌名称] 域名: [URL] 行业: [行业]

Brand Authority Score: [X]/100 ([Rating])

品牌权威度评分: [X]/100 ([评级])

Platform Breakdown

平台细分

PlatformScoreWeightWeightedStatus
YouTube[X]/10025%[X][Active Channel / Mentioned / Absent]
Reddit[X]/10025%[X][Active / Discussed / Absent]
Wikipedia[X]/10020%[X][Article / Mentioned / Absent]
LinkedIn[X]/10015%[X][Active / Basic / Absent]
Other Platforms[X]/10015%[X][Summary]
Total[X]/100
平台分数权重加权分数状态
YouTube[X]/10025%[X][活跃频道 / 被提及 / 无曝光]
Reddit[X]/10025%[X][活跃 / 被讨论 / 无曝光]
Wikipedia[X]/10020%[X][有条目 / 被提及 / 无曝光]
LinkedIn[X]/10015%[X][活跃 / 基础 / 无曝光]
其他平台[X]/10015%[X][总结]
总分[X]/100

Platform Detail

平台详情

YouTube ([X]/100)

YouTube ([X]/100)

Official Channel: [Yes/No] | [URL if exists] Subscribers: [Count or N/A] Videos: [Count or N/A] Last Upload: [Date or N/A] Third-Party Mentions: [Estimated count] Key Findings:
  • [Finding 1]
  • [Finding 2]
官方频道: [是/否] | [URL（若存在）] 订阅数: [数量或无] 视频数: [数量或无] 最新上传: [日期或无] 第三方提及数: [估计数量] 关键发现:
  • [发现1]
  • [发现2]

Reddit ([X]/100)

Reddit ([X]/100)

Official Account: [Yes/No] | [URL if exists] Own Subreddit: [Yes/No] | [URL and member count if exists] Mention Volume: [Estimated thread count] Primary Subreddits: [List of subreddits where brand is discussed] Sentiment: [Positive/Negative/Neutral/Mixed] Key Findings:
  • [Finding 1]
  • [Finding 2]
官方账号: [是/否] | [URL（若存在）] 专属Subreddit: [是/否] | [URL和成员数（若存在）] 提及量: [估计帖子数] 主要Subreddit: [品牌被讨论的Subreddit列表] 情感倾向: [正面/负面/中性/混合] 关键发现:
  • [发现1]
  • [发现2]

Wikipedia ([X]/100)

Wikipedia ([X]/100)

Company Article: [Yes/No] | [URL if exists] Founder Article: [Yes/No] | [URL if exists] Wikidata Entry: [Yes/No] | [Q-number if exists] Cited in Other Articles: [Yes/No] | [Which articles] Key Findings:
  • [Finding 1]
  • [Finding 2]
公司条目: [是/否] | [URL（若存在）] 创始人条目: [是/否] | [URL（若存在）] Wikidata条目: [是/否] | [Q编号（若存在）] 被其他条目引用: [是/否] | [具体条目] 关键发现:
  • [发现1]
  • [发现2]

LinkedIn ([X]/100)

LinkedIn ([X]/100)

Company Page: [Yes/No] | [URL if exists] Followers: [Count or N/A] Post Frequency: [Weekly/Monthly/Rare/Never] Key Findings:
  • [Finding 1]
  • [Finding 2]
公司主页: [是/否] | [URL（若存在）] 粉丝数: [数量或无] 发帖频率: [每周/每月/极少/从不] 关键发现:
  • [发现1]
  • [发现2]

Other Platforms ([X]/100)

其他平台 ([X]/100)

PlatformPresenceNotes
Quora[Yes/No][Brief note]
Stack Overflow[Yes/No][Brief note]
GitHub[Yes/No][Brief note]
Hacker News[Yes/No][Brief note]
News/Press[Yes/No][Brief note]
Podcasts[Yes/No][Brief note]
平台曝光情况备注
Quora[是/否][简短备注]
Stack Overflow[是/否][简短备注]
GitHub[是/否][简短备注]
Hacker News[是/否][简短备注]
新闻/媒体[是/否][简短备注]
播客[是/否][简短备注]

Recommendations

优化建议

Immediate Actions (Week 1-2)

立即行动（第1-2周）

  1. [Platform]: [Specific action to take with expected impact]
  2. [Platform]: [Specific action]
  1. [平台]: [具体行动及预期效果]
  2. [平台]: [具体行动]

Short-Term Strategy (Month 1-3)

短期策略（第1-3个月）

  1. [Platform]: [Strategy with tactics]
  2. [Platform]: [Strategy with tactics]
  1. [平台]: [策略及执行细节]
  2. [平台]: [策略及执行细节]

Long-Term Authority Building (Month 3-12)

长期权威建设（第3-12个月）

  1. [Platform]: [Long-term strategy]
  2. [Platform]: [Long-term strategy]
  1. [平台]: [长期策略]
  2. [平台]: [长期策略]

Competitive Context

竞品参考

[If competitors were analyzed, show a brief comparison table]
BrandYouTubeRedditWikipediaLinkedInOtherTotal
[Subject Brand][X][X][X][X][X][X]
[Competitor 1][X][X][X][X][X][X]
[Competitor 2][X][X][X][X][X][X]
[若分析了竞品，展示简要对比表格]
品牌YouTubeRedditWikipediaLinkedIn其他总分
[目标品牌][X][X][X][X][X][X]
[竞品1][X][X][X][X][X][X]
[竞品2][X][X][X][X][X][X]

Key Takeaway

核心结论

[1-2 sentence summary of the brand's AI visibility standing and the single most impactful action to take]

---
[1-2句话总结品牌的AI可见性现状，以及最具影响力的行动建议]

---

Reference Data

参考数据

Correlation Strengths (Ahrefs Dec 2025, 75K Brands)

相关性强度（Ahrefs 2025年12月，7.5万个品牌）

SignalCorrelation with AI CitationTraditional SEO Value
YouTube mentions~0.737Low (not a ranking factor)
Reddit mentionsHigh (exact coefficient not published)Low
Wikipedia presenceHighModerate (trust signal)
LinkedIn presenceModerateLow
Domain Rating~0.266Very High
Backlink count~0.266Very High
Organic trafficModerateVery High
Key insight: The signals that matter most for AI visibility (YouTube, Reddit) are almost irrelevant in traditional SEO, and the signals that matter most for traditional SEO (backlinks, DR) are weak predictors of AI visibility. This requires a fundamentally different optimization strategy.
信号与AI引用的相关性传统SEO价值
YouTube提及~0.737低（非排名因子）
Reddit提及高（具体系数未公布）低
Wikipedia存在高中等（信任信号）
LinkedIn存在中等低
域名评级~0.266极高
反向链接数~0.266极高
自然流量中等极高
核心洞察： 对AI可见性最重要的信号（YouTube、Reddit）在传统SEO中几乎无关，而对传统SEO最重要的信号（反向链接、DR）对AI可见性的预测性很弱。这需要完全不同的优化策略。

Platform-Specific Tips for Building Presence

平台曝光建设技巧

YouTube Quick Wins:
  • Create a channel and upload 3-5 explainer videos about your core topics.
  • Ensure your brand name appears in video titles, descriptions, and spoken content.
  • Pursue guest appearances on relevant industry YouTube channels.
  • Create comparison or "alternatives" videos (these get cited by AI for comparison queries).
Reddit Quick Wins:
  • Identify 3-5 subreddits where your target audience is active.
  • Participate authentically (do not shill -- Reddit communities detect and punish this).
  • Do an AMA if appropriate for your brand.
  • Monitor and respond to mentions of your brand.
  • Create genuinely helpful posts that naturally mention your brand's expertise.
Wikipedia Strategy:
  • Hire a Wikipedia-knowledgeable consultant -- do NOT edit your own article (conflict of interest).
  • Build notability through press coverage, academic citations, and industry recognition first.
  • Ensure your Wikidata entry is complete even if you do not have a Wikipedia article.
  • Contribute to industry-relevant articles where your brand can be naturally cited as a source.
LinkedIn Quick Wins:
  • Optimize your company page with complete information and regular posting.
  • Encourage leadership to post thought leadership content weekly.
  • Publish LinkedIn articles on topics where your brand has unique expertise.
  • Engage with industry discussions to increase brand visibility in professional contexts.
YouTube快速优化：
  • 创建频道并上传3-5个关于核心主题的讲解视频。
  • 确保品牌名称出现在视频标题、描述和口语内容中。
  • 争取在相关行业YouTube频道客串。
  • 制作对比或“替代方案”类视频（这类视频会被AI用于对比查询的引用）。
Reddit快速优化：
  • 确定3-5个目标受众活跃的Subreddit。
  • 真实参与社区（不要硬广——Reddit社区会识别并惩罚此类行为）。
  • 若合适，举办AMA活动。
  • 监控并回复品牌提及。
  • 发布真正有帮助的帖子，自然融入品牌的专业能力。
Wikipedia策略：
  • 聘请熟悉Wikipedia规则的顾问——不要自行编辑品牌条目（存在利益冲突）。
  • 先通过媒体报道、学术引用和行业认可建立品牌显著性。
  • 即使没有Wikipedia条目，也要完善Wikidata条目。
  • 为行业相关条目做贡献，在合适的位置自然引用品牌作为来源。
LinkedIn快速优化：
  • 完善公司主页信息，定期发帖。
  • 鼓励管理层每周发布思想领导力内容。
  • 发布品牌拥有独特专业能力的主题文章。
  • 参与行业讨论，提升品牌在专业场景的曝光度。