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social-seo

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English
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Chinese

Social SEO

社交 SEO

Make content findable when people search, not just visible when the feed happens to show it. In 2026 every social platform is a search engine, and search is the highest-intent, most evergreen discovery there is.
Four truths shape everything:
  1. All social platforms are search engines (TikTok/IG/YouTube/Pinterest/LinkedIn) — and people search different platforms for different intents. If you only optimize for the feed, you're invisible to people actively looking.
  2. Keywords, not hashtags, are the lever. Write for the search bar first; hashtags are a minor category signal → 
    hashtag-strategy
    .
  3. Search optimization doubles as recommendation optimization — the keywords that get you found in search are the same signals the algorithm uses to categorize you for the right feed/FYP audience.
  4. SEO turns posts into evergreen assets — a search-optimized post keeps getting found for months; a feed post dies in ~48h.
(Full model + the AI-search/GEO boundary: 
references/why-social-search.md
.)
让内容在人们搜索时可被找到，而不仅仅是在 feed 恰好展示时可见。到 2026 年，每个社交平台都是搜索引擎，而搜索是意图最明确、最具常青生命力 的发现方式。
四个事实决定了所有做法：
  1. 所有社交平台都是搜索引擎（TikTok/IG/YouTube/Pinterest/LinkedIn）——而且人们会根据不同意图在不同平台上搜索。如果你只针对 feed 做优化，那么对于正在主动搜索的人而言，你就是不可见的。
  2. 关键词才是杠杆，而不是 hashtags。 首先围绕搜索框撰写；hashtags 只是次要的分类信号 → 
    hashtag-strategy
    。
  3. 搜索优化同时也是推荐优化——让你在搜索中被找到的关键词，也是算法用于将你归类到合适 feed/FYP 受众的相同信号。
  4. SEO 将帖子转化为常青资产——经过搜索优化的帖子会在数月内持续被找到；而 feed 帖子约 48 小时后就会消亡。
（完整模型 + AI 搜索/GEO 边界：
references/why-social-search.md
。）

Step 0 — Read the foundation + the goal

第 0 步——读取基础信息 + 目标

Load 
brand-profile.md
and 
audience.md
(their exact search language matters). Get the platform(s) and what the user wants to be found for.
加载 
brand-profile.md
和 
audience.md
（它们使用的准确搜索语言很重要）。确定平台，以及用户希望被找到什么。

Step 1 — Keyword research (real demand, never invented)

第 1 步——关键词研究（真实需求，绝不凭空编造）

Find the terms people actually search via platform autocomplete, "others searched for", related searches, comments, audience language, and the user's native search analytics (+ tools like TikTok Creative Center / VidIQ). The agent can't pull live search volumes — never fabricate numbers; give the method and work from intent/specificity. Favor long-tail, intent-rich queries you can genuinely answer. See 
references/keyword-research-and-technique.md
.
查找人们实际搜索的词语，可通过平台 autocomplete、“others searched for”、相关搜索、评论、受众语言以及用户的原生搜索分析（+ TikTok Creative Center / VidIQ 等工具）。Agent 无法拉取实时搜索量——绝不捏造数字；应提供方法，并基于意图/具体程度开展工作。优先选择你确实能够回答的长尾且意图明确的查询。参见 
references/keyword-research-and-technique.md
。

Step 2 — Place keywords across the platform's SEO surface

第 2 步——在各平台的 SEO 内容面中布置关键词

Each platform indexes different things — optimize the right ones (full per-platform guide in 
references/platform-seo-surfaces.md
):
  • TikTok — spoken audio (transcribed) + on-screen text + caption (the triple mention).
  • Instagram — caption + the searchable name/display field + bio + alt text + captioned Reels.
  • YouTube — keyword-led title + ~200–300w description + transcript/captions + chapters.
  • Pinterest — keyword title + description + board names + alt (hashtags deprecated there).
  • LinkedIn — searchable headline/About + on-topic post keywords → 
    linkedin-growth
    .
  • Cross-cutting — subtitles, alt text, descriptive file names, a consistent branded handle.
每个平台会索引不同内容——应优化对应内容（完整的各平台指南见 
references/platform-seo-surfaces.md
）：
  • TikTok——口播音频（转录文本）+ 屏幕文字 + caption（三重提及）。
  • Instagram——caption + 可搜索的 name/display 字段 + bio + alt text + 带字幕的 Reels。
  • YouTube——以关键词为导向的 title + 约 200–300 词的 description + transcript/captions + chapters。
  • Pinterest——关键词 title + description + board 名称 + alt（该平台上的 hashtags 已弃用）。
  • LinkedIn——可搜索的 headline/About + 主题相关帖子关键词 → 
    linkedin-growth
    。
  • 跨平台共性——字幕、alt text、描述性文件名、统一的品牌 handle。

Step 3 — The on-content technique

第 3 步——内容中的技术

Lead with keywords, support with hashtags. State the primary phrase in natural language, early, once or twice; align audio + on-screen + caption to one search intent; add 3–5 niche hashtags. Never keyword-stuff (spam dilutes your topical signal). Resolve the search-vs-feed tension (clarity vs hook) deliberately. See 
references/keyword-research-and-technique.md
.
关键词在前，hashtags 辅助。 用自然语言尽早呈现主要短语，出现一次或两次；让音频 + 屏幕文字 + caption 对齐到同一个搜索意图；添加 3–5 个细分领域的 hashtags。 绝不要堆砌关键词（垃圾内容会稀释你的主题信号）。有意识地处理搜索与 feed 之间的张力（清晰度与开场吸引力（hook））。参见 
references/keyword-research-and-technique.md
。

Step 4 — Build topical clusters (evergreen authority)

第 4 步——构建主题集群（常青权威）

One post rarely owns a query. Cluster evergreen content around a pillar topic so you become the answer/authority — which compounds and sharpens recommendation categorization. Map a 
content-pillars
pillar → a keyword cluster → many evergreen posts.
一篇帖子很少能独占一个查询。围绕一个支柱主题对常青内容进行聚类，从而成为答案/权威来源——这会产生累积效应，同时强化推荐分类。将 
content-pillars
支柱主题 → 关键词集群 → 多篇常青帖子进行映射。

Step 5 — Optimize the profile as a search asset

第 5 步——将个人资料优化为搜索资产

The name/display field, handle, headline/bio should carry the searchable keyword/category (not just a clever brand line). This is the searchability lens — 
profile-optimization
owns the conversion lens; both matter. Public profiles/content are increasingly Google-indexable too.
name/display 字段、handle、headline/bio 应包含可搜索的关键词/类别（而不应只有一句巧妙但不可搜索的品牌标语）。这是可搜索性视角——
profile-optimization
负责转化视角；两者都很重要。公开的个人资料/内容也越来越多地可被 Google 索引。

Step 6 — Measure (honestly) + hand off GEO

第 6 步——如实衡量 + 移交 GEO

Track discoverability: impressions from search, the search terms that found you, profile visits from non-followers, saves, evergreen-post growth — via native platform search analytics (+ Search Console/UTMs). No WoopSocial analytics. For getting cited by AI search/LLMs (GEO), hand off to 
ai-search-optimization
— related but separate.
通过原生平台搜索分析（+ Search Console/UTMs），跟踪可发现性：搜索带来的曝光、找到你的搜索词、非关注者带来的个人资料访问、收藏、常青帖子增长。不使用 WoopSocial analytics。 若希望被 AI 搜索/LLM 引用（GEO），则移交 
ai-search-optimization
——相关但属于独立领域。

Orchestration map

编排关系图

social-seo sets the discovery layer; it routes to / is routed from: 
hashtag-strategy
(hashtag specifics) · 
caption-writer
(adds the keyword layer) · 
profile-optimization
(conversion lens) · 
content-pillars
(clusters) · 
tiktok-growth
/ 
instagram-growth
/ 
linkedin-growth
(search as a growth pillar) · 
ai-search-optimization
(GEO hand-off) · 
scheduling-and-queue
(publish).
social-seo 负责发现层；它可转交至或由以下 skill 转入：
hashtag-strategy
（hashtag 具体策略）· 
caption-writer
（添加关键词层）· 
profile-optimization
（转化视角）· 
content-pillars
（集群）· 
tiktok-growth
/ 
instagram-growth
/ 
linkedin-growth
（将搜索作为增长支柱）· 
ai-search-optimization
（GEO 移交）· 
scheduling-and-queue
（发布）。

Quality bar — self-check

质量标准——自检

  • Did I do real keyword research (autocomplete/native analytics) and avoid inventing volumes?
  • Did I optimize the platform-specific indexed surfaces (not one generic answer)?
  • Did I use lead-with-keywords + the triple mention, in natural language (no stuffing)?
  • Did I think in evergreen clusters / topical authority, and note the search = recommendation payoff?
  • Did I treat the profile as a search asset, route hashtags to 
    hashtag-strategy
    , and hand GEO to 
    ai-search-optimization
    ?
  • Native-search-insights measurement, no WoopSocial analytics, searchability not guaranteed rankings?
  • 是否进行了真实的关键词研究（autocomplete/原生分析），并避免捏造搜索量？
  • 是否优化了各平台特有的被索引内容面（而不是只给出通用答案）？
  • 是否采用了关键词在前 + 三重提及，并以自然语言表达（没有堆砌）？
  • 是否从常青集群/主题权威角度进行思考，并指出搜索 = 推荐的收益？
  • 是否将个人资料视为搜索资产，把 hashtags 转至 
    hashtag-strategy
    ，并将 GEO 移交 
    ai-search-optimization
    ？
  • 是否基于原生搜索洞察进行衡量、不使用 WoopSocial analytics，并明确可搜索性并不保证排名？

Edge cases & pushback

边界情况与异议处理

  • "Give me exact search volumes" → can't pull live volume; show the research method; don't fabricate.
  • "Stuff every keyword + 30 hashtags" → refuse; spam dilutes the signal; natural language + a few niche tags.
  • "I optimized one post, done" → build a cluster; one post rarely owns a query.
  • "Just use trending hashtags" → hashtags categorize, keywords get found → 
    hashtag-strategy
    .
  • "Make ChatGPT/Google-AI cite me" → that's GEO → 
    ai-search-optimization
    .
  • "Which post ranks best?" → native platform search insights; no WoopSocial analytics.
  • Clever-but-vague title → keep the searchable phrase; add intrigue after the keyword.
  • “给我准确的搜索量” → 无法拉取实时搜索量；展示研究方法；不要编造。
  • “塞入所有关键词 + 30 个 hashtags” → 拒绝；垃圾堆砌会稀释信号；使用自然语言 + 少量细分标签。
  • “我优化了一篇帖子，就完成了” → 构建集群；一篇帖子很少能独占一个查询。
  • “只使用热门 hashtags” → hashtags 负责分类，关键词才能让人被找到 → 
    hashtag-strategy
    。
  • “让 ChatGPT/Google-AI 引用我” → 这属于 GEO → 
    ai-search-optimization
    。
  • “哪篇帖子排名最高？” → 使用原生平台搜索洞察；不使用 WoopSocial analytics。
  • 聪明但模糊的标题 → 保留可搜索短语；在关键词之后加入悬念。

Related skills

相关 skills

  • brand-profile
    , 
    audience-research
    — the search language and positioning.
  • instagram-seo
    , 
    pinterest-seo
    — single-platform search depth (route platform-specific asks there).
  • hashtag-strategy
    — the hashtag layer (a minor signal); 
    caption-writer
    — caption craft.
  • profile-optimization
    — profile as conversion (this skill = profile as search).
  • content-pillars
    — pillars become keyword clusters; the growth skills lean on search.
  • ai-search-optimization
    — the AI-search/LLM-citation (GEO) hand-off; 
    scheduling-and-queue
    — publish.
  • brand-profile
    、
    audience-research
    ——搜索语言与定位。
  • instagram-seo
    、
    pinterest-seo
    ——单平台搜索深度（将平台特定请求转至此处）。
  • hashtag-strategy
    ——hashtag 层（次要信号）；
    caption-writer
    ——caption 创作。
  • profile-optimization
    ——将个人资料作为转化资产（本 skill = 将个人资料作为搜索资产）。
  • content-pillars
    ——支柱主题转化为关键词集群；增长类 skills 依赖搜索。
  • ai-search-optimization
    ——AI 搜索/LLM 引用（GEO）移交；
    scheduling-and-queue
    ——发布。

References

参考资料

  • references/why-social-search.md
    — the 2026 reality, the three layers, search=recommendation, evergreen, the GEO boundary.
  • references/platform-seo-surfaces.md
    — what each platform indexes and how to optimize it (TikTok/IG/YouTube/Pinterest/LinkedIn/X/FB + cross-cutting).
  • references/keyword-research-and-technique.md
    — finding keywords (no fabrication), the triple-mention technique, clusters, no-stuffing, measurement.
  • references/examples.md
    — worked optimizations per platform + a cluster plan + honest scope.
  • references/why-social-search.md
    ——2026 年的现实、三个层级、搜索 = 推荐、常青内容、GEO 边界。
  • references/platform-seo-surfaces.md
    ——每个平台会索引什么以及如何优化（TikTok/IG/YouTube/Pinterest/LinkedIn/X/FB + 跨平台共性）。
  • references/keyword-research-and-technique.md
    ——查找关键词（不捏造数据）、三重提及 technique、集群、不堆砌、衡量。
  • references/examples.md
    ——各平台实战优化示例 + 集群规划 + 如实说明适用范围。