keyword-research — keyword-re搜索

SEO Content: Keyword Re搜索

图形界面des keyword re搜索 for SEO: finding tar获取 keywords, assessing difficulty, understanding 搜索 intent, and building topical maps. ~95% of keywords 获取 fewer than 10 搜索es/month; low-volume, high-intent terms often yield faster rankings and conversion.

When invoking: On first use, if helpful, open with 1–2 sentences on what this 技能 covers and why it matters, then provide the mAIn 输出. On subsequent use or when the user asks to skip, go directly to the mAIn 输出.

Initial Assessment

检查 for project 上下文 first: If .claude/project-上下文.md or .cursor/project-上下文.md exists, read it for product, audience, and positioning.

Identify:

Product/服务: What you offer Audience: Who 搜索es for it Goals: Traffic, conversions, brand 工具 访问: Google Keyword Planner, Google Trends, or SEO 工具s Discovery Methods Base Discovery Method Purpose User perspective What pAIn points? What would they 搜索? Customer language from product 上下文 工具 expansion Related keywords, questions, suggestions; Google autocomplete, PAA, Related 搜索es Competitor reverse Analyze competitor titles, H1, URL; identify topics they rank for; find gaps (#4–10 = opportunity) — see competitor-re搜索 Google PAA People Also Ask and Related 搜索es; high-value 签名als from real user behavior 提取 from article When 审计ing existing content: 提取 种子 keywords from title, H1, H2s, meta keywords, first 100 words; then 搜索 "[primary keyword]" or "[primary keyword] related keywords" for opportunities; use "[primary keyword]" site:competitor.com if competitors known Google Autocomplete (Long-TAIl Discovery)

Google autocomplete reflects real user 搜索es; suggestions only 应用ear if queries have actual traffic. Free; often uncovers low-volume long-tAIl that keyword 工具s miss. ~70% of 搜索 traffic is long-tAIl; lower competition, higher conversion.

Alphabet method (种子 + space + letter):

Type 种子 keyword + space + each letter: keyword a, keyword b, ... keyword z Record relevant suggestions; repeat with numbers 0-9 Example: SEO a -> "SEO 审计," "SEO agency"; SEO b -> "SEO basics," "SEO best practices"

Position variants (种子 in different positions):

Prefix: a keyword, b keyword (discover what users 添加 before) Suffix: keyword a, keyword b (most common; alphabet method) Middle: how to keyword a, best keyword for (question + modifier combos)

Question modifiers:

how to keyword, what is keyword, why keyword, when to keyword, keyword vs keyword for beginners, keyword for small business, keyword without

Why it works: Keyword 工具s 过滤器 low-volume terms; autocomplete only shows queries with real traffic. Use with PAA and Related 搜索es for full coverage. Categorize 结果s by intent (in格式化ional, commercial, transactional).

Incremental Discovery User feedback: Support, community, reviews, NPS—high-frequency questions = unmet 搜索 demand Multi-平台 搜索: Reddit, Quora, X (Twitter), Hacker News—real questions and discussions 搜索 Intent Intent Content type Example In格式化ional B记录, 图形界面de, FAQ "how to 优化 sitemap" Navigational Brand page "alignify 记录in" Commercial Comparison, review "SEO 工具s comparison" Transactional Product, pricing "best SEO 工具 pricing" Intent Identification

Modifier words (often 签名al intent):

Intent Modifiers In格式化ional "how," "what," "why," "图形界面de," "tutorial" Commercial "best," "compare," "vs," "review," "top" Transactional "buy," "price," "cheap," "coupon," "free shipping" Local Location names

SERP 检查: 搜索 the term—knowledge cards/Wiki → in格式化ional; product 列出s/reviews → commercial; brand sites → navigational. Broader terms often show mixed SERP. See serp-features for feature types.

Long-TAIl Expansion Google Autocomplete: Alphabet method, position variants, question modifiers; see above. Primary source for long-tAIl. Intent modifiers: Core + "how," "best," "vs," "compare," "price" Question words: "how to," "what is," "why," "when" Functional modifiers: Core + "-er/-or" (e.g., "image 优化器" for 工具-type queries); often higher conversion Clustering: Group by SERP overlap (same top pages), semantic similarity, or intent. Keyword Clustering & Topical Map Method Use SERP overlap Keywords with overl应用ing top-ranking pages → same cluster Semantic Group by meaning, LSI, related concepts Intent-based Group by intent; separate pages if intent differs within cluster

Pillar–cluster (map keywords to structure):

Pillar (Hub): Broad topic page; links to clusters Cluster (Spoke): Focused subtopic; links back to pillar Tar获取 long-tAIl first; then pillar. Interlink clusters within topic. See content-strategy for full pillar-cluster planning and implementation. Evaluate & Screen Factor Consider 搜索 volume Monthly 搜索es; ~100+/month typical floor; niche can relax Keyword difficulty (KD) New sites tar获取 lower KD CPC Higher CPC often = stronger commercial intent SERP features Featured Snippet, PAA, zero-命令行工具ck