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seo-keyword-metrics

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Original

English
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Translation

Chinese

SEO Keyword Metrics

SEO关键词指标

Enrich the keyword candidate pool with quantitative metrics: search volume, keyword difficulty, and search intent.
为关键词候选池补充量化指标：搜索量、关键词难度（KD）和搜索意图。

Credentials Check

凭证检查

If 
DATAFORSEO_LOGIN
or 
DATAFORSEO_PASSWORD
are missing, tell the user:
"DataForSEO credentials are not configured. Please run 
seo-seed-discovery
first — it will guide you through the setup."
如果缺少
DATAFORSEO_LOGIN
或
DATAFORSEO_PASSWORD
，请告知用户：
"未配置DataForSEO凭证。请先运行
seo-seed-discovery
——它会引导您完成设置。"

When to Use

使用时机

After 
seo-keyword-expansion
has completed and 
candidate-pool.json
exists in the workspace.
在
seo-keyword-expansion
完成且工作区中存在
candidate-pool.json
之后。

Prerequisites

前提条件

  • Workspace with 
    candidate-pool.json
    (merged from expansion results)
  • 包含
    candidate-pool.json
    的工作区（由扩展结果合并而来）

Procedure

操作步骤

Step 1: Bulk Search Volume

步骤1：批量获取搜索量

bash
node {baseDir}/scripts/bulk-volume.ts --workspace <workspace_path>
Fetches monthly search volume + CPC + competition for all candidate keywords. Writes 
volume.json
.
bash
node {baseDir}/scripts/bulk-volume.ts --workspace <workspace_path>
获取所有候选关键词的月度搜索量 + 每次点击费用（CPC） + 竞争度。生成
volume.json
文件。

Step 2: Bulk Keyword Difficulty

步骤2：批量计算关键词难度

bash
node {baseDir}/scripts/bulk-kd.ts --workspace <workspace_path>
Calculates keyword difficulty scores. Writes 
kd.json
.
bash
node {baseDir}/scripts/bulk-kd.ts --workspace <workspace_path>
计算关键词难度得分。生成
kd.json
文件。

Step 3: Search Intent Classification

步骤3：搜索意图分类

bash
node {baseDir}/scripts/search-intent.ts --workspace <workspace_path>
Classifies search intent (informational / navigational / commercial / transactional). Writes 
intent.json
.
After all three steps, a merged 
metrics.json
is produced.
bash
node {baseDir}/scripts/search-intent.ts --workspace <workspace_path>
对搜索意图进行分类（信息型/导航型/商业型/交易型）。生成
intent.json
文件。
完成上述三个步骤后，会生成合并后的
metrics.json
文件。

Expert Analysis Framework

专家分析框架

Analyze the metrics data as an SEO strategist:
  1. Volume Distribution: What's the volume range? Are there hidden gems in the 100-1000 range?
  2. KD vs Volume Efficiency: Plot keywords on a KD/Volume matrix. Find the "sweet spot" — reasonable volume with manageable difficulty
  3. Intent Distribution: What percentage is informational vs commercial? Does this match the user's content strategy?
  4. CPC as Signal: High CPC keywords often indicate commercial value even if volume is low
  5. Quick Win Candidates: Low KD + decent volume keywords the domain could rank for quickly
以SEO策略师的身份分析指标数据：
  1. 搜索量分布：搜索量范围是多少？100-1000区间内是否有潜力关键词？
  2. KD与搜索量效率：在KD/搜索量矩阵上绘制关键词，找到“最佳平衡点”——合理搜索量且难度可控的关键词
  3. 意图分布：信息型和商业型关键词的占比分别是多少？这是否符合用户的内容策略？
  4. CPC作为信号：高CPC关键词即使搜索量低，通常也具有商业价值
  5. 快速见效候选词：低KD + 可观搜索量的关键词，域名可快速获得排名

Output Format

输出格式

  • Metrics Summary (total keywords, average volume, average KD)
  • Distribution Analysis (volume tiers, KD tiers, intent breakdown)
  • Top 15 Sweet Spot Keywords (high value / achievable difficulty)
  • Quick Win List (KD < 30, Volume > 100)
  • 指标摘要（关键词总数、平均搜索量、平均KD）
  • 分布分析（搜索量层级、KD层级、意图细分）
  • Top 15最佳平衡关键词（高价值/可实现难度）
  • 快速见效列表（KD < 30，搜索量 > 100）