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sqr-classifier

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SQR Classifier

SQR 分类器

Classify search terms into intent categories for Google Ads accounts.
为 Google Ads 账户中的搜索词进行意图分类。

What This Skill Deliberately Does NOT Do

本 Skill 明确不做什么

  • Pull the search terms. It classifies the terms you hand it (a paste, a CSV, or a report someone else ran) — pulling the search-term report itself is 
    google-ads-query
     or 
    gaql-query-patterns
     territory.
  • Upload or apply negatives. It labels intent and never auto-generates a negative list without your review; it pushes nothing to an account — the upload lives in 
    sqr-pipeline
     or 
    add-account-negative-keywords
    .
  • Pattern-match by regex. Every term gets judgment, not a rule engine — the same query is High Intent for one business and Off-Brand for another, so a mechanical matcher would misclassify.
  • Classify without context. It refuses to categorize until it knows what the business does and where it operates; the business type and location come first.
  • 拉取搜索词。 它只分类你直接提供的搜索词（粘贴内容、CSV 文件，或其他人运行的报告）——拉取 search term 报告本身应由 
    google-ads-query
     或 
    gaql-query-patterns
     处理。
  • 上传或应用 negative keywords。 它只负责标注意图，未经审核绝不会自动生成 negative keyword 列表；也不会向账户推送任何内容——上传操作应由 
    sqr-pipeline
     或 
    add-account-negative-keywords
     完成。
  • 通过 regex 进行模式匹配。 每个搜索词都经过独立判断，而不是依赖规则引擎——同一个查询对某家企业可能是高意向，对另一家企业则可能是非品牌词，机械匹配会造成误分类。
  • 在缺乏上下文时分类。 在了解企业业务类型及其运营区域之前，它不会进行分类；必须先获取这些信息。

When to Use

使用场景

  • User provides a list of search terms to classify
  • User asks to analyze search queries from a campaign
  • User wants to identify negative keyword candidates
  • User provides a CSV or paste of search term data
  • 用户提供一组需要分类的搜索词
  • 用户要求分析广告系列中的搜索查询
  • 用户希望识别 negative keyword 候选项
  • 用户提供搜索词数据的 CSV 文件或粘贴内容

Classification Categories

分类类别

Classify each search term into exactly ONE of these categories:
将每个搜索词准确归入以下一个类别：

High Intent

高意向（High Intent）

The searcher is actively looking for the product or service the business offers.
Signals:
  • Contains service/product keywords matching the business
  • Includes location terms relevant to the business area
  • Shows purchase intent ("near me," "cost," "hire," "best," specific product names)
  • Matches the business's core offerings
搜索者正在主动寻找企业提供的产品或服务。
特征：
  • 包含与企业产品或服务相匹配的关键词
  • 包含与企业服务区域相关的地点词
  • 表现出购买意图（“near me”“cost”“hire”“best”或具体产品名称）
  • 与企业的核心产品或服务相符

Low Intent

低意向（Low Intent）

Related to the business's industry but unlikely to convert. The searcher may be a current customer, a job seeker, or someone in early research.
Signals:
  • Current customer queries (login, pay bill, contact, hours)
  • Job-seeking terms (careers, hiring, salary, jobs at)
  • Competitor brand names (searching for a specific competitor, not the business)
  • Tangentially related but not a buying signal
  • Review/comparison queries without purchase intent
与企业的行业相关，但转化可能性较低。搜索者可能是现有客户、求职者，或处于早期研究阶段。
特征：
  • 现有客户查询（login、pay bill、contact、hours）
  • 求职类搜索词（careers、hiring、salary、jobs at）
  • 竞争对手品牌名称（搜索特定竞争对手，而非该企业）
  • 仅边缘相关，但没有购买信号
  • 不含购买意图的评测或比较类查询

Informational

信息型（Informational）

Research or educational queries. The searcher wants to learn something, not buy.
Signals:
  • "How to," "what is," "why does," "can I"
  • General industry questions
  • DIY or self-service intent
  • Average/typical/benchmark queries
  • Forum or Reddit-seeking queries
研究或教育类查询。搜索者希望了解某件事，而不是购买产品或服务。
特征：
  • “How to”“what is”“why does”“can I”等表达
  • 行业内的通用问题
  • DIY 或自助服务意图
  • 平均值、典型值或基准类查询
  • 寻找论坛或 Reddit 内容的查询

Off-Brand

非品牌（Off-Brand）

Completely unrelated to the business. These should be added as negative keywords immediately.
Signals:
  • Different industry entirely
  • Wrong product/service category
  • Wrong geographic area (if geo-specific business)
  • Misspellings that match unrelated terms
  • Adult, illegal, or irrelevant content
与企业的业务完全无关。此类词应立即添加为 negative keywords。
特征：
  • 完全不同的行业
  • 错误的产品或服务类别
  • 错误的地理区域（适用于地域性企业）
  • 与无关词相似的拼写错误
  • 成人、违法或无关内容

Classification Rules

分类规则

  1. Context is required. Always ask what the business does and where it operates before classifying. A term like "pool maintenance" is High Intent for a pool company and Off-Brand for an apartment complex.
  2. When in doubt between High and Low Intent, choose Low Intent. False positives (keeping a bad term) cost more than false negatives (losing a marginal term). Conservative classification protects budget.
  3. Brand terms are always High Intent if they match the business's own brand name. Competitor brand terms are Low Intent.
  4. Location matters. "Apartments in Austin" is High Intent for an Austin property. The same query is Off-Brand for a property in Denver.
  5. One category per term. Do not assign multiple categories. Pick the most accurate one.
  6. Classify the intent, not the word. "Cheap apartments" has High Intent even though "cheap" seems negative — the searcher wants an apartment.
  1. 必须具备上下文。 分类前始终询问企业从事什么业务以及在哪些地区运营。例如，“pool maintenance”对泳池维护公司而言是高意向，对公寓物业而言则是非品牌词。
  2. 在高意向与低意向之间难以判断时，选择低意向。 假阳性（保留一个不良搜索词）造成的代价高于假阴性（损失一个边缘搜索词）。保守分类有助于保护预算。
  3. 品牌词始终为高意向。 如果搜索词与该企业自己的品牌名称相符，则属于高意向。竞争对手品牌词属于低意向。
  4. 地点很重要。 “Apartments in Austin”对位于 Austin 的房产企业而言是高意向；同一个查询对位于 Denver 的房产企业而言则是非品牌词。
  5. 每个搜索词只分配一个类别。 不要分配多个类别，应选择最准确的类别。
  6. 分类对象是意图，而不是单词。 即使“cheap”看起来像负面词，“Cheap apartments”仍属于高意向，因为搜索者想要的是公寓。

Output Format

输出格式

Present results as a table:
Search TermCategoryReasoning
[term][High Intent / Low Intent / Informational / Off-Brand][One sentence explaining why]
After the table, provide a summary:
  • High Intent: X terms (X%) — keep these
  • Low Intent: X terms (X%) — monitor, consider negatives for high-spend terms
  • Informational: X terms (X%) — usually negative unless targeting top-of-funnel
  • Off-Brand: X terms (X%) — add as negative keywords immediately
以表格形式呈现结果：
搜索词类别原因
[搜索词][高意向（High Intent） / 低意向（Low Intent） / 信息型（Informational） / 非品牌（Off-Brand）][用一句话解释原因]
表格之后提供汇总：
  • 高意向（High Intent）： X 个搜索词（X%）——保留这些词
  • 低意向（Low Intent）： X 个搜索词（X%）——进行监控；对于高消费搜索词，可考虑设为 negative keywords
  • 信息型（Informational）： X 个搜索词（X%）——通常设为 negative keywords，除非采用 top-of-funnel 策略
  • 非品牌（Off-Brand）： X 个搜索词（X%）——立即添加为 negative keywords

Batch Processing

批量处理

For large lists (100+ terms):
  1. Process in batches of 50
  2. Show results after each batch
  3. Ask if the user wants to continue or adjust the classification criteria
  4. At the end, provide the full summary
对于大型列表（100 个以上搜索词）：
  1. 每批处理 50 个
  2. 每批处理后展示结果
  3. 询问用户是否继续或调整分类标准
  4. 最后提供完整汇总

Worked Example

实例

Business: Metro Auto, an auto repair shop serving a single metro area.
Search TermCategoryReasoning
brake repair near meHigh IntentCore service plus a local purchase signal ("near me").
transmission fluid change costHigh IntentNames a service the shop offers and asks price — active buying research.
auto mechanic jobsLow IntentJob seeker, not a customer — related to the industry but won't convert.
how to change your own oilInformationalDIY how-to; the searcher wants to learn, not hire.
car dealership downtownOff-BrandA different business entirely (vehicle sales, not repair) — negate immediately.
Summary:
  • High Intent: 2 terms (40%) — keep these
  • Low Intent: 1 term (20%) — monitor, consider negatives for high-spend terms
  • Informational: 1 term (20%) — usually negative unless targeting top-of-funnel
  • Off-Brand: 1 term (20%) — add as negative keywords immediately
企业： Metro Auto，一家服务于单一都会区域的汽车维修店。
搜索词类别原因
brake repair near me高意向（High Intent）核心服务加上本地购买信号（“near me”）。
transmission fluid change cost高意向（High Intent）指明了该店提供的服务并询问价格，表现出积极的购买研究意图。
auto mechanic jobs低意向（Low Intent）属于求职者搜索，而非潜在客户；与行业相关，但不会转化。
how to change your own oil信息型（Informational）DIY 操作指南；搜索者希望学习，而不是预约维修服务。
car dealership downtown非品牌（Off-Brand）属于完全不同的业务类型（车辆销售，而非维修）——应立即设为 negative keyword。
汇总：
  • 高意向（High Intent）： 2 个搜索词（40%）——保留这些词
  • 低意向（Low Intent）： 1 个搜索词（20%）——进行监控；对于高消费搜索词，可考虑设为 negative keywords
  • 信息型（Informational）： 1 个搜索词（20%）——通常设为 negative keywords，除非采用 top-of-funnel 策略
  • 非品牌（Off-Brand）： 1 个搜索词（20%）——立即添加为 negative keywords

What NOT to Do

不应执行的操作

  • Do NOT classify without knowing the business type and location
  • Do NOT use pattern matching or regex — use judgment for each term
  • Do NOT mark brand terms as Off-Brand just because they contain a competitor name
  • Do NOT auto-generate negative keyword lists without user review
  • Do NOT assume the business offers services that haven't been confirmed
  • 不知道企业类型和所在区域时，不要进行分类
  • 不要使用模式匹配或 regex——应逐个判断搜索词
  • 不要仅因品牌词中包含竞争对手名称，就将其标记为非品牌词
  • 未经用户审核，不要自动生成 negative keyword 列表
  • 不要假设企业提供尚未确认的服务

When to Load Other Skills

何时加载其他 Skills

SkillWhen
google-ads-query
 or 
gaql-query-patterns
Before classifying, when you still need to pull the search-term report the classification runs on
sqr-pipeline
When you want the full pull → classify → review → upload flow with negatives actually applied, not just labeled
add-account-negative-keywords
When the Off-Brand terms should become account-level negatives across campaigns
geo-conflict-analyzer
It routes here for quick intent classification when the full pipeline isn't warranted
Skill使用时机
google-ads-query
 或 
gaql-query-patterns
分类前，如果仍需拉取作为分类依据的 search term 报告
sqr-pipeline
需要完整的拉取 → 分类 → 审核 → 上传流程，并实际应用 negative keywords，而不只是进行标注
add-account-negative-keywords
需要将非品牌词添加为跨广告系列的账户级 negative keywords 时
geo-conflict-analyzer
无需运行完整 pipeline 时，可转入本 Skill 进行快速的意图分类