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Search Query Analyst

Analyze search term reports to classify intent and build negative keyword taxonomies.

Updated Apr 16, 2026
Search Tags:#queries#search#campaign-optimization#intent-classification#negative keywords#paid-search#waste-reduction
One-click install
npx skills add https://github.com/jc180105/.opencode --skill search-query-analyst-jc180105
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Search Query Analyst
Source: https://github.com/jc180105/.opencode/tree/main/.opencode/skills/paid-media-search-query-analyst
Command: npx skills add https://github.com/jc180105/.opencode --skill search-query-analyst-jc180105

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyzes large-scale search term data to reduce wasted spend by mapping queries to buyer intent and building scalable negative keyword taxonomies.

Core Features & Use Cases

  • Search Term Analysis: Large-scale mining of search term reports, pattern identification, and clustering by intent.
  • Negative Keyword Architecture: Tiered negative keyword lists across account, campaign, and ad group levels, plus shared lists and conflict detection.
  • Intent Classification: Mapping queries to buyer intent stages and aligning with landing pages.
  • Match Type Optimization: Close variant impact analysis and boundary testing.
  • Query Sculpting: Directing queries to right campaigns/ad groups through negatives and match type combinations.
  • Waste Identification: Flagging non-converting and high-CPC low-value queries.
  • Opportunity Mining: Discover high-potential keywords from converting terms.
  • Reporting & Visualization: Trend analysis and waste-over-time reporting.

Quick Start

Analyze the latest search term report and generate a tiered negative keyword list with recommended match types.

Frequently Asked Questions about Search Query Analyst

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I reduce wasted spend in paid search campaigns?▼

Reduce wasted spend by mining search term reports to identify non-converting queries and building a tiered negative keyword architecture across account, campaign, and ad group levels.

What is query sculpting and how does it improve high-intent traffic?▼

Query sculpting directs search queries to the correct campaigns by combining negative keywords and match type adjustments, ensuring high-intent traffic aligns with specific landing pages.

How do I build a negative keyword taxonomy for large paid search accounts?▼

Build a negative keyword taxonomy by clustering large-scale search term data by buyer intent, applying tiered lists across account levels, and detecting conflicts to prevent blocking high-potential keywords.

Can I analyze search term reports to classify buyer intent stages?▼

Analyze search term reports to map queries to buyer intent stages, identify high-potential converting terms, and align them with corresponding landing pages for optimization.

What is the best way to identify wasted spend from high-CPC low-value queries?▼

Identify wasted spend by analyzing large-scale search term data to flag non-converting and high-CPC low-value queries, visualizing waste-over-time trends for ongoing optimization.

When do I need match type optimization for search query analysis?▼

Match type optimization is needed when analyzing close variant impacts and boundary testing to ensure queries are directed to the right campaigns and ad groups through query sculpting.

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