search-term-ngrams

Aggregate Google Ads search-term n-grams to identify negative keyword candidates and expansion themes.

17|5|Updated Jun 25, 2026

Search Tags:#optimization #google ads #ppc #search terms #negative keywords #n-grams

Ready to run

npx skills add https://github.com/portermetricsample/marketing-skills --skill search-term-ngrams

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: search-term-ngrams
Source: https://github.com/portermetricsample/marketing-skills/tree/main/google-ads/search-terms/n-grams
Command: npx skills add https://github.com/portermetricsample/marketing-skills --skill search-term-ngrams

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill solves the problem of inefficient Google Ads account hygiene by identifying patterns in search terms that are invisible at the individual term level, allowing you to optimize spend and discover new growth opportunities.

Core Features & Use Cases

Waste Mining: Automatically identifies non-converting n-grams that drain budget, providing candidates for list-level negative keywords.
Theme Discovery: Surfaces high-performing n-grams that represent successful customer intent, which can be expanded into new ad groups or keywords.
Blast-Radius Protection: Uses LLM-adjudicated safety checks to prevent the accidental exclusion of brand-driving or load-bearing terms.

Quick Start

Run the search-term-ngrams skill to analyze the last month of search query data and generate a list of negative keyword candidates and expansion themes.

Frequently Asked Questions about search-term-ngrams

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

FAQPage Schema

How do I find negative keywords from Google Ads search terms reports?▼

N-gram analysis groups individual search terms into multi-word phrases (n-grams) to reveal aggregate performance patterns, surfacing budget-wasting tokens or high-converting themes that remain invisible at the single-term level.

How does n-gram analysis work for PPC search terms?▼

N-gram analysis groups individual search terms into multi-word phrases to reveal aggregate performance patterns, surfacing budget-wasting tokens or high-converting themes that remain invisible at the single-term level for PPC account hygiene.

Do I need the Porter Metrics MCP to analyze search term data?▼

Yes, you need the Porter Metrics MCP to fetch raw search-term data and process it through deterministic n-gram analysis to mine search terms for waste and winning themes.

Can I prevent accidental exclusion of brand keywords during negative keyword mining?▼

Yes, LLM-adjudicated safety checks apply blast-radius protection to prevent the accidental exclusion of brand-driving or load-bearing terms when adding mined n-grams to your negative keyword lists.

What is the best way to discover new ad group themes from Google Ads search queries?▼

The best way to discover new themes is using n-gram aggregation to surface high-performing multi-word phrases that represent successful customer intent, which you can then expand into new ad groups or keywords.

Why should I use n-grams instead of individual search terms for Google Ads optimization?▼

You should use n-grams because individual search terms often lack sufficient volume to show performance patterns, whereas n-gram aggregation reveals budget-wasting tokens and high-converting opportunities across your PPC account.