perf-google-search-term-audit

Analyze Google Ads search terms for wasted spend and intent cannibalization.

1|Updated Jun 22, 2026

Search Tags:#performance marketing #google ads #data-driven marketing #search term audit #ad acquisition

Ready to run

npx skills add https://github.com/perceptiv-digital/ecommerce-operator-playbooks --skill perf-google-search-term-audit

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: perf-google-search-term-audit
Source: https://github.com/perceptiv-digital/ecommerce-operator-playbooks/tree/main/skills/perf-google-search-term-audit
Command: npx skills add https://github.com/perceptiv-digital/ecommerce-operator-playbooks --skill perf-google-search-term-audit

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, google-api-python-client, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a comprehensive audit and optimization solution for Google Ads search terms, helping to identify and eliminate wasted spend and improve acquisition efficiency.

Core Features & Use Cases

Search-Term Audit: Analyze search terms for wasted spend and intent cannibalization.
Decision Rules: Apply numeric decision rules and vetoes for a defensible answer.
Data Integration: Gather evidence from various sources like search terms reports, campaigns, and ad groups.
Use Case: Identify and negate terms with high spend and zero conversions, tighten match types for relevant terms, and protect high-converting terms.

Quick Start

Run the perf-google-search-term-audit skill on your Google Ads search terms report to get a detailed analysis and actionable recommendations.

Frequently Asked Questions about perf-google-search-term-audit

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

FAQPage Schema

How do I audit Google Ads search terms for wasted spend?▼

A Google Ads search term audit analyzes search terms reports and campaign data to identify wasted spend and intent cannibalization. It applies numeric decision rules and vetoes to pinpoint terms requiring negation or match type tightening.

What is intent cannibalization in Google Ads and how do I identify it?▼

Intent cannibalization in Google Ads occurs when overlapping search terms compete and reduce acquisition efficiency. You identify it by analyzing search terms reports and ad group data to apply decision rules that isolate conflicting terms.

How do I apply decision rules and vetoes to Google Ads search terms?▼

You apply decision rules and vetoes to Google Ads search terms by evaluating search terms reports against numeric thresholds for spend and conversions. This creates a defensible audit to negate wasted spend and protect high-converting terms.

Do I need Python and Pandas to analyze Google Ads search term reports?▼

Yes, analyzing Google Ads search term reports with this approach requires Python, Pandas, and Numpy to process the data. You also need the google-api-python-client to gather campaign and ad group information directly.

What is the best way to tighten match types for relevant Google Ads search terms?▼

The best way to tighten match types for relevant Google Ads search terms is to run a data-driven audit using Python scripts. This analyzes search terms reports to protect high-converting terms while applying negations to irrelevant queries.