mx-ppc-relevance-check

Name: mx-ppc-relevance-check
Availability: InStock
Author: MixShift

Classify PPC search terms and ASIN targets as Relevant, Borderline, or Irrelevant.

2|Updated May 13, 2026

Search Tags:#brand context #ppc #relevance classification #search term #asin target

Ready to run

npx skills add https://github.com/miXshift/mx-claude-plugin --skill mx-ppc-relevance-check

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: mx-ppc-relevance-check
Source: https://github.com/miXshift/mx-claude-plugin/tree/main/plugins/mixshift-ai/skills/mx-ppc-relevance-check
Command: npx skills add https://github.com/miXshift/mx-claude-plugin --skill mx-ppc-relevance-check

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires brand context file, MySQL database, browser, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the classification of search terms and ASIN targets for PPC campaigns, providing a verdict table with confidence scores and reasoning.

Core Features & Use Cases

Semantic Relevance Classification: Classifies search terms and ASIN targets as Relevant, Borderline, or Irrelevant based on brand-specific training and context.
Brand-Specific Training: Requires brand-specific training and account manager calibration for accurate classification.
Use Case: Use this Skill to classify search terms for your PPC campaigns, helping you identify terms that are most likely to convert and optimize your ad spend.

Quick Start

Run the mx-ppc-relevance-check skill with the 'run relevance check' command.

Frequently Asked Questions about mx-ppc-relevance-check

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

FAQPage Schema

How do I automate PPC relevance classification for search terms and ASIN targets?▼

You can automate PPC relevance classification by running a skill that semantically evaluates search terms and ASIN targets, outputting a verdict table with confidence scores and reasoning for each item.

Do I need a MySQL database to classify search terms for my PPC campaigns?▼

Yes, semantic relevance classification requires access to a MySQL database to store and retrieve the search term and ASIN target data needed to generate the verdict table.

How does brand-specific training affect search term relevance classification?▼

Brand-specific training calibrates the relevance classifier to your brand's context, ensuring search terms and ASIN targets are accurately categorized as Relevant, Borderline, or Irrelevant based on your unique criteria.

What is the best way to identify which PPC search terms are likely to convert?▼

The best way is to use an automated relevance check that classifies search terms into Relevant, Borderline, or Irrelevant categories with confidence scores, helping you optimize ad spend by targeting high-converting terms.

Can I use this relevance classification for both search terms and ASIN targets?▼

Yes, the semantic relevance classification process evaluates both search terms and ASIN targets, providing a verdict table with confidence scores and reasoning to help you optimize your PPC campaigns.

Why does relevance classification require a brand context file?▼

A brand context file is required to provide the specific brand training and account manager calibration necessary for the classifier to accurately categorize search terms and ASIN targets for your PPC campaigns.