sem-ecommerce-metrics

Standardize SEM and ecommerce KPIs across Google Ads, GA4, and Meta Ads.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/Expanly/expanly-claude-code-agents --skill sem-ecommerce-metrics
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sem-ecommerce-metrics
Source: https://github.com/Expanly/expanly-claude-code-agents/tree/main/plugins/expanly-scoring-model/skills/sem-ecommerce-metrics
Command: npx skills add https://github.com/Expanly/expanly-claude-code-agents --skill sem-ecommerce-metrics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill consolidates SEM and ecommerce metrics knowledge for analytics teams, enabling faster insight and governance over campaign performance.

Core Features & Use Cases

  • Unified metric definitions: ROAS, Revenue, AOV, CTR, and other essential KPIs across Google Ads, GA4, and Meta Ads.
  • Attribution modeling & multi-channel analysis: Compare channel contributions and build blended ROAS models for accurate ROI assessment.
  • Data modeling guidance: Structuring product feeds, event data, and revenue data to support reliable analytics and scoring models.
  • Use Case: A data team reviews last-quarter campaign performance to identify top channels and adjust budgets for higher ROAS.

Quick Start

Query the knowledge base to summarize last 30 days of ad spend, revenue, and ROAS across Google Ads, GA4, and Meta Ads.

Frequently Asked Questions about sem-ecommerce-metrics

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

FAQPage Schema
How do I standardize ecommerce metrics across Google Ads, GA4, and Meta Ads?

To standardize ecommerce metrics across Google Ads, GA4, and Meta Ads, you define unified KPIs like ROAS, Revenue, AOV, and CTR. This ensures consistent multi-channel performance reporting and reliable attribution modeling for campaign analysis.

What's the best way to build a blended ROAS model for multi-channel attribution?

Building a blended ROAS model for multi-channel attribution requires comparing channel contributions across Google Ads, GA4, and Meta Ads. You standardize revenue and ad spend data sources to accurately assess multi-channel ROI and identify top-performing channels.

How does data modeling for product feeds and event data support reliable ecommerce analytics?

Data modeling for product feeds and event data supports reliable ecommerce analytics by structuring revenue information consistently. This structured data foundation enables accurate performance scoring, standardized KPI tracking, and dependable multi-channel attribution reporting.

Can I use this approach to review last-quarter campaign performance and adjust budgets?

Yes, you can review last-quarter campaign performance and adjust budgets by summarizing 30 days of ad spend, revenue, and ROAS across Google Ads, GA4, and Meta Ads. This identifies top channels to optimize budget allocation for higher ROAS.

Why do I need unified metric definitions for SEM and ecommerce analytics workflows?

Unified metric definitions for SEM and ecommerce analytics workflows are needed to govern campaign performance accurately. Standardizing KPIs across platforms prevents data discrepancies, enabling faster insight generation and reliable cross-channel ROI assessment.