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marketing-reports

Aggregate and normalize marketing campaign metrics from LinkedIn, Google Ads, Meta, and Microsoft Ads.

Updated Feb 14, 2026
Search Tags:#reports#analytics#marketing#api#cross-platform#benchmark#campaigns
One-click install
npx skills add https://github.com/Shakudo-io/opencode-skills --skill marketing-reports
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: marketing-reports
Source: https://github.com/Shakudo-io/opencode-skills/tree/main/marketing-reports
Command: npx skills add https://github.com/Shakudo-io/opencode-skills --skill marketing-reports

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires httpx, google-ads, facebook_business, bingads, python-dotenv, and includes scripts (resource) components.

What problem does it solve?

Marketing teams struggle to consolidate cross-channel campaign data and derive actionable insights from disparate advertising platforms. This Skill centralizes queries to LinkedIn, Google Ads, Meta (Facebook), and Microsoft Ads to deliver a unified view of campaigns and performance metrics.

Core Features & Use Cases

  • Unified cross-platform querying: Retrieve campaigns, spend, impressions, clicks, and conversions across channels into a single data model.
  • Normalized analytics model: Outputs a common Campaign schema with computed metrics like CTR and CPC for benchmarking.
  • Use Case: Build quarterly marketing reports, optimize budgets, and compare platform performance side-by-side.

Quick Start

Run the unified cross-platform campaigns query to fetch marketing data for the last 7 days and review the resulting JSON

Frequently Asked Questions about marketing-reports

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

FAQPage Schema
How do I consolidate cross-platform marketing campaign metrics from Google Ads and Meta?▼

Cross-platform marketing campaign metrics are consolidated by querying each advertising platform's API, retrieving spend and conversions, and normalizing the results into a unified Campaign data model with computed metrics like CTR and CPC for side-by-side channel benchmarking.

What is the best way to normalize LinkedIn and Microsoft Ads data into a single report?▼

Normalizing LinkedIn and Microsoft Ads data involves querying both platforms via their APIs, mapping disparate campaign fields into a common schema, and computing standardized metrics to generate a unified cross-channel performance report.

Do I need API credentials configured to run cross-channel campaign analytics?▼

Yes, API credentials configured for each advertising platform are required. The process reads credentials for LinkedIn, Google Ads, Meta, and Microsoft Ads from your environment to authenticate and successfully query each platform.

Can I benchmark campaign performance across different advertising platforms for specific date ranges?▼

Yes, campaign performance can be benchmarked across different advertising platforms for specified date ranges. The system queries each channel for the requested timeframe and computes normalized metrics like CPC and CTR to compare results side-by-side.

What computed metrics are included when I aggregate marketing data from multiple ad networks?▼

When marketing data is aggregated from multiple ad networks, the output includes a normalized Campaign schema with computed metrics such as Click-Through Rate (CTR) and Cost-Per-Click (CPC) to facilitate cross-platform performance comparisons.

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