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metrics-normalization-formatter

Normalize creator campaign metrics from multiple sources into a standardized table.

20|6|Updated Feb 19, 2026
Search Tags:#data cleaning#data normalization#creator marketing#metrics standardization#influencer analytics#cross-platform reporting
One-click install
npx skills add https://github.com/archive-dot-com/creator-marketing-skills --skill metrics-normalization-formatter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: metrics-normalization-formatter
Source: https://github.com/archive-dot-com/creator-marketing-skills/tree/main/skills/metrics-normalization-formatter
Command: npx skills add https://github.com/archive-dot-com/creator-marketing-skills --skill metrics-normalization-formatter

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill tackles the common challenge of inconsistent and messy creator campaign metrics from various sources, transforming them into a single, clean, and standardized table ready for analysis.

Core Features & Use Cases

  • Data Standardization: Normalizes disparate metrics (reach, impressions, engagement, etc.) into consistent field names.
  • Cross-Platform Merging: Combines data from Instagram, TikTok, YouTube, and third-party tools into one unified dataset.
  • Deduplication: Identifies and merges duplicate entries from different data sources.
  • Use Case: You've received campaign performance data from Instagram Insights, TikTok analytics, and a HypeAuditor report. This Skill will merge them into a single table with standardized columns like creator_handle, platform, reach, impressions, and engagement_total, making it easy to paste into your master tracker.

Quick Start

Use the metrics-normalization-formatter skill to clean and standardize the pasted creator metrics data.

Frequently Asked Questions about metrics-normalization-formatter

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

FAQPage Schema
How do I standardize creator campaign metrics from multiple platforms into one table?▼

Normalize messy creator metrics by mapping disparate fields from Instagram, TikTok, and YouTube to a canonical schema. This produces a single clean table with consistent columns for cross-platform reporting and analysis.

What is the best way to merge influencer analytics data from third-party tools with native platform exports?▼

Merge influencer analytics by combining third-party tool exports with native platform data into one unified dataset. The process maps disparate fields to a canonical schema and deduplicates entries to ensure data consistency.

Can I use this to clean and deduplicate duplicate entries from different data sources?▼

Yes, you can clean and deduplicate entries from different data sources. The process identifies duplicate records across merged cross-platform datasets and consolidates them into a standardized table with consistent field names.

Does the metrics normalization process work with Instagram, TikTok, and YouTube data?▼

Yes, metrics normalization works with Instagram, TikTok, and YouTube data. It standardizes disparate metrics like reach, impressions, and engagement from these platforms into consistent field names within a unified dataset.

How do I map disparate field names from various campaign reports to a canonical schema?▼

Map disparate field names to a canonical schema by applying data standardization techniques that transform inconsistent inputs into consistent columns like creator_handle, platform, reach, and engagement_total for analysis.

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