attribution-modeling

Name: attribution-modeling
Availability: InStock
Author: Synter

Analyze multi-touch attribution models for advertising campaigns across platforms.

1|Updated Mar 7, 2026

Search Tags:#marketing analytics #customer journey #attribution #ROAS #conversion paths #data-driven attribution

Ready to run

npx skills add https://github.com/Synter-Media-AI/free-skills --skill attribution-modeling-synter-media-ai

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: attribution-modeling
Source: https://github.com/Synter-Media-AI/free-skills/tree/main/skills/attribution-modeling
Command: npx skills add https://github.com/Synter-Media-AI/free-skills --skill attribution-modeling-synter-media-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you understand the true value of each marketing touchpoint in your customer journey, moving beyond simplistic last-click attribution to reveal how different channels work together to drive conversions.

Core Features & Use Cases

Multi-touch Attribution: Analyze conversion paths using various models (First-Touch, Last-Touch, Linear, Time-Decay, Position-Based, Data-Driven, Markov Chain).
Conversion Path Analysis: Visualize and quantify customer journeys from initial interaction to final conversion.
Cross-Channel Comparison: Understand how different attribution models redistribute credit across your marketing mix.
Use Case: Determine if your top-of-funnel display ads are truly assisting conversions attributed to bottom-of-funnel search ads, and adjust budgets accordingly.

Quick Start

Analyze the conversion paths from the provided GA4 export data using a position-based attribution model.

Frequently Asked Questions about attribution-modeling

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

FAQPage Schema

How do I analyze multi-touch attribution models for my advertising campaigns?▼

Multi-touch attribution models analyze advertising conversion paths by redistributing credit across all touchpoints. You can apply first-touch, last-touch, linear, time-decay, position-based, data-driven, and Markov chain models to quantify channel contributions accurately.

What is the best way to allocate cross-channel budgets based on conversion path data?▼

Cross-channel budget allocation relies on quantifying assisted conversions and channel contributions across the customer journey. Comparing attribution models reveals how top-of-funnel ads assist bottom-of-funnel conversions, guiding data-driven budget shifts.

Does this attribution modeling approach work with Google Ads and Meta conversion paths?▼

Yes, conversion path analysis supports platforms like Google Ads and Meta. It evaluates customer journeys across these advertising networks to understand how different channels interact and assist conversions.

How does a Markov chain attribution model quantify channel contributions?▼

Markov chain attribution models quantify channel contributions by analyzing the statistical probability of conversion paths. This data-driven approach calculates the removal effect of each touchpoint to reveal its true value in the customer journey.

Why does last-click attribution misrepresent my marketing channel contributions?▼

Last-click attribution assigns 100% of conversion credit to the final touchpoint, ignoring top-of-funnel interactions. Multi-touch attribution models solve this by visualizing complete conversion paths and quantifying assisted conversions across the journey.