analytics-attribution

Compute marketing attribution for campaigns and channels across dimensions.

Updated Aug 23, 2026

Search Tags:#dashboards #LTV #attribution #ROI #tracking #CAC

Ready to run

npx skills add https://github.com/leduclinh7141/aitykit-marketing --skill analytics-attribution

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: analytics-attribution
Source: https://github.com/leduclinh7141/aitykit-marketing/tree/main/.claude/skills/analytics-attribution
Command: npx skills add https://github.com/leduclinh7141/aitykit-marketing --skill analytics-attribution

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill covers tracking, attribution modeling, dashboards, and ROI/CAC/LTV calculations to inform smarter marketing decisions.

Core Features & Use Cases

Analytics framework with channels, dimensions, and metrics
Attribution models (last-click, first-click, linear, time-decay, data-driven)
Marketing dashboards and ROI reporting
Cross-domain tracking and data governance

Quick Start

Set up a simple GA4-style attribution dashboard for last-click and data-driven comparison for your funnel.

Frequently Asked Questions about analytics-attribution

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

FAQPage Schema

How do I set up marketing attribution tracking across channels?▼

Attribution tracking requires implementing UTM parameters on campaign links, integrating data from your analytics platform and CRM, and selecting an attribution model (last-click, first-click, linear, time-decay, or data-driven) that matches your funnel. The Skill provides frameworks and templates to automate this setup across channels, devices, and geographies.

What's the difference between last-click and data-driven attribution models?▼

Last-click attribution credits only the final touchpoint before conversion, while data-driven attribution uses machine learning to weight each touchpoint based on its actual influence. Data-driven models reveal true channel contribution but require more historical data. This Skill lets you compare both to identify which model suits your campaigns.

How do I calculate ROI, CAC, and LTV from campaign data?▼

ROI, CAC, and LTV calculations require attributing revenue to campaigns, tracking acquisition costs by channel, and modeling lifetime value from cohorts. This Skill automates these calculations across dimensions like channel, device, and geography, then exports results to dashboards and reports for performance analysis.

Can I integrate offline conversion data into my attribution dashboard?▼

Yes. Multi-touch attribution requires connecting online touchpoints to offline conversions through CRM data integration. This Skill supports offline integration and cross-domain tracking to unify online and offline customer journeys in a single attribution and ROI model.

What data governance do I need before building attribution dashboards?▼

Proper attribution requires clean UTM discipline (consistent parameter naming), synchronized data from analytics and CRM systems, aligned KPI definitions across teams, and documented tracking rules. This Skill includes governance frameworks and exportable templates to standardize these before modeling begins.

Do I need historical data to use multi-touch attribution?▼

Last-click and linear models work immediately with minimal data, but data-driven attribution models require sufficient historical conversion volume to train accurately. This Skill supports all model types, so you can start simple and graduate to data-driven as your dataset grows.