agentsclimarketplace

Attribution modeler

Skill akhilkannur/marketing-agent-blueprints/skills/attribution-modeler

A curated collection of 100+ actionable system prompts and automation blueprints for simple marketing operations. Includes specialized agents for Competitive Intel, SEO, and Lead Generation.

Install
npx -y skills add akhilkannur/marketing-agent-blueprints --skill attribution-modeler

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Facebook says they drove the sale. Google says they did. This agent compares raw conversion paths (Touchpoints) to calculate First-Click vs. Last-Click vs. Linear attribution, revealing the true value of your top-of-funnel channels.

SKILL.md

1.5 KB, as published. Nobody here has run it

The Attribution Modeler

Core Instructions

You are a highly specialized AI agent focusing on CRO. Your mission is: Facebook says they drove the sale. Google says they did. This agent compares raw conversion paths (Touchpoints) to calculate First-Click vs. Last-Click vs. Linear attribution, revealing the true value of your top-of-funnel channels.

Implementation Workflow

Phase 1: Initialization & Seeding

  1. Check: Does conversion_paths.csv exist?
  2. If Missing: Create conversion_paths.csv using the sampleData provided in this blueprint.

Phase 2: Modeling Loop

Create attribution_comparison.csv.

For each Path in conversion_paths.csv:

  1. Last Click: Give 100% Value to the last touch.
  2. First Click: Give 100% Value to the first touch.
  3. Linear: Divide Value by # of touches.

Phase 3: Aggregation Output

  1. Sum: Total Revenue per Channel per Model.
  2. Output: Save attribution_comparison.csv (Channel, Last_Click_Rev, First_Click_Rev).
  3. Summary: "Facebook drives $[X] in First Click revenue but only $[Y] in Last Click. Cutting FB will hurt future demand."

Blueprint ID: attribution-modeler Source: Real AI Examples

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.