marketing

mta: Accurate Marketing Attribution

Get clear marketing insights with mta.
131 stars37 forksPythonGuide quality 8/10Updated 8/30/2026100% free · open source
What it does

Mta provides clear marketing insights by attributing conversions to multiple touchpoints, enabling data-driven marketing decisions.

When to use it
  • When you need to understand the impact of each marketing channel on customer conversion
  • When you want to optimize your marketing budget allocation across different channels
  • When you need to measure the return on investment (ROI) of your marketing campaigns
Ready-to-paste prompt
python mta.py -c config.json -d data/marketing_data.csv -o output/attribution_report.json
Heads up: You need to have Python 3.8 or higher installed, as well as the required dependencies listed in the 'requirements.txt' file, to run the mta tool successfully
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

✅ Light setup

Installs with a command or two; your AI agent can do it for you.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/mta && curl -fsSL https://workflowstacks.com/api/skills/mta/claude-skill -o ~/.claude/skills/mta/SKILL.md
Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How mta: Accurate Marketing Attribution works
Codeflow
Free to inspect

Mta: Accurate Marketing Attribution is a small Python project (~950 lines across 2 code files, plus 11 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit 3 months ago, MIT license, has a test suite.

Size
Small codebase
~950 lines · 2 code files · 8 min skim
Setup
One-command install
Installs like a normal app. Reading the code is optional.
Runs on
Python
No API keys detected
Python 100%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    pyproject.toml
    Dependencies and the commands it exposes
  3. 3
    mta/__init__.py
    Inside mta/ — the main logic begins here
What's in each folder
mta/Core code — the actual logic4 files
tests/Tests — proof it works11 files
.github/CI / automation (GitHub Actions)1 files
img/Images & static assets1 files
READMEHas testsThin docsCI checksMIT licenseUpdated 3 mo ago
Quick Actions
Details
Creator
eeghor
Language
Python
Category
marketing
Published
10/31/2018

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