In simple English
This tool helps you figure out which marketing channels actually drove your sales. It processes customer journeys to show which ads or pages deserve the credit for a purchase. You can use it to replace manual spreadsheet calculations with automated reports. It is free to use under an open source licence, but you need to know some Python programming to run it. Setting it up takes about fifteen minutes.
What it is
A Python library built on Polars (a fast library for working with table data in Python) that calculates both simple and advanced marketing attribution models. It supports multiple input formats and generates interactive HTML reports or JSON exports for business intelligence tools.
What it is good for
Solo founders and marketers who want to run advanced attribution models like Markov chains or Shapley values on their customer journey data without relying on paid third-party software.
- Calculates classic heuristics like last click, first click, linear, position based, and time decay.
- Includes advanced algorithmic models including Markov chains and Shapley values.
- Generates interactive single-page HTML reports and structured JSON exports.
- Requires writing and executing Python scripts to process your data.
- Needs clean customer journey data formatted correctly before analysis.
- Documentation and README examples are primarily written in Portuguese.
manual attribution calculations in spreadsheets
pandas
source .venv/bin/activate pip install -e .[dev]