devtools

Optimize with Awesome-Marketing-Science

Name: Optimize with Awesome-Marketing-Science
Author: shakostats

Get curated marketing science resources for data-driven decisions. For startup founders in marketing and advertising.

69 stars10 forksHealth Score 8/10Updated 5/6/2026100% free · open source

What it does

Awesome-Marketing-Science provides a curated list of marketing science resources for data-driven decisions in marketing and advertising

Install / run

Visit https://github.com/shakostats/Awesome-Marketing-Science and star ⭐ the repository to show support

When to use it

•When you need to understand geo incrementality testing for location-based marketing campaigns
•When you want to implement media mix models to optimize your advertising budget
•When you need to learn about multi-touch attribution to analyze customer journey

Quick start

1Browse the README to find relevant marketing science resources
2Explore the curated lists of resources, such as geo incrementality testing and media mix models
3Click on a resource to learn more about it, such as a blog post or research paper
4Contribute your own favorite resources by submitting a pull request to the repository
5Star ⭐ the repository if it helps you to show support and encouragement

Ready-to-paste prompt

Search for 'geo incrementality testing' in the Awesome-Marketing-Science repository to find relevant resources

Heads up: Note that this repository is a curated list of resources and not a tool that requires an API key or runtime version, but you may need to create a GitHub account to contribute or star the repository

Saves to your device

Topics

advertising

causal-inference

causality

geo-experiment

geo-incrementality

geo-testing

geotesting

incrementality

marketing

marketing-analytics

marketing-machine-learning

marketing-mix-modeling

marketing-science

marketinganalytics

martech

media-mix-modeling

mmm

How Optimize with Awesome-Marketing-Science works

Codeflow

Free to inspect

Optimize with Awesome-Marketing-Science is a documents-only repository (1 doc file) — something you read, not something you run. There is nothing to install. Last commit 4 months ago, MIT license.

Size

Documents only

1 document · 11 min skim

Setup

Nothing to install

A guide / curated list. Just read it and follow the links.

Runs on

Nowhere — you read it

A reading resource, not a program.

Where to start reading