A curated list of awesome marketing science resources including geo incrementality testing, media mix models, multi-touch attribution, causal inference, and more from shakostats.com . Star ⭐ the repo if it helps you, and feel free to contribute your own favorite resources

A dynamic method for detecting faults in incremental and parallel builds.

The complete operating system for managing paid media accounts. Foundational SOPs and platform-specific playbooks (Meta, Google, TikTok, YouTube, Axon, Native/DSP).

Geographic Experiment design and Evaluation Tool designed to help you determine the true lift of marketing efforts.

This repository provides open-source best practices for for conducting geographic randomized controlled trials (Geo RCTs) for measuring incremental sales effect of advertising cammpaigns. It includes details on one design type in particular, a multi-armed stepped experimental design that has particular advantages in terms of statistical strength.

Simba — Bayesian Marketing Mix Modeling (MMM) platform. Media attribution, budget optimization, incrementality measurement, and scenario planning. Built on PyMC-Marketing. No-code, fully transparent, enterprise-ready.

End-to-end incrementality sandbox on M5-style retail data (DiD + Synthetic Control + placebo tests) with Streamlit dashboard.

A curated list of attribution, measurement, and marketing analytics resources. Open-source libraries, commercial platforms, research papers, datasets, and the people thinking hard about which marketing dollar caused which revenue dollar.

Lightweight, transparent marketing mix models for DTC brands. Estimate per-channel causal lift from spend + sales data — with honest diagnostics about when not to trust the result.

AI Skill for consistent, reliable 12-hour optimization of marketing campaign budgets across OpenClaw, ChatGPT Codex, and Claude.

Geo-based incrementality testing framework with synthetic control, DiD analysis, and power analysis for measuring true causal marketing lift

Measure the true incremental value of your marketing campaigns with GeoLift

Causal analysis case study measuring true incremental conversions across paid media audiences using propensity score matching.

Bayesian marketing mix modeling, multi-touch attribution, and causal inference toolkit for unified marketing measurement and incrementality analysis.

Marketing Mix Modeling with Google Meridian on GA4 data. Bayesian inference, full posterior distributions, PyMC-powered. Applied to real GA4 ecommerce data with step-by-step guide.

Official agent skills for the Lifesight MCP — causal marketing measurement inside Claude and Claude Code. Claude Code plugin + Claude.ai bundle.

A curated, vendor-neutral list of tools, libraries, research, and resources for measuring marketing effectiveness — MMM, incrementality, causal inference, and attribution.

Marketing Mix Modeling project for a DTC fertility brand — regression-based MMM, attribution comparison, and budget optimization in Python.

Paid-media measurement playbook: geo lift, MTA, incrementality, MMM, web attribution. Synthetic data, reproducible.

End-to-end retail media experimentation platform for measuring causal lift, evaluating campaign performance, and optimizing budget allocation using data-driven insights.