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Media-Science-Strategy-Analytics-Stack

📖 Introduction:

This repository serves as a next-generation toolkit for Data Science in Media Buying and Autonomous Strategy. While it covers foundational media planning, it is specifically architected to navigate the industry's evolution from persuading human audiences to persuading Autonomous Agents.

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This strategic analysis was curated and prompts-engineered by Hande Gabrali-Knobloch,Powered by NotebookLM based on the provided texts.

Build Status Python Domain

📂 Repository Structure

The repository is organized into seven core modules, each addressing a specific vertical of media analytics:

📂 Media-Science-Strategy-Analytics-Stack
├── 📁 01_audience_intelligence
├── 📁 02_marketing_mix_modeling
├── 📁 03_attribution_modeling
├── 📁 04_programmatic_bidding
├── 📁 05_brand_sentiment
├── 📁 06_consumer_behavior
├── 📁 07_agentic_M2M_Marketing
├── 📁 GA4_Project
└── ... (other files)

📚 References & Academic Literature

Strategic Analysis & Credits: This strategic analysis was curated and prompts-engineered by Hande Gabrali-Knobloch, Powered by NotebookLM.

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Statistical and ML methods for advertising: media mix modeling, targeting, and marketing automation for data scientists and AdTech engineers.

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