The Art of Marketing Science is a blog focused on applying data science in marketing, sharing from concepts to practical code for readers. Here we explore different ways to apply data science to marketing problems, think about marketing data, and implement various algorithms in Python & R.

Data science is widely applied in marketing as every company on this planet is looking to better understand their marketing efforts in hopes to reduce inefficiencies and maximize effectiveness but there is a lack of resources covering practical application of data science in marketing. This blog is geared towards data scientist currently working in marketing and marketing analysts looking to expand beyond traditional analytics.

Marketing is a complex domain and I am just scratching the surface here. My hope is that readers will learn something from this blog and I can connect with other folks working in this domain space.

Are you currently a data scientist in marketing? Do you have specific marketing science knowledge that you'd love to share? This blog is currently open to guest blogging! If you're interested in contributing as a guest blogger

1. Please open up an issue in the github repo describing your topic.
2. Submit your article and/or Jupyter/R notebook
3. I'll Peer review prior to merging

Similarily, if there is a topic you'd like to discuss or want me to write about, please open up an issue in the github repo.