Predicting customer shopping behaviour on the Google Merchandise Store during a specific timeperiod.

Companies need to take a closer look at their customer base in order to launch targeted marketing campaigns. Machine lerarning helps to effectively analyze characteristics such as access device, demographic information, surfing / consumer behavior & media usage and to derive forecasts.

AI-powered models and analytics insights to help advertisers determine the best campaigns across different e-commerce advertising channels at specific times for their customers behavior to maximize customer revenue.

Download the datasets and place it in the subfolder 📁 data ❗

☁️ https://drive.google.com/file/d/1yKfVN6l4Ge4F6xftLhcVwAuqOuez8PvP/view?usp=sharing

• Use the requirements file in this repo to create a new environment. For this you can either use make setup or the following commands:

  pyenv local 3.8.5
  python -m venv .venv
  source .venv/bin/activate
  pip install --upgrade pip
  pip install -r requirements.txt
  pip install pycaret
  python3 -m pip install nb-clean
  

Cleanup jupyter notebooks before push to GitHub:

jupyter nbconvert --clear-output --inplace my_notebook.ipynb