Get the data from here: GA_Data
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The 80/20 rule has proven true for many businesses–only a small percentage of customers produce most of the revenue. As such, marketing teams are challenged to make appropriate investments in promotional strategies.
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In this competition, we’re challenged to analyze a Google Merchandise Store (also known as GStore, where Google swag is sold) customer dataset to predict revenue per customer. Hopefully, the outcome will be more actionable operational changes and a better use of marketing budgets for those companies who choose to use data analysis on top of GA data.
- Customer targeting is one of the most successful techniques to induce recurring revenue. The developed machine learning methods predict customer spending and allow for a more concise use of marketing budgets, resulting in higher revenue and profitability for companies.
- Business Understanding
- Data Mining
- Quick Data Exploration
- Data Cleaning
- Feature Engineering
- Modelling - Classification
- Modelling - Regression
- Data Visualization
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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