Offer optimization using machine learning techniques with Starbucks dataset.
Every businessmen interested in maximizing their profit and that's why they have offers to attract more customers. But what if we know that how the customer will react before giving offers? Dream Come true, right? This project is using machine learning techniques to illustrate it.
Starbucks.ipynb : contains code
data/portfolio.json : contains offers metadata
data/profile.json : contains customers metadata
data/transcript.json : contains interaction customer-offers
Numpy
Pandas
Matplotlib
Seaboarn
Sklearn
Pre-processing techniques: https://pandas.pydata.org/docs/
Machine learning techniques: https://scikit-learn.org/stable/auto_examples/index.html#classification
All business related questions solved with just analysis that is in project notebook and blog, too.
Which customers have higher income? Who will be more attracted to complete offers? These are the sample questions those are answered by analysis.
You can run this ipynb with jupyter notebook or take it to Google Colab.
#Results
