Predicting Customer Response to Different Offer Types: Starbucks Capstone Challenge

This Project is affiliated with the Data Science Nano Degree from Udacity.

Photo by TR on Unsplash

Introduction

A Brief look into the provided Data.

Project Overview

Data Exploration and Analysis

1. Profiles

Profiles grouped by Gender
Distribution of Customers based on how long they have been members of the Starbucks App
Profile Dataset after Label Encoding

2. Portfolio

Label Encoded Portfolio Data

3. Transcript

Example of Offer Influence
Example of No Influence
Response/Influence to the 2 examples above
Input Data for Modelling

Evaluation Metrics

F1 Score Formula

Modelling and Predictions

Default XGBoost Classification
Confusion Matrix Default Hyperparameters
Randomized GridSearchCV
Confusion Matrix with Tuned Hyperparameters
Feature Importance produced by XGBoost

Conclusion

Improvements

Data Science enthusiast looking to learn and share interesting ideas and approaches on Data Analysis and Machine Learning.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store