okoihue/capstone

Data Scientist Nanodegree (Term 2)

Table of Contents

1. Installation
2. Project Motivation
3. File Descriptions
4. Results
5. Licensing, Authors, and Acknowledgements

Installation

Necessary libraries to run the code here beyond the Anaconda distribution of Python. The code should run with no issues using Python versions 3.*.

Additionally, below JSON files contained in the data folder are needed to runt the code

• portfolio.json - containing offer ids and metadata about each offer (duration, type, etc.)
• profile.json - demographic data for each customer
• transcript.json - records for transactions, offers received, offers viewed, and offers completed

Project Motivation

For this project, I have used the data available supplied b Starbucks for the Udacity Capstone Challenge: After some Analysing the data and you can have insight as well if you look into the Dataset part of the notebook.

I have decided to find answers to the below question:

1. What are the successful offers based on types based on different demographics (age, gender, income)
2. There s specefic group were they complete offers without knowing about them, what are the key characteristics for them?
3. Is there a specefic channel type that affects the success of the offer (Quantity Vs quality)

File Descriptions

This repository contains analysis for the Starbucks Capstone Challenge. Main file to run is (Starbucks_Capstone_notebook.ipynp) a Jupyter notebook to go over the anlysis and results genrated. Other files are the datasets used in the notebook

Results

Analysis of the findings and results can be found at the post available here.

Licensing, Authors, Acknowledgements

Must give credit to Starbucks the data provided to be analyzed. All used data are listed under the Data directory.