Starbucks Capstone Challenge Using FunkSVD!

Let’s start understanding and analyze Starbucks customers on how they respond to various offers so that Starbucks can in return help their customers in a better way possible!

Introduction:

Our Strategy:

The data sets for this project are provided by Starbucks & Udacity in three files:

Data From transcripts.json
Data From portfolio.json
Data From portfolio.json

Data Preparation:

We will use this cleaned_portfolio for modeling!
We will use this cleaned_profile for modeling!
Here offer is transcript

Modeling:

Algorithm:

Metrics:

Our user_item matrix looks like this:

This is just the .head() representation as to the user_item matrix I got is pretty huge! And this is with 10 latent factors(Default I considered).

Evaluation:

What will be the offer recommendations for an existing customer?

What will be the new recommendations for a potential new customer?

What percent of the gender population is considering the ‘BOGO’ offer( buy one get one) and standard discount offer?

What percent of the gender population is responding to certain platforms for offers like ‘web’ source/ ’email’ / ’mobile’ / ’social’?

Improvement:

Conclusion:

To view the code:

To connect with me via Linkedin :

I would love to connect :) See You in the next blog until then keep Hustling and stay safe!

Junior Machine Learning Engineer-Omdena | Microsoft Learn Student Ambassador-Beta | Exploring Data Science | Pythoneer | I’m curious about tech and Love chess|