This case study was conducted as part of an internship recruitment process.
The prompt for the final case study was the following:
Your client asks that you provide them with insights into the customer base and customer behaviors that can be used to increase revenue. You should use Python, SQL, or R to explore the data.
The following files were given:
- customer_data.csv
- subscription_prices.json
The analysis was presented with the help of a slide deck (churn_analysis_presentation.pdf) during a successful final interview! You can find the code that I wrote in the notebook in this repository (analysis.ipynb).
Below are some example slides, that I created for the final presentation, with a brief explanation for each one:
Exploratory data analysis (EDA)
A summary of the interesting trends I found in the data and why it led to a customer churn/retention analysis.
Customer churn prediction
An explanation of how the data was manipulated to enable accurate customer churn prediction, and how the predictions could be used to increase customer retention.
Next steps
The next steps that the client should take to increase customer retention and profitability.
Methodology
A brief description of the methodology used to make this analysis.