Bank of Corporate Exploratory Data Analysis

Bank of Corporate conducted a telemarketing campaign for one of its financial products, ‘Term deposits. The Aim is To identify the target customers and the driving factors behind a successful customer conversion for future marketing campaigns.

1. ASSIGNMENT GUIDELINES Make the changes in the PPT as you solve the parts This file contains the template for the EDA part of the project. Check the instructions added in the note section of every slide for clarity. Don’t move around any image or text box If you require more/lesser elements, be careful when you copy/delete the existing ones.

2. ASSIGNMENT THARUN R Problem Statement Bank of Corporate conducted a telemarketing campaign for one of its financial products, ‘Term deposits’, to build a long-term relationship with the existing customers. Your goal is to identify the target customers for the term deposits from the pool of the bank’s existing customers. You should also capture the key driving factors (or driver variables) behind the successful conversion of a customer, i.e., the customer opening a term deposit account with the bank.  Assignment Objective To identify the target customers and the driving factors behind a successful customer conversion for future marketing campaigns.

3. PART I : Univariate Analysis AGE The age distribution shows some negative values, which are likely errors. Apart from that , most customers are in the age range of 20-60, with a peak around the 30-40 range.

4. PART I : Univariate Analysis Job Types : The majority of customers are in management, blue-collar, and technician roles. There are also many customers with their job listed as "unknown."

5. PART I : Univariate Analysis Cash Balance : : The cash balance distribution is skewed, with most customers having lower balances. There are a few customers with significantly higher balances.

6. PART I : Univariate Analysis Term Deposit Subscription : : A large portion of the customers did not subscribe to the term deposit, indicating a relatively low conversion rate.

7. PART II : Bivariate Analysis Age vs. Subscription : : The age distribution of those who subscribed to the term deposit is quite similar to those who didn't. However , it appears that younger customers are slightly more likely to subscribe.

8. PART II : Bivariate Analysis Job vs. Subscription : : Customers in management, blue-collar, and technician jobs have higher subscription rates, while those in "unknown" job types are less likely to subscribe.

9. PART II : Bivariate Analysis Cash Balance vs. Subscription : : Customers with higher cash balances are more likely to subscribe to the term deposit. The median cash balance is significantly higher for those who subscribed.

10. PART II : Bivariate Analysis Education vs. Subscription : : Customers with higher education levels (Doctorate, Masters) seem to have higher subscription rates, while those with "unknown" education are less likely to subscribe.

11. PART III: Major insights Age Distribution Errors : The age distribution contains some negative values, indicating data errors that should be addressed. Most customers fall within the 20-60 age range, with a peak around 30-40 years. Skewed Cash Balance : The cash balance distribution is heavily skewed, with the majority of customers having lower balances and a few with significantly higher balances. Low Term Deposit Conversion : A large portion of the customer base did not subscribe to the term deposit, pointing to a relatively low conversion rate overall. Job Influence on Subscription : Customers in management, blue-collar, and technician roles have higher term deposit subscription rates, whereas those with "unknown" job types are less likely to subscribe. Higher Education Linked to Subscription : Customers with advanced education levels, such as Doctorate and Masters, show higher subscription rates, while those with "unknown" education levels have lower rates.