BUSINESS ANALYTICS CASE STUDY: CUSTOMER SUBSCRIPTIONS ANALYSIS FOR BANK TERM DEPOSIT
Dataset Used: Bank Marketing Dataset
Prepared By: Ibeh Doris Chinelo
August, 2026
PROJECT OVERVIEW
This project analyzes the UCI Bank Marketing dataset to understand what drives customers to subscribe to a term deposit. The goal is to provide data-driven recommendations to help the bank improve campaign performance and increase conversion rates
Tool Used: Python-Jupyter Notebook, Pandas, NumPy, Matplotlib and Seaborn.
BUSINESS PROBLEM STATEMENT
The bank is conducting marketing campaigns to promote term deposit subscriptions, but the conversion rate remains low.
The objective of this analysis is to identify key customer characteristics and campaign strategies that drive subscription, in order to optimize targeting, reduce costs, and increase overall campaign success.
DATASET DESCRIPTION
The dataset contains 11,162 records of bank client interactions during marketing campaigns.
It includes 17 attributes covering customer demographics, financial information, and campaign
details.
The target variable is 'deposit' which indicates whether the client subscribed to a term deposit ('yes' or 'no').
• Where YES indicated that customers subscribed to a term deposit.
• Where NO indicated that Customers did not subscribe to a term deposit.
Key variables analyzed include age, job, educational level, marital status, contact method, number of contacts, and previous campaign outcome.
Data Quality: The initial data quality assessment indicated that the dataset contained no missing values and no duplicate records, making it appropriate for analysis without comprehensive data cleaning.
EXPLORATORY DATA ANALYSIS (EDA) was performed to uncover trends and relationships.
Visualizations focused on: age distribution, occupation, education level, marital status, contact method, previous campaign outcomes, number of contacts, and age group comparisons. A correlation heatmap was also used to ex …