This project focuses on analyzing and predicting customer behavior for a Portuguese banking institution's direct marketing campaigns.
These campaigns involved phone calls to promote term deposits, a financial product where clients invest money for a fixed period.
The aim is to predict whether a client will subscribe to a term deposit (y) based on various client and campaign-related features.
The dataset includes information gathered from multiple direct marketing campaigns conducted through phone calls. It provides insights into client demographics, campaign information, and previous interactions. By analyzing this data, we aim to uncover the factors influencing customers' decisions, enabling the bank to refine future marketing strategies.
Term deposits are a crucial product for banks, providing clients with a secure investment option while ensuring liquidity for the institution. Predicting which clients are likely to subscribe to term deposits allows banks to target their marketing efforts more effectively, improving conversion rates and reducing costs associated with reaching out to uninterested clients.
The primary objective is to build a predictive model that accurately identifies clients who are likely to subscribe to a term deposit. This will help the bank:
- Focus its marketing resources on potential subscribers.
- Tailor marketing messages to target groups based on identified influencing factors.
- Enhance the efficiency and success rate of future marketing campaigns.
By developing a well-performing model, we aim to provide actionable insights that will support the bank in optimizing its outreach strategies and achieving better results in promoting term deposits.