The following project focus on the analysis of a dataset 'Bank Marketing' which contains data about the direct marketing campaigns of a Portuguese banking institution. The goal of this project is to find ways to look for future strategies in order to improve future marketing campaigns for the bank.
View source of data: here
The project is structured as follows:
- Data Cleaning + Feature Engineering
- Exploratory Data Analysis
- Data Visualisation
- Logistic Regression Model
Language used: R
- Potentially similar micro-targeting will increase the overall effectiveness of the entire marketing company.
- Take into account the time of the company (May is the most effective)
- Increase the time of contact with customers (perhaps in a different way formulating the goal of the company). It is possible to use other means of communication.
- Focus on specific categories. The model shows that students and senior citizens respond better to proposal.
- It is imperative to form target groups based on socio-economic categories. Age, income level (not always high), profession can accurately determine the marketing profile of a potential client.
Given these factors, it is recommended to concentrate on those consumer groups that are potentially more promising.The concentration of the bank’s efforts will effectively distribute the company’s resources to the main factor - the bank’s contact time with the client - it affects most of all on conversion.