Stories

The graph illustrates the relationship between contact methods and education levels within the dataset. It shows that individuals with a university degree contacted via cellular methods have the highest count, while those with a basic education of 9 years have the lowest count.

The graph analyzes the relationship between housing status and job types concerning the sum of consumer confidence and consumer price indices. It reveals that a majority of respondents have housing loans ('yes'), with very few cases marked as 'unknown' regarding housing status. This suggests a strong prevalence of housing among individuals in the dataset.

The tree map illustrates the relationship between loan status and marital status in relation to the sum of duration and Pdays. The analysis indicates that married individuals tend to have a higher number of Pdays, suggesting a greater engagement with loan services compared to other marital statuses. This insight highlights the importance of marital context in understanding loan dynamics within the dataset.

The analysis examines the relationship between the outcome of previous marketing campaigns (Potcome), subscription status (Y), and the count of records per month. The findings reveal that May has the highest count, indicating a significant level of engagement during this month compared to others in the dataset. This pattern suggests that marketing efforts may have been particularly effective in May.

This dashboard presents detailed insights into the bank-full and bank datasets, which are not ordered by date. It highlights key metrics, distributions, and characteristics of the data, enabling users to explore patterns and trends without the influence of chronological ordering. This format allows for a comprehensive understanding of customer behaviors and outcomes within the datasets.

This dashboard provides a comprehensive overview of the bank-additional-full and bank-additional datasets, both of which are ordered by date. It showcases essential metrics, trends, and distributions, allowing for an analysis of how marketing campaigns have evolved over time. This chronological organization facilitates a deeper understanding of customer responses and campaign effectiveness, highlighting key insights for strategic decision-making.

This dashboard presents visualizations of all four datasets from the Portuguese banking institution, including bank-additional-full, bank-additional, bank-full, and bank. Each visualization offers insights into various aspects of the marketing campaigns, customer demographics, and responses to term deposit subscriptions. By integrating data from these datasets, the dashboard enables users to explore trends, patterns, and correlations, supporting informed decision-making and strategy development in direct marketing efforts.