Mobile payment technology has changed how people conduct financial transactions in recent years. From contactless payment for public transportation and buying groceries to peer to peer mobile transfers after social gatherings, mobile payments solutions have made our lives easier. This shift shows a significant evolution in consumer behavior and financial technology adoption.
Understanding these differences are important for financial institutions and other technological companies to develop strategies and plan to address the digital divides in accessing financial technologies.
The visualizations utilized the 2023 Survey of Customer Diary and Payment Adoption Choice, which included approximately 4,580 respondents. After excluding entries with incomplete data, we extracted relevant columns related to mobile payment usage and demographic information, focusing on key variables including age, gender, race, highest education level, and mobile adoption status.
Data preparation involved demographic categorization. Age was grouped into meaningful brackets (18-25, 25-30, etc.). Education levels were categorized as "<HS Diploma", "HS Grad/GED", "Some College", "Bachelor's", and "Advanced Degree", consistent with the 2023 Survey of Customer Diary and Payment Adoption Choice Codebook. Bar charts were selected for demographic breakdowns to compare adoption rates between groups. Side-by-side comparisons show direct contrasts between demographic segments. A heatmap was chosen to visualize the intersection of age and income factors, displaying patterns in a digestible format. Filters were incorporated in the heatmap to explore how educational level, race, and gender influence the age-income relationship.
A series of bar charts showing mobile payment adoption rates across individual demographic factors (age, education, race, gender). This dashboard allows viewers to quickly identify which specific demographic factors show the strongest correlations with technology adoption.
The dashboard's strength lies in its clarity for audiences with varying levels of data literacy. By presenting each demographic factor independently, viewers can quickly understand the relative importance of age as the dominant predictor, while still exploring the effects of education level and other factors.
Age emerged as the strongest predictor of mobile payment adoption, with adults aged 25-30 showing the highest adoption rate (86%), contrasting dramatically with adults 65+ who adopt at much lower rates (approximately 48%). Education correlates positively with adoption rates, though less dramatically than age. Those with advanced degrees show notably higher adoption compared to those without high school diplomas.
A visualization showing the intersection of age and income factors, revealing more complex patterns that emerge when multiple demographic variables interact. The heatmap includes filters for education level, race, and gender, enabling exploration of how these factors influence the primary age-income relationship.
While the dashboard clearly presents individual variables, the interactive heatmap explores a deeper question: how do these demographic factors relate to one another? The heatmap uses color intensity to show the connection between age and income, making it easy to spot trends—such as the higher adoption of mobile payments among younger, higher-income groups.
Adding interactive filters for education, race, and gender turns this from a static chart into a flexible tool. It allows users to explore the data for themselves, uncovering patterns and testing ideas rather than just viewing the final conclusions. For example, filtering by education shows how the age-income pattern changes for those with advanced degrees compared to those without high school diplomas. The visualization effectively demonstrates that mobile payment adoption is concentrated among higher-income and younger populations, with interesting variations appearing when filtered by other demographic factors. This visualization approach reveals patterns that would remain hidden in simpler analyses, highlighting the importance of intersectional perspectives when examining technological adoption.
Tableau: Primary visualization tool to create interactive visualizations and dashboards
Google Sheets: Used for data cleaning and preparation
I see the potential to expand this project in several directions: analyzing year-over-year trends in mobile payment adoption, conducting geographical analysis with state-by-state breakdowns, and performing deeper penetration analysis. I'm also interested in identifying which platforms are most popular among different demographic groups and understanding the specific barriers to adoption faced by segments with lower usage rates.
Federal Reserve Bank of Atlanta. "Survey and Diary of Customer Payment Choice." 2023.