Digitalisation of payments is a global trend, with the COVID-19 pandemic having triggered accelerated adoption. While India has been at the forefront of this transition, there is little understanding of how the Unified Payments Interface (UPI), India’s real-time digital payment system, has diffused and the extent of its inclusive scaling within the country.
Phonepe is India's leading fintech platform, where Digital India is making progress by reducing the usage of money in physical form.Licensed under the CDLA-Permissive-2.0 open data license, the PhonePe Pulse Dataset API is a first of its kind open data initiative in the payments space. PhonePe Pulse is India's first interactive website with data, insights and trends on digital payments in the country.This project relies on state and district level data from PhonePe, to better understand the heterogeneity in patterns of diffusion across states and districts of India.
Dataset source : Github
Transaction Data: Provides a granular breakdown of financial activity, including transaction amounts, transaction count, geographic identifiers, and transaction type. This data is essential for uncovering payment patterns, regional dynamics, and customer spending behavior.
User Data: Consists of demographic attributes, in-app usage statistics, and preference indicators. It enables detailed profiling and segmentation, helping to assess engagement levels, predict user behavior, and identify opportunities for personalization.
Insurance Data: Covers end-to-end insurance interactions, such as policy purchases and premium contributions. It supports evaluation of market adoption, risk exposure, and evolving consumer needs within the insurance landscape.
Ways to Visualize Data
Interactive Dashboards Show data using charts, graphs, and maps that users can click, filter, and explore. 👉 Example: A dashboard with pie charts showing transactions by category, and heatmaps showing states with high PhonePe usage.
Geospatial Analysis (Maps) Use maps to see where transactions, users, or insurance purchases are happening. 👉 Example: A map of India with states highlighted based on PhonePe adoption.
Time-Series Analysis (Trends Over Time) Track how numbers change across days, months, or years to spot trends and patterns. 👉 Example: A line chart showing how online payments rise during festive seasons.
🔹 Why Visualization is Useful
Better Decisions – Data insights help plan marketing, product updates, and resources.
Happier Customers – By knowing user behavior, PhonePe can improve and personalize the app.
Fraud Prevention – Spotting unusual patterns helps detect and stop fraud.
Market Insights – Helps find new opportunities and stay ahead of competitors.
🔹 Challenges to Keep in Mind
Data Security & Privacy – User information must be protected.
Data Quality – Data should be accurate and consistent for reliable insights.
Skills Needed – Using data tools requires some technical knowledge.
🔹 Conclusion
Exploring and visualizing PhonePe data can give powerful insights to improve decisions, enhance customer experience, and detect risks. By handling data carefully and using it responsibly, PhonePe can continue to lead India’s digital payments growth.