Assessment of Consumer Purchase Behavior Through Digital Payment Transaction History: A Two-Month Behavioral Analytics Study Using R
Abstract
Consumer's purchasing behaviours have been altered because of the capability of Digital Payment Systems which provide the user with the ability to conduct a transaction from anywhere at any-time with a seamless transaction through UPI, Mobile Wallets, and Online Banking solutions. This is a study based on the anonymised two (2) month Electronic Transaction Histories of Two Hundred Thirty-Six (236) Respondents Who Conducted Transactions In Vijayawada, Guntur And Hyderabad. Data from these transactions were analysed using built-in R-programming techniques correlation, regression, RFM segmentation and event-impact comparison to obtain the results of this study. It has been shown that during the major promotional events (Amazon – Great Indian Festival / Flipkart – Big Billion Days) there was an increase in user spending by Thirty-Two Point Six Percent (32.6%) and the frequency of transactions increased by Twenty-Seven Point Four Percent (27.4%). Models for Transaction Frequency, Promotional Influences and Event Impacts were shown to positively predict Consumer Purchase Behaviour (R² = 0.644). These findings provide marketers with valuable data-driven insights for targeted-promotion and sales-event instruments.
Keywords
Consumer Behaviour, Digital Payments, E-Commerce Sale Events, RFM Analysis, Behavioural Analytics, R-Programming.
Citations
IRE Journals:
Guvvala Leela Kumar Reddy, Guvvala Leela Naga Karthik Reddy, Chikkam Sri Harsha, Dr. Kanagala Anusha "Assessment of Consumer Purchase Behavior Through Digital Payment Transaction History: A Two-Month Behavioral Analytics Study Using R" Iconic Research And Engineering Journals Volume 9 Issue 6 2025 Page 676-683 https://doi.org/10.64388/IREV9I6-1712696
IEEE:
Guvvala Leela Kumar Reddy, Guvvala Leela Naga Karthik Reddy, Chikkam Sri Harsha, Dr. Kanagala Anusha
"Assessment of Consumer Purchase Behavior Through Digital Payment Transaction History: A Two-Month Behavioral Analytics Study Using R" Iconic Research And Engineering Journals, 9(6) https://doi.org/10.64388/IREV9I6-1712696
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