Understanding Pakistani E-commerce Consumer Behavior through Analyzing Online Shopping Data
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Bria Williams
CoPIs:
Kevin Lochard, Balla Diaite
College:
The Dorothy and George Hennings College of Science, Mathematics, and Technology
Major:
Computer Information Systems
Faculty Research Advisor(s):
Ching-yu Huang
Abstract:
This research project aims to unveil hidden patterns, relationships, and insights within Pakistan's burgeoning e-commerce sector. We aim to analyze the most readily available e-commerce dataset from Pakistan, which comprises over half a million transaction records from March 2016 to August 2018. This dataset, sourced from various e-commerce merchants, provides a comprehensive overview of online retail activities and consumer behavior in a rapidly growing digital marketplace.
By employing techniques such as ETL (Extract, Transform, Load), outlier detection, correlation analysis, and clustering, our study aims to identify significant trends, customer purchasing behaviors, and potential growth areas within the Pakistani e-commerce landscape. Specifically, our analysis seeks to quantify the extent to which discounts influence Pakistani consumers' purchasing decisions, revealing how price reductions correlate with increased order volumes and shifts in product category preferences. Additionally, we aim to uncover seasonal trends in e-commerce activity, identifying periods of heightened shopping activity and the types of products most sought after during those times.
This analysis offers valuable insights into the state of e-commerce in Pakistan from 2016 to 2018 and aids in forecasting future trends, thereby supporting startups and established businesses in strategic decision-making. Through this research, we anticipate shedding light on the intricate dynamics of online shopping in Pakistan for businesses to tailor their strategies effectively.