Authors: Mayuri Dongre, Arshiya Sahare, Sarang Dumbhare
Abstract: In the age of digitalisation, a lot of transaction information is produced online, and it is significant to understand customer behaviour and market trends. This paper aims at examining the behavioural patterns in transaction data based on a data-driven approach. The information is gathered using web scraping on Flipkart, primarily in the electronic products categories of mobiles, headphones, smart watches, speakers, accessories with the help of Selenium WebDriver and Python. The obtained data is saved in the CSV format and processed with Python libraries, such as Pandas and NumPy, that allow cleaning data, eliminating duplicates, missing values, and categorizing products. Additional analysis is conducted to establish customer preferences, expenditure trends and product demand trends. The end results are presented in visual representations in the form of dashboards and reports to aid in improved business decision-making. This research assists in interpreting the behaviour of transactions and is useful in the data-driven strategies.
