Analysis of Customer Buying behaviour Using Data Mining
SUDHA RAMESH
, Meenakshi , Samyukhthaa Sajeevan , Sanika Mangutkar , Ganga Nutanaganti
Data Mining; Customer Purchasing behaviour; Clustering; Classification; Association Rule Mining; Consumer Analytics; Online Shopping; Marketing Strategy.
It's very important to know how customers decide what to buy, as this understanding can help companies tailor their marketing strategies and improve customer satisfaction. Businesses operating in highly competitive markets face significant challenges. Because online shopping is growing so quickly, companies gather a lot of data through platforms, digital payments, and customer databases. every day. Using traditional methods to get useful information from such large datasets is challenging, especially when companies need to analyze vast amounts of data quickly to stay competitive in the rapidly growing online shopping market. It is challenging to use analytical methods. Data mining techniques are a beneficial way to solve the problem because they let businesses find hidden patterns, correlations, and trends in customer data, which can lead to more informed decision-making and improved marketing strategies.
This research paper investigates the function of data mining in the analysis of customer purchasing behaviour. It looks at dif erent analytical methods, like clustering, classification, and Association rule mining helps businesses find patterns in their customers' purchases and group them into groups. customers based on what they like. These methods help businesses figure out which products customers often buy together and how dif erent groups of customers act in the market. The results show that data mining can make marketing strategies a lot better by
allowing businesses to tailor of ers, suggest relevant products, and foresee future
trends in buying. Companies that make good use of customer data can improve customer satisfaction and stronger ties with their target audience. The study comes to the conclusion that data mining is now a must-have for modern businesses that want to make smart decisions. Make decisions and get ahead of the competition.
"Analysis of Customer Buying behaviour Using Data Mining ", JETNR - JOURNAL OF EMERGING TRENDS AND NOVEL RESEARCH (www.JETNR.org), ISSN:2984-9276, Vol.4, Issue 4, page no.b348-b354, April-2026, Available :https://rjpn.org/JETNR/papers/JETNR2604171.pdf
Volume 4
Issue 4,
April-2026
Pages : b348-b354
Paper Reg. ID: JETNR_233345
Published Paper Id: JETNR2604171
Downloads: 00028
Research Area: Science and Technology
Country: -, -, India
ISSN: 2984-9276 | IMPACT FACTOR: 9.87 Calculated By Google Scholar | ESTD YEAR: 2023
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.87 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: RJPN (IJPublication) Janvi Wave
