Research Paper on Customer Segmentation Using K-Means Clustering And RFM Analysis

Research Paper on Customer Segmentation Using K-Means Clustering And RFM Analysis

Mrs. S. N. Firame (Guide)

Department of Information Technology Sinhgad Institute of Technology and Science

Pune, India

Mr. Harshvardhan Yadav

Department of Information Technology Sinhgad Institute of Technology and Science

Pune, India

Mr. Jayesh Kadam

Department of Information Technology Sinhgad Institute of Technology and Science

Pune, India

Mr. Aditya More

Department of Information Technology Sinhgad Institute of Technology and Science

Pune, India

Mr. Vinay Wakchaure

Department of Information Technology Sinhgad Institute of Technology and Science

Pune, India

Abstract— Customer segmentation, a crucial step in data driven marketing and personalization, entails breaking up a customer base into discrete groups that share characteristics or behaviors. Simple demographic divisions, like age or income, have given way to more intricate behavioral and psychographic groupings, influenced by preferences, lifestyle choices, and purchasing patterns, as businesses work to better understand their clientele. Businesses can now create highly refined customer segments using advanced analytical techniques and vast amounts of data thanks to technological advancements. These segments inform personalized customer journeys, product recommendations, and targeted marketing campaigns. This section talks about the increasing importance of customer segmentation and how machine learning has increased the range of possible uses for it, allowing businesses to make well-informed decisions supported by data.