This project aims to find the underlying buying patterns of the customers of an automobile part manufacturer based on the past 3 years of the Company's transaction data and hence recommend customized marketing strategies for different segments of customers.
Recency-Frequency-Monetary (RFM) methodology is used to create 4 segments of customers. Insights are generated on these segments to create actionable recommendations. Strategies are devised to target promotional activities and increase their spends alongwith retention efforts.
RFM, Exploratory Data Analysis, Python, Time Series, KNIME, Excel