Capstone Project: Customer Segmentation Analysis with Retail Transaction Data
Within a week, I analysed an online retail transaction dataset and proposed A/B testing plans and personalisation strategies with the aim to increase revenue by $850,000. Data was analysed using Python and strategies were recommended based on: (i) customer segments such as high value customers (HVC) identified based on recency, frequency and monetary-value (RFM) model; (ii) an interactive dashboard developed with Tableau to aid in understanding each customer segment's spending habits and; (iii) products frequently purchased together by top countries were analysed based on association rule (market basket analysis).