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).
Within 3 days, I analysed and joined multiple datasets to develop a interactive Tableau dashboard showing the performance drivers of Brazilian e-commerce (Olist) in terms of their B2B business.
The datasets are publicly available in Kaggle.
2020-2 - 2020-2
Rebranding strategies and tag management strategies for Google Merchandise Store
Based on Google Analytics data, developed rebranding strategies for Google Merchandise Store using (i) eco-friendly product range and (ii) localisation strategy for serving mobile landscape in Philippines and Indonesia. Recommendations included proposal of tag management strategy for measuring the success of the proposed plans.
2020-2 - 2020-2
Google Analytics demo account analysis and e-commerce strategies
Analyzed Google Merchandise Store’s data on Google Analytics and developed e-commerce strategy for 'Less Plastic Life' product range and made recommendations for increasing revenue by 30%