QINGYU WANG

• Marketing Data Analysis & Commercial Insights: Consolidated multi-platform (Amazon, TikTok, Shein, Xiaomi Official Site) sales and customer behavior data to build automated analytical dashboards (Excel + SQL). Monitored key KPIs including conversion rate, ROI, and customer retention, providing data-driven recommendations to marketing and sales teams.
• Customer Segmentation & Campaign Evaluation: Designed post-campaign performance models and applied regression analysis to evaluate ROI across different promotion types (discounts, bundles, add-on offers). Identified high-conversion customer segments and proposed optimization strategies, improving campaign conversion rate by over 15%.
• Data Modeling & Forecasting: Built stock-out and clearance alert models based on historical sales and inventory data to forecast demand fluctuations accurately. Enabled cross-platform inventory coordination, improving turnover efficiency and reducing aged inventory by over 80%.
• Cross-functional Reporting & Strategic Support: Delivered concise, visualization-driven reports to commercial teams and senior leadership, supporting the UK market launch and pricing strategy of five key flagship products (e.g., Xiaomi 15T / 15T Pro), driving a 30% YoY GMV increase.

• Data Infrastructure and Daily Report Push: Conducted daily data acquisition and processing of Oreo, Tuc and other brand cookies, handling 100,000+ records daily from sales and user-side data. Developed SQL templates and collaborated with business teams to build core BI monitoring boards. Automated daily report generation and chart delivery using Python.
• Metrics Attribution: Monitor core metrics such as sales volume, user churn, channel side and brand side performance, identifying fluctuations and root causes of abnormal decline.
• Brand Market and Competitor Analysis: Analysed market penetration, growth rates, customer retention rate and other core indicators to interpret the market performance and trends of brands and competitors. Integrated demographic profiling like interest, region and age to uncover customer behaviour insights, informing data-driven business decisions.

Key Project: Optimising Suntory Sparkling Wine’s Sales Strategy at FamilyMart in Shanghai

• Problem Identification: Monitored November sales data for Suntory Sparkling Wine and found that the highest sales occurred on Fridays and weekends. However, company marketing activities were only implemented during the weekends, leaving Friday’s potential growth untapped.
• Solution: Recommended adjusting the marketing strategy to include online coupon distribution and SMS notifications on Fridays, along with optimising in-store displays to enhance impulse purchase conversion. Also proposed a “buy two, get one free” promotion to increase customer interest.
• Result: Post-implementation, the coupon redemption conversion rate on Fridays increased by 14.1%, and overall sales saw a 20.9% boost.

• Data Cleaning, Regression Analysis & Statistical Modelling: Standardised and processed 68,392 financial data samples for the China Household Finance Survey Project. Utilised advanced Excel functions and applied fixed-effect, Tobit, and other panel regression techniques to update 11 control variable tables. Conducted robustness tests, including heteroscedasticity and collinearity checks, to ensure data accuracy and reliability for further analysis of financial systems and economic development.
• Imputation Techniques & Data Optimisation: Applied multiple imputation regression techniques (chained, PMM, intreg) to handle missing data across 68,392 samples, achieving an 85% imputation success rate. Enhanced the quality of large datasets by optimising multiple imputation methods in Stata.