π Data Projects
Jordan 2.0 Store Study
Analyzed customer behavior and store performance for Jordan 2.0 flagship store investments. Used FPA (Full-path Analysis) data to evaluate trade zones and site selection decisions.
View Project βIn-store A/B Testing on Signage Design
Innovative in-store A/B testing experiment at Shanghai Live store. Tested two signage variants (orange vs multi-color) using dwell time as the key metric. Sample size: 1,109 customers over 5 days.
View Project βInline Scalper Detection Machine
Built a machine learning model to identify scalpers ("Yellow Cows") in customer data. Used unsupervised learning to cluster patterns and separate high-value customers from scalpers based on frequency, cadence, and purchase behavior.
View Project βNike Fit Service Study
Analyzed the effectiveness of Nike Fit (foot measurement service) in stores. Evaluated customer adoption rates, service efficiency, and impact on conversion.
View Project βLive Store Traffic Analysis
Analyzed in-store traffic patterns using FPA sensor data. Provided insights on customer flow, dwell time, and peak hours for store operations optimization.
View Project βMember Day Analysis
Analyzed member engagement during special promotional events. Evaluated member acquisition, retention, and spending patterns.
View Project β365 Experience Study
Analyzed customer experience metrics across Nike stores. Evaluated service quality, customer satisfaction, and relationship with repeat visits.
View Project βLive Store Learning Program
Analyzed the effectiveness of in-store learning programs. Measured employee training outcomes and knowledge retention.
View Project βNike Live Unlock Box Study
Analyzed customer behavior and engagement with the Unlock Box promotional campaign. Evaluated conversion rates and customer satisfaction.
View Project βSanlitun Rise Store Analysis
Analysis of Nike Rise store at Sanlitun (δΈιε±―), Beijing. Evaluated store performance, customer engagement, and trade zone analysis for one of China's most iconic retail locations.
View Project βRise at XuJiaHui Potential-Consumer Data
Data analytics project for Rise store at XuJiaHui. Identified potential customers and analyzed conversion patterns.
View Project βπ½οΈ Presentations
Geospatial Analysis and Store Location Selection
Presentation on using geospatial data and machine learning for retail store site selection. Covered LBS/POI analysis, trade zone evaluation, and predictive modeling.
View Presentation βResearch Presentation 0715
Internal research presentation covering store analytics methodologies and findings. Presented to stakeholders on data-driven decision making.
View Presentation βResearch Presentation 0217
Presentation on analytical methodologies and research findings for Nike Greater China store operations.
View Presentation βResearch Presentation 1119
Additional research presentation covering advanced analytics techniques and business insights.
View Presentation β