Project Background: Nielsen's customized e-commerce digital sample library analysis project for a client faced challenges in 2021 due to discrepancies between the data trends reflected and the client's internal understanding. The client demanded higher data quality standards, and the project also faced slow response times due to the large volume of data.

Responsibilities: Conducted labeling and visual analysis of sample library users, confirmed hierarchical logic, and calculated weightings for each level using multiple linear regression. The recalculated weightings were used to calculate e-commerce core metrics such as purchase penetration, visit penetration, and average order value. Additionally, designed an intermediate table solution to improve efficiency and address the slow response times.

Achievements: Successfully corrected data indicators to a reasonable range and resolved sample representativeness issues. Intermediate table solution reduced data query time by 80%. Renewed the client's CBA project contract for the following year


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