Project Background: Nielsen's customized e-commerce digital sample library analysis project for clients showed discrepancies between the amplitude of fluctuations reflected by the project data and the client's internal understanding. In 2021, the client raised higher requirements for data quality. Additionally, due to the large volume of data, the response speed to client inquiries was slow.

Responsibilities: Conducted tagging and visual analysis of sample library users, confirmed stratification logic, and used multiple linear regression to calculate weightings for each level. Re-weighted core e-commerce metrics such as purchase penetration, visit penetration, and average order value. Furthermore, designed an intermediate table solution to improve efficiency in response to the slow client inquiry issue.

Achievements: Successfully corrected data indicators to a reasonable range and resolved sample representativeness issues. The intermediate table solution reduced data query time by 80%. The contract for the next year's CBA project was successfully renewed with the client


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