For our final project in QAC 151, my partner Kavya Panjwani and I analyzed skincare data. We combined skills from data analysis, consumer economics, and market research to understand how skincare products are priced and perceived by consumers.
Our project, “Analyzing Skincare Data,” used data analysis techniques to explore a dataset from Kaggle. We aimed to uncover factors influencing skincare product prices and consumer perceptions.
Our approach was risky because we applied advanced methods like REGEXEXTRACT in Google Sheets to analyze price-per-volume, which was uncommon in skincare analysis. Our findings challenged common beliefs about skincare product pricing and ingredient effectiveness.
Defense and Explanation We justified our project by showing how it helps consumers make informed choices. By examining prices and ingredients, we revealed that higher prices don’t always mean better quality. This empowers consumers to choose skincare products that meet their needs and budget.
In conclusion, our project aimed to demystify skincare product pricing using data analysis. We hope our findings make it easier for consumers to select effective and affordable skincare products. This work demonstrates how data analysis can provide practical insights into everyday decisions.
