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SMU Data Science Review

CURLe Hair Care

Abstract

Since the early twentieth century, cosmetics production has largely been controlled by a handful of multi-national corporations. Since then, the market has expanded globally into a $532 billion a year industry. The advent of social media and E-commerce platforms has allowed smaller companies to easily find and cater to niche markets often overlooked by those larger cosmetic brands. However, as the volume and variety of hair care products grows, customers often need assistance identifying the products best suited for their individual needs. We worked with CURLe, an e-commerce start-up, to develop a classification model that recommends products to customers based on their answers to a series of survey questions. We also used a clustering technique to identify unique attributes about segments of the company’s current customer base to help CURLe personalize their consumers’ experience and provide optimal customer satisfaction.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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