AI-Driven Beauty Recommendations
BeautyGPT
BeautyGPT (current working name) is an AI-powered tool designed to offer personalized beauty recommendations based on individual user input.
The goal is to help users find skincare and beauty products that align with their unique needs and preferences. This ongoing project leverages machine learning to transform the beauty shopping experience, making it more intuitive and tailored for each person.
Objective
In the beauty industry, customers often struggle to find products suited to their specific skin types and concerns. BeautyGPT is designed to close this gap by offering personalized, AI-driven recommendations, reducing the frustration of product discovery and enhancing overall customer satisfaction.
My Role
As the lead product manager for BeautyGPT, I’ve overseen the entire product lifecycle, from defining the product vision and strategy to delivering a working prototype. In preparation for demo day, I focused on creating a comprehensive Product Requirements Document (PRD) and leading the development of an MVP that demonstrates BeautyGPT’s core capabilities. This involved managing all aspects of the project myself, with future plans to explore scaling options through collaborations with data scientists and potential partnerships with beauty brands to further enhance the tool’s reach and capabilities.
Process & Solution
As the sole lead on the BeautyGPT project, I focused on defining the core problem it aims to solve and translating that into a structured Product Requirements Document (PRD). My process began with identifying key user pain points in the beauty recommendation space, followed by conducting extensive research to ensure BeautyGPT’s recommendations address a diverse range of skin types and concerns, creating a tool that feels both personalized and inclusive.
The MVP, launched in time for demo day, enables users to input their skincare concerns and receive customized product recommendations. This prototype highlights BeautyGPT’s core functionality and serves as a foundation for future iterations. Next steps include refining the user experience based on initial feedback and exploring ways to expand the tool’s capabilities.
Goal Metrics
Increase user engagement by 25% through personalized product recommendations.
Reduce product return rates by 15%, ensuring better product fit for users.
Achieve a 90% accuracy rate in product recommendations based on user feedback.
Improve conversion rates by 20% as users find suitable products faster and more efficiently.
Conclusion
BeautyGPT is set to revolutionize how customers discover beauty products, delivering personalized experiences that meet users’ unique needs while enhancing overall satisfaction.
Try the BeautyGPT demo now
