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Enhancing Personalized Shopping With...

Bervell, Keziah,

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Enhancing Personalized Shopping With AI: Integrating User Wardrobes Into Style Recommendation Systems /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Enhancing Personalized Shopping With AI: Integrating User Wardrobes Into Style Recommendation Systems // Keziah Bervell.
Author:	Bervell, Keziah,
Description:	1 electronic resource (50 pages)
Notes:	Source: Masters Abstracts International, Volume: 86-11.
Contained By:	Masters Abstracts International86-11.
Subject:	Design. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=32038329
ISBN:	9798315745426

Enhancing Personalized Shopping With AI: Integrating User Wardrobes Into Style Recommendation Systems /
Bervell, Keziah,

Enhancing Personalized Shopping With AI: Integrating User Wardrobes Into Style Recommendation Systems /Keziah Bervell. - 1 electronic resource (50 pages)

Source: Masters Abstracts International, Volume: 86-11.

This thesis explores how artificial intelligence (AI) can be used to enhance the online shopping experience by providing personalized style and purchase recommendations through wardrobe integration. The research focuses on building Niavell, a fashion app designed to help users shop more intentionally by combining a virtual closet with AI-powered outfit suggestions. Grounded in user experience (UX) design principles, the project addresses common user pain points such as decision fatigue, lack of personalization, and disconnection between what users already own and what they are encouraged to buy.Through competitor analysis, primary research, and iterative design, the project identifies opportunities for innovation in digital fashion tools, especially around wardrobe-based recommendations and sustainable shopping behaviors. The final app prototype centers on two key features: a Virtual Closet, where users can upload and manage their existing wardrobe, and AI Recs, a recommendation system that suggests outfits or new purchases based on their current clothing items and preferences.Feedback from peers and faculty shaped the direction of the design, emphasizing low-friction interaction patterns, playful and intuitive interfaces, and the integration of technologies like reverse image search and large language models. The goal of Niavell is not only to deliver a more personalized shopping experience but also to encourage users to be more mindful of their consumption habits.This thesis ultimately contributes to the growing conversation at the intersection of fashion, design, and technology by proposing a tool that redefines what it means to shop smart in a digital-first world.

English

ISBN: 9798315745426Subjects--Topical Terms:

518875
Design.
Subjects--Index Terms:

Mobile app

Enhancing Personalized Shopping With AI: Integrating User Wardrobes Into Style Recommendation Systems /
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520 $a This thesis explores how artificial intelligence (AI) can be used to enhance the online shopping experience by providing personalized style and purchase recommendations through wardrobe integration. The research focuses on building Niavell, a fashion app designed to help users shop more intentionally by combining a virtual closet with AI-powered outfit suggestions. Grounded in user experience (UX) design principles, the project addresses common user pain points such as decision fatigue, lack of personalization, and disconnection between what users already own and what they are encouraged to buy.Through competitor analysis, primary research, and iterative design, the project identifies opportunities for innovation in digital fashion tools, especially around wardrobe-based recommendations and sustainable shopping behaviors. The final app prototype centers on two key features: a Virtual Closet, where users can upload and manage their existing wardrobe, and AI Recs, a recommendation system that suggests outfits or new purchases based on their current clothing items and preferences.Feedback from peers and faculty shaped the direction of the design, emphasizing low-friction interaction patterns, playful and intuitive interfaces, and the integration of technologies like reverse image search and large language models. The goal of Niavell is not only to deliver a more personalized shopping experience but also to encourage users to be more mindful of their consumption habits.This thesis ultimately contributes to the growing conversation at the intersection of fashion, design, and technology by proposing a tool that redefines what it means to shop smart in a digital-first world.
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650 4 $a Film studies. $3 2122736
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710 2 $a New York University Tandon School of Engineering. $b Technology, Culture & Society. $e degree granting institution. $3 3815302
720 1 $a Shalom, Dalit $e degree supervisor.
720 1 $a Bloom, Jabe $e degree supervisor.
773 0 $t Masters Abstracts International $g 86-11.
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