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Personalised Wardrobe Service: Fashion Designers Curate Your Style

A fashion startup aiming to provide personalised wardrobe curation based on a user's past purchases and budget.

Task

Project

An MVP where users subscribe to a service that analyses their clothing purchase history and delivers tailored outfit suggestions via email or dashboard.

Challenge

The client wanted to create a unique service where fashion designers could curate personalised wardrobes for users based on their actual clothing purchases. To achieve this, they needed a system that could securely access and analyse users' email invoices from web stores, extracting key purchase details to guide the fashion recommendations.

Objectives

  • Develop an MVP allowing users to subscribe and grant access to their email for parsing clothing purchase invoices.

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  • Build a system that analyses past purchases, identifies key pieces, and matches them with user budgets.

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  • Deliver fashion designer-curated wardrobes via email and a user dashboard.

Solution

We built a Fashion Wardrobe MVP that included:

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  • Email Invoice Parsing: The system could securely access user emails, scan invoices from web stores, and extract details on past clothing purchases.

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  • Fashion Designer Integration: Using the purchase data and user-set budgets, fashion designers crafted personalised wardrobe recommendations.

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  • Email & Dashboard Delivery: Users could view their curated outfits either in their inbox or through a custom dashboard, making it easy to access their recommendations.

Impact and Results

  • Personalised Style: Users received tailored wardrobe suggestions, helping them get the most out of their current wardrobe while introducing new pieces within their budget.

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  • Scalable Model: The MVP laid the groundwork for a scalable subscription service, with a seamless user experience from email parsing to wardrobe delivery.

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  • Future Growth: The startup has since evolved into a successful business, attracting a dedicated user base interested in curated fashion experiences.

Technologies Used

  • Email parsing for secure access to user purchase history.

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  • Data analytics for clothing trends and wardrobe recommendations.

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  • Web development for user dashboard and email integration.

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