Dilliad

Dilliad

My Role

Team Lead (PM) — Project Planning, Feature Scoping, User Research

Team

Cain Susko (Sr. Dev)
Connor Leung (Dev)
Savannah Han (Dev)
Sindusara Munasinghe (Dev)
Daniel Joseph (Dev)
Mike Nguyen (UI/UX)
Steven Vuong (Sr. BA)
Marcus Hui (BA)
Cynthia Choi (BA)

Cain Susko (Sr. Dev)
Connor Leung (Dev)
Savannah Han (Dev)
Sindusara Munasinghe (Dev)
Daniel Joseph (Dev)
Mike Nguyen (UI/UX)
Steven Vuong (Sr. BA)
Marcus Hui (BA)
Cynthia Choi (BA)

Timeline

Mar 2023 - Mar 2024

Overview

Overview

As AI started to take over in early 2023, builders were finding all sorts of applications for the technology. When our team came together, we focused on how we could utilize AI as a means of improving our efficiency in our day-to-day tasks while also applying it as a learning tool. That's when our team looked into the fashion space.

Dilliad leverages AI to help people master their current wardrobe and inspire new additions. Dilliad's flagship feature designs outfit concepts based on emerging trends, colour schemes, or seasonal styles that the user might be interested in. Drawing from the user's current wardrobe and recommended options, outfit creation and fashion expression has never been easier.

PROBLEM IDENTIFICATION & RESEARCH

PROBLEM IDENTIFICATION & RESEARCH

Developing your own style and finding a fit is too hard.

Developing your own style and finding a fit is too hard.

After interviewing 6 people and surveying 50 more, we discovered that while daily outfit choices are often quick decisions, where special occasions drive people to experiment more extensively with their looks. Weather, mood, and desired aesthetic emerged as key factors, with most relying on a core rotation of staple items. While AI-powered outfit visualization resonated strongly with users, the friction of uploading and tagging wardrobe items proved to be a significant barrier. This revealed an opportunity for solutions that balance convenience with smart features like mood-based suggestions, weather coordination, and seamless wardrobe management.

After interviewing 6 people and surveying 50 more, we discovered that while daily outfit choices are often quick decisions, where special occasions drive people to experiment more extensively with their looks. Weather, mood, and desired aesthetic emerged as key factors, with most relying on a core rotation of staple items. While AI-powered outfit visualization resonated strongly with users, the friction of uploading and tagging wardrobe items proved to be a significant barrier. This revealed an opportunity for solutions that balance convenience with smart features like mood-based suggestions, weather coordination, and seamless wardrobe management.

RESEARCH & INTERVIEW INSIGHT

RESEARCH & INTERVIEW INSIGHT

Newbie or fashionista, didn't matter.

Newbie or fashionista, didn't matter.

Our initial hypothesis targeted fashion newcomers seeking guidance with style combinations. However, user interviews revealed an unexpected insight: the most engaged audience was actually fashion enthusiasts who already possessed a strong style foundation. These "fashionistas" weren't looking for basic guidance but rather new tools to expand their creative expression and outfit possibilities.

Our initial hypothesis targeted fashion newcomers seeking guidance with style combinations. However, user interviews revealed an unexpected insight: the most engaged audience was actually fashion enthusiasts who already possessed a strong style foundation. These "fashionistas" weren't looking for basic guidance but rather new tools to expand their creative expression and outfit possibilities.

Time Convenience

Time Convenience

Time emerged as the most critical pain point across all demographics. Users reported spending excessive time on outfit decisions, often resorting to night-before planning to streamline their mornings. This time burden was particularly impactful given the direct connection between clothing choices and self-image, creating a daily tension between wanting to look good and needing to be efficient.

Time emerged as the most critical pain point across all demographics. Users reported spending excessive time on outfit decisions, often resorting to night-before planning to streamline their mornings. This time burden was particularly impactful given the direct connection between clothing choices and self-image, creating a daily tension between wanting to look good and needing to be efficient.

GOALS

GOALS

Make Fashion quick and easy.

Make Fashion quick and easy.

As we started to understand our users better, some problem areas we wanted to tackle were (1) outfit generation and visualization, (2) seeing personalized outfit/clothing recommendations, and (3) making the app sociable.

As we started to understand our users better, some problem areas we wanted to tackle were (1) outfit generation and visualization, (2) seeing personalized outfit/clothing recommendations, and (3) making the app sociable.

SOLUTION

SOLUTION

Fashion shouldn't be hard.

Fashion shouldn't be hard.

After pitching to a panel of McKinsey & Co. judges, our product was picked as the winner of the demo day!

After pitching to a panel of McKinsey & Co. judges, our product was picked as the winner of the demo day!

Outfit Curation & Recommendations

Outfit Curation & Recommendations

Creating new outfit combinations from an existing wardrobe often feels overwhelming, while shopping for new pieces that complement your style can be hit-or-miss. To address this, we developed an intelligent wardrobe system that not only generates fresh outfit combinations by considering style, occasion, and weather, but also provides curated shopping recommendations that align with the user's aesthetic and fill genuine gaps in their wardrobe.

Creating new outfit combinations from an existing wardrobe often feels overwhelming, while shopping for new pieces that complement your style can be hit-or-miss. To address this, we developed an intelligent wardrobe system that not only generates fresh outfit combinations by considering style, occasion, and weather, but also provides curated shopping recommendations that align with the user's aesthetic and fill genuine gaps in their wardrobe.

Shareable Galleries and Collections

Shareable Galleries and Collections

We built a comprehensive outfit library that combines user-created looks, AI-curated selections, and community-shared styles, enabling users to both organize their fashion inspiration and discover new combinations from a trusted, personalized source.

We built a comprehensive outfit library that combines user-created looks, AI-curated selections, and community-shared styles, enabling users to both organize their fashion inspiration and discover new combinations from a trusted, personalized source.

AI-Generated Inspiration

AI-Generated Inspiration

Our trend-based outfit generator analyzes emerging fashion trends, seasonal styles, and color palettes to suggest fresh outfit concepts that align with both current fashion movements and the user's established preferences.

Our trend-based outfit generator analyzes emerging fashion trends, seasonal styles, and color palettes to suggest fresh outfit concepts that align with both current fashion movements and the user's established preferences.

REFLECTION

REFLECTION

What is product management?

What is product management?

Going into this project, I was staffed as the product manager after a stellar year creating and managing Sift. But, to be completely honest, I didn't really know what a product manager does or what effective product management looked like. I was still new to this whole tech thing.


Hailing from a business/design background, I had the fundamentals; however, managing a development team would be a completely new experience. There were a lot of "break this down for me," "what does that mean," and "what can work for you." I am very thankful to each of my devs for being so patient and understanding as we tackled our first AI project together.


In retrospect, I was a terrible PM. But, all the hardships we had told me a lot about what I need to do in the future if I wanted to pursue more PM experiences. We all have to start somewhere.


Dilliad was a project that I really wanted to succeed. It was an idea I was fully passionate about, and I thought it had the legs to break into the smart fashion market. I wanted to use it so bad, I have no clue on how to dress myself. And the more I told others about the project, the more they wanted to use it, too! Unfortunately, the project had to come to a close after our pitch, but seeing similar apps coming forth validated that we had something special.


Shout out to STYL! Seeing them grow and accomplish everything we set our eyes on was really fun.

You can just do things.

You can just do things.

You can just do things.

Projects

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