Style sync
Wardrobe Management Assistant built to assist users in managing their wardrobes. Users can upload photos of their closets, and the app will offer organization tips and tailored outfit suggestions based on their style preferences and upcoming events.
As a student in the Product Design and Development course, individuals created teams to create a product, conduct user research, and formulate design, development, and business strategies to position our product for success in a competitive market.
Timeline
September 2024 - Present
Team
Graduate Students (5)
Tools
Figma, Canva
Step 1
Opportunity identification
Opportunity Screening
As a team of 5, each member was tasked with brainstorming 2 ideas each , resulting in a total of 10 distinct concepts. To build upon these ideas, we held collaborative group sessions where we shared, discussed, and refined our concepts. To facilitate the evaluation process, a group discussion was held and the top two ideas were chosen. The collective goal chosen prior, had been to develop an app to help busy individuals with productivity and organization while integrating AI tools. We ultimately identified these two key markets with significant potential for AI integration: the wardrobe management sector, which could help users streamline outfit selection and organization, and a procrastination-combating application designed to enhance productivity and focus.
Developing Opportunities
We considered a variety of questions including the following:
Is there an existing market?
Is the product possible?
Can the product be competitive?
Will the product be profitable at an acceptable risk?
Does launching this product make sense?
We gathered answers to these questions for both of the selected product opportunities to gain a better understanding of if our product is achievable or if we should circle back to previous ideas.
Opportunity Assessment was conducted with both mobile app ideas to understand the significance of the need, the effectiveness of the solution, customer acquisition challenges, team positioning/abilities, and the risks or uncertainties that come with our product ideas. We agreed that the need for tools that help users overcome decision challenges and increase efficiency is significant, particularly in environments where performance and time management are crucial. Our personalized approach will help users save time and our dual-purpose solution effectively caters to a broad audience interested in both fashion and efficiency. The key will be distinguishing the app through its AI capabilities, which provide personalized outfit recommendations based on users’ wardrobes and upcoming events. With a team consisting of academics in AI development with a strong focus on user-centric design, our team is capable of creating an app that not only functions well but also provides a delightful user experience. We can iterate and refine the product based on feedback from fashion-conscious early adopters.
Step 2
Product Planning
Competitive Strategy
Leveraging cutting-edge computer vision and AI, the app can automatically recognize and categorize clothing items from uploaded pictures, offering tailored organization suggestions. This AI-driven analysis allows for an efficient, user-specific wardrobe structure that saves time and space. In addition, the app uses machine learning algorithms to generate personalized outfit combinations based on the user's preferences, weather patterns, and social contexts (e.g., work, casual, formal). Our team’s expertise in cloud infrastructure ensures scalable performance, and the use of efficient AI models guarantees quick and accurate feedback, providing a seamless user experience.
Market Segmentation
We created a list of a few competitors that were being utilized by many other users to list out specific features.
Technology Roadmap
Step 3
MARKET eVALUATION
Market Size:
The fashion tech market is expected to reach $1.2 billion by 2026, with consumers seeking tools to streamline wardrobe management. Our app targets fashion-conscious individuals who prioritize convenience and personalization.
Market Growth Rate:
This market is growing at a CAGR of 8.1%, fueled by increasing interest in personalization and sustainable fashion. AI-powered apps that optimize wardrobe decisions are gaining traction in this expanding space.
Competitive Intensity:
Competition exists from apps like Pureple and Stylebook, but few integrate AI for real-time personalized recommendations. Our app could stand out by offering dynamic, AI-driven outfit suggestions.
Firm’s Knowledge of the Market and Technology:
Our expertise in AI and product design positions us well to create a seamless user experience. We have the technical capabilities to build an app that adapts to user style preferences and habits.
Fit with Firm’s Other Projects:
This project aligns with our mission to use AI for simplifying decision-making in daily life. It complements our focus on AI-driven personalization across various lifestyle areas, including productivity.
Potential for Patents, Trade Secrets, or Competitive Advantages:
Proprietary algorithms for style recommendations and image recognition could offer competitive advantages. This could also provide opportunities for patents, particularly in AI-driven fashion personalization.
Product Champion Within the Firm:
Our team’s interest in fashion technology and AI makes this app an exciting opportunity. The growing demand for smart wardrobe solutions makes this a perfect fit for us to champion.
Financial Model
Our team decided to implement a "freemium" model, offering a free basic subscription with limited daily outfit suggestions based on trends, closet size, and general fashion tips. In-app purchases could range from personalized sewing patterns to consultations with stylists. The premium subscription will provide detailed AI recommendations, seasonal trend tips, upcycling tutorials, and unlimited outfit suggestions. While the app primarily shows outfit combinations from a user's inventory, it will also recommend additional outfits as advertisements for our brand partnerships, generating commission revenue.
Mission statement
Product Description:
An AI-based app that assists users in managing their wardrobes. Users can upload images of their closets, and the app will provide organization suggestions and personalized outfit combinations based on their style preferences and upcoming events.
Benefit Proposition:
This application simplifies outfit selection and closet organization, saving users time and reducing decision fatigue while helping them maximize their existing wardrobe.
Key Business Goals:
Launch the application by Q1 2026.
Acquire 50,000 users within the first three months of launch.
Reach $250,000 in revenue within the first year through premium features and partnerships.
Primary Market:
Fashion-conscious individuals aged 20-40 want to optimize their wardrobes and reduce their time on outfit selection.
Assumptions:
Users are interested in improving their wardrobe management and outfit choices.
The app’s AI will provide valuable insights that users find helpful.
Constraints:
There is a need for high-quality image processing and AI accuracy in fashion recommendations.
Potential partnerships with clothing brands for user engagement.
Stakeholders:
Product design and development team
Fashion consultants and stylists
Marketing team
End users
Vision and Key Milestones:
Design Ready: Q3 2025
Prototype Ready: Q4 2025
Beta Testing: Q1 2026
Official Launch: Q1 2026