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Alaire
Designed a comprehensive styling experience powered by a smart quiz algorithm, responsive layouts, and admin automation that jointly captures client preferences to generate uniquely styled personas.
Project overview
Alaire is a personal styling platform designed to deliver bespoke fashion recommendations through interactive tools like quizzes and moodboards, while offering direct communication with professional stylists. The project was built using Bubble.io, a no-code platform that supports responsive web design and enables seamless integration of multiple systems from e-commerce to real-time messaging.
My Role
As the Lead Product Designer, I was responsible for conceptualizing, designing, and implementing all the features. This involved conducting user research, developing user personas, creating wireframes and prototypes, and working closely with developers and stakeholders.
Problem Statement
Modern consumers crave personalized fashion guidance but often face these challenges:
- Limited personalization: Many styling services use generic recommendations.
- High entry barriers: Users are forced to create accounts before exploring.
- Fragmented experience: No smooth integration between quizzes, chats, and product shopping.
- Inefficient communication: Delays between users and stylists lead to poor engagement.
Alaire sought to solve this by building a personal styling ecosystem that understands user preferences, creates style personas, and provides interactive moodboards and chat-driven engagement.
Goal
To create a seamless and interactive personal styling platform that:
- Delivers personalized style recommendations through a dynamic quiz system.
- Connects users directly with a stylist via real-time chat.
- Provides shoppable moodboards tailored to users’ personas and budgets.
- Enables admin efficiency for managing user requests, moodboards, and communications.
Product Metrics
- Quiz Completion Rate: 80% of users completing the 28-question quiz.
- Conversion Rate: 80%of quiz participants who signed up post-quiz.
- Engagement Rate: High frequency of interactions with moodboards (Love/Pass/Restyle actions).
- Chat Activity: Average number of 20 conversations per user with the stylist.
- Purchase Click-Through: 80% of users who clicked shoppable links from moodboards.
Research & Analysis (How we generated the product metrics)
Before coming up with the solution, I conducted interview with prospective users and also identified friction points on existing online styling platforms
Here are the interview questions and key insights
Interview Questions
- What motivates you to trust digital styling platform recommendations?
- Do you prefer quizzes and moodboards to physical stylist session?
Key findings
- Personalization drives engagement: Users are 3x more likely to sign up when they see personalized results first.
- Visual presentation matters: Moodboards with contextual outfits (vs. item grids) led to higher approval rates.
- Direct communication increases retention: Users value stylist accessibility and feedback loops.
- Privacy & convenience: Allowing users to start the quiz anonymously reduced abandonment rates.
My Process
I followed a user-centered and iterative approach, integrating research findings into the workflow:
- Empathize: I conducted Interviews and competitor analysis to identify user expectations.
- Define: I framed the problem around accessibility and personalization gaps.
- Ideate: I created journey maps showing the path from quiz entry to purchasing.
- Prototype: I designed interactive mockups
- Test: I conducted usability test to refine the flow
Design Solution
Style Quiz page
I implemented the Anonymous quiz initiation to lower sign-up friction
Moodboard page
Two-column responsive moodboard (left: preview, right: scrollable items).
Interactive Buttons
Interactive buttons (Love/Pass/Restyle) to simulate stylist collaboration.
Admin tools
Admin tools to track and manage requests efficiently.
Prototype
Website
Admin Dashboard
Admin Dashboard (Mobile)
User Testing
Usability sessions focused on onboarding clarity, feedback controls, and admin request discoverability.
Testing Goals
- Evaluate the clarity and appeal of the quiz show
- Observe interactions with moodboards.
- Assess responsiveness and communication ease.
Findings from Testing
- 95% of testers completed the quiz once they began.
- 70% mentioned the direct messaging with the stylist made the experience feel human and premium.
- 80% found the “Love/Pass/Restyle” feature intuitive and engaging.
Results
After iterative refinement:
- Quiz-to-sign-up conversion improved by 42%.
- Admin task time reduced by 25%, thanks to automated request tracking and notifications.
- User engagement on moodboards increased by 58% due to interactive feedback tools.
- Stylist response time decreased by 30%, enhancing communication efficiency.
Challenges Faced
- Balancing personalization with simplicity: Ensuring the quiz felt intuitive despite 28 questions.
- Privacy compliance: Ensuring user data was securely handled during anonymous quiz sessions and registration.
Conclusion
The Alaire project transformed personal styling into an interactive, data-informed, and user-friendly experience. Through smart quiz algorithms, engaging visuals, and seamless communication, it successfully blended technology and creativity to redefine how users discover their style.
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