MDSTUDIOS
What is MDSTUDIOS?
Artist Showcase Website – A personal website designed to present Christina De La Cruz’s interdisciplinary work, including fine art, digital pieces, and sculpture
Seamless Buying & Inquiry Experience – The site allows visitors to explore artwork, learn about Christina’s practice, and easily purchase prints or contact the artist for commissions
Accessible and User-Friendly Design– Built to provide a clear, inviting way for fans, collectors, and potential clients to engage with Christina’s work on both desktop and mobile devices
Background
Christina De La Cruz needed an online portfolio that not only showcased her interdisciplinary artwork but also made it easier for visitors to explore, purchase, and connect with her. Existing solutions lacked a tailored experience that reflected her artistic identity while providing clear pathways for inquiries and sales.
Research Goals
To understand how potential buyers and fans engage with an artist’s website and identify opportunities to improve the browsing, purchasing, and contact experience. The goal was to create a site that balances artistic storytelling with user-friendly functionality.
Objectives
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Add an online shop
Online store to sell original paintings, prints, and sculptures
Features: categories, product details, and a secure checkout.
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Integrate a booking system
Clients can book consultations or commissions through an embedded calendar
Choose dates/times based on the artist’s availability.
Maintain portfolio functionality
Keep the portfolio as the visual centerpiece of the site
Ensure easy browsing and focus on showcasing Christina’s work
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Improve Usability & Aesthetic
Deliver a visually unified and artistically reflective design
Create an intuitive, visitor-friendly interface
Competitor Analysis
2. User Interviews
To create a more intuitive music organization experience, I conducted in-depth user interviews to uncover how listeners currently use Spotify’s “Liked Songs” and their challenges with organizing music. The insights gathered from these interviews shaped the feature concept — an effortless way to auto-generate playlists using filters like genre, mood, and listening habits
Understanding Users’ Listening and Playlist Habits
Findings (interviewed 5 users):
Common User Needs: Easy organization of liked songs, time-saving playlist creation, intuitive filter options
Motivations: Want playlists that reflect current mood, activity, or time of day
Pain Points: Manual playlist creation is tedious and often ignored despite interest
Desired Experience: Fast, personalized playlist creation with smart suggestions
Impact: Improved user satisfaction and deeper engagement with saved music
Affinity Mapping
Color-coded the key insights from each interview to reveal any patterns.
Separated the patterns into 10 groupings
Key Insights
Liked Songs are cluttered
Users often save tracks without organizing them, making it hard to revisit or create meaningful playlists later
High demand for automation
Participants want to filter and auto-generate playlists based on genre, mood, or listening patterns — saving time and effort
Personalization matters
Users value playlists that reflect their routines, emotions, or preferences, and want contextual recommendations to feel more connected
Simplicity is key
A clean, intuitive interface is essential. Users prefer features that are easy to find and use without heavy onboarding
Music is emotional and social
Playlists are often tied to moods or memories. Users also want to share and explore playlists with others
Competitor influence
Users referenced features from Pandora and YouTube Music as better at recommendation and automation, setting higher expectations for Spotify
Moving Forward
Based on user insights, there’s a clear opportunity to enhance Spotify’s "Liked Songs" feature with smarter automation, stronger personalization, and streamlined playlist creation. Moving forward, the focus will be on designing an intuitive experience that empowers users to quickly generate meaningful playlists from their saved songs — all while aligning with their moods, routines, and listening goals
3. Define
Clarifying the User’s Needs and the Core Problem
User Needs: Organize and access saved music more easily without manual playlist creation
Personas & Empathy Maps: Two personas helped define user frustrations and automation desires
Problem Statement: Manual playlist creation is tedious and “Liked Songs” quickly become cluttered. Users want a smarter, more intuitive way to organize music that reflects their habits and moods
Persona 1:
This user describes someone that moves to a new location is finding it hard to adjust to the difficult cultural dynamics of the new location
Persona 2:
This user describes someone that moves to a new location is finding it hard to adjust to the different weather climate
4. Prioritization
Generating and Prioritizing Solutions for User Needs
Project Goals
User Flows
Sitemapping
5. Prototype
Transforming Insights into Interactive Solutions
Wireframing: Created low-fidelity wireframes to visualize how users could scan their "Liked Songs" and automatically organize them into curated playlists by mood, genre, or activity.
Refinement: Developed high-fidelity mockups that brought the concept to life, focusing on intuitive playlist generation, smart filters, and a seamless music discovery experience.
Lofi Wireframes
HiFi Wireframes
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Flow 1
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Flow 2
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Flow 3
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Flow 4
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Flow 5
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Flow 6
6. Testing
Validating the Design with Usability Testing
Usability Testing: Conducted usability sessions to evaluate how effectively users could create smart playlists from their “Liked Songs.” Feedback highlighted pain points around playlist customization and automation triggers.
Iterative Improvements: Adjusted flows and copy for clarity, added visual cues, and streamlined interactions to improve usability and better align with user expectations.
User Testing Summary
The playlist creation flow was tested with 5 participants to evaluate clarity, efficiency, and feature usefulness. Overall, users found the experience intuitive and valuable, with no major obstacles.
Key Insights
All participants easily located “Liked Songs” in their library.
Users intuitively used the Create Playlist button and appreciated the filter options (genre, mood, recency).
The ability to edit playlists (e.g., rename) was clear and quick.
The filtering system helped reduce friction in playlist organization.
User Feedback Insights
“It felt smoother than apps like Pandora.”
“I wouldn’t have discovered it on my own — it needs a little more guidance.”
“Loved how easy it was to create mood-based playlists.”
Users appreciated the concept but suggested reducing text and adding icons for better visual clarity.
Opportunities
Enhance Discoverability: Use onboarding tips or visual prompts to highlight the new playlist creation feature.
Improve Filter UI: Reduce text and add intuitive icons to make the filter screen feel lighter and more engaging.
Conclusion
The new playlist creation feature aligns with user needs for simplicity and customization. With minor design tweaks and discoverability enhancements, this addition could significantly improve music organization and engagement.
7. Iteration
Refining the Design Based on User Feedback
During usability testing, users responded positively to the playlist creation flow but highlighted one key area for improvement: the Filter Screen.
Main Feedback:
“There’s too much text — icons would make it easier to scan.”
“I like the filters, but the layout feels dense.”
“A visual approach would make this faster to use.”
Design Iteration Focus:
Reduced Text Load
Replaced long filter category labels (e.g., “Filter by Mood”) with short titles or icon-only buttons.
Added Visual Cues
Introduced intuitive icons for Genre, Mood, and Recency to improve scanability.
Used tooltips or brief pop-ups for added context, only if needed.
Improved Layout Hierarchy
Grouped filter options visually using spacing and subtle dividers.
Conclusion
Feature-Driven Design: This project introduced a smart playlist creation tool, improving the user experience by making music organization faster and more intuitive.
User-Centered Tool: By focusing on real listener habits and frustrations, the feature helps users curate playlists based on mood, genre, or activity — all with minimal effort and maximum personalization.