Turning live radio moments into personal playlists.

Designing a “Save My Set” feature for the KEXP app to help listeners capture songs from live DJ sets, preserving music discovery moments that would otherwise disappear. This was a feature-focused UX project, moving from user research through prototyping and usability testing, guided by a lean, iterative process.

Project Overview

Project Goal:

KEXP’s audience values live DJ curation, but listeners often miss song details or forget what they heard by the time they can act on it. The goal was to design a lightweight, non-disruptive feature enabling users to save songs from live sets directly in the KEXP app, preserving the discovery experience without requiring third-party tools or manual note-taking.

The challenge was to seamlessly integrate this feature into an existing app ecosystem, keeping it consistent with KEXP’s brand and technical limitations, while making it easy for listeners to find, organize, and revisit their saved songs.

My Role:

Served as the sole UX/UI designer, managing the end-to-end design process. Applied design thinking methodology to research, strategy, design, and testing, conducting user interviews, affinity mapping, and persona creation; defining task flows and feature priorities; designing wireframes and high-fidelity mockups in Figma; and running Maze-based usability tests to inform iterative improvements.


Tools:

Figma, Maze, Google Meet

The Problem

KEXP listeners regularly discover new music during live DJ sets but often lose track of the songs. Current workarounds, including using Shazam, jotting down notes, or searching online, are cumbersome and break the listening flow. The lack of an in-app saving tool results in lost engagement and diminished music discovery potential.

The Solution

The “Save My Set” feature lets users save songs in real-time or retroactively from the playlist feed. Saved songs are stored in a personal library within the KEXP app, with options to:

  • Add songs directly during a live set

  • Save multiple songs at once from a past playlist

  • Organize saved music into playlists

  • Easily export to a preferred streaming service

The feature integrates with existing playlist data, keeping the experience consistent with KEXP’s design system and requiring minimal cognitive load from listeners.

Research

User Interviews

I interviewed 5 participants (ages 22–50) who regularly listen to KEXP’s live sets and value music discovery. Interviews focused on:

  • How they currently discover and save music

  • Frustrations with existing processes

  • Desired features for saving and organizing music

  • Integration with streaming services

Key Questions:

  • What’s your current process for saving a song you hear live?

  • What stops you from saving music in the moment?

  • How important is playlist organization to you?

  • How do you revisit music you’ve saved?

Key Insights:

  • Music discovery is core - listeners view KEXP as a trusted curator and want an easy way to revisit tracks.

  • Disruption kills the moment - switching apps or tools during listening feels jarring.

  • Organization matters - users want to group saved songs by mood, DJ, or event.

  • Integration is valued - exporting to Spotify or Apple Music is a common request.

Quantitative Highlights:

  • 100% of participants said they’ve missed songs they wanted to remember while listening live.

  • 80% reported using makeshift systems (notes, screenshots, voice memos) that they found frustrating.

  • 60% said they would save more music if it could be done in one tap without leaving the app.

Affinity Map Debrief

Overview

The affinity mapping exercise revealed clear patterns in how participants listen to music, discover new tracks, identify songs, and manage their personal music libraries. It also highlighted frustrations with current tools, desired improvements, and the nuanced differences between playlist and DJ set preferences.

Key Insights

Listening Contexts & Habits

  • Music is woven into daily routines - used for focus, workouts, chores, commuting, and relaxation.

  • Many select music based on context (gym, party, cooking) or social setting (who’s around).

  • A mix of formats is used: full albums, DJ sets, mood-based playlists, and podcasts.

Music Discovery Behavior

  • Discovery is both active (TikTok, radio, concerts, YouTube) and passive (DJ sets, background music, friends).

  • Organic, serendipitous discovery is valued over algorithmic suggestions.

  • Some participants rarely seek new music, relying on live experiences or social circles.

Song Identification Methods

  • Shazam is popular but has usability issues (battery drain, poor recognition for obscure tracks, switching apps).

  • Others prefer lyric searches, Siri, or screenshots, though these methods often result in missed downloads.

  • Desire for passive, always-on recognition that integrates seamlessly into listening flow.

Saving & Organizing Music

  • Methods range from curated, mood-based playlists to minimal organization.

  • “Liked Songs” lists are often seen as cluttered and unhelpful.

  • Some enjoy curation, but others find it tedious, especially when saving music across multiple platforms.

Frustrations & Pain Points

  • Clunky workflows from discovery to saving (3-4 steps).

  • Platform silos make music management difficult.

  • Algorithms feel repetitive and uninspiring.

  • Song identification tools interrupt listening flow and fail with niche tracks.

Desired Features & Improvements

  • Passive song recognition without manual activation.

  • Direct integration from identification to saving in existing playlists.

  • AI-assisted playlist generation with vibe filters.

  • A central music hub to manage content across platforms.

  • More transparency and accessibility for song info during live or streamed sets.

Playlists vs DJ Sets

  • DJ sets are valued for intentional curation, flow, and community feel - seen as less repetitive than algorithmic playlists.

  • Many create playlists inspired by the “set” format, but still enjoy full albums.

  • Playlists are often situational or mood-specific.

Music Sharing Behavior

  • Sharing is mostly within close circles, often in person rather than online.

  • Collaborative playlists are appreciated, especially with contributor visibility.

  • Music acts as a bonding experience, often tied to nostalgia.

Design Opportunities

Based on the affinity map, the “Save My Set” feature focuses on:

  1. Passive Recognition - Always-on, non-intrusive identification that works for obscure tracks.

  2. One-Step Saving - Directly add identified tracks to specific playlists without extra navigation.

  3. Cross-Platform Sync - A unified library for managing songs across Spotify, Apple Music, etc.

  4. DJ Set Integration - Preserve track flow from live or recorded sets, maintaining curation integrity.

Conclusion

Listeners deeply value intentional curation, effortless discovery, and smooth saving workflows. The biggest gap lies in bridging discovery moments, especially in DJ sets, into organized, accessible libraries without disrupting the listening experience. “Save My Set” has the potential to be the connective tissue between live music moments and personal music collections.

Persona Highlight

Goals

  • Save songs from live sets effortlessly

  • Revisit music in a way that feels personal and organized

  • Avoid breaking the listening experience

Pain Points

  • Losing track of songs before being able to save them

  • Manual saving methods are clunky and slow

  • No central place in KEXP to store personal favorites

Competitive Audit

To understand how other platforms handle live radio, song saving, and playlist interaction, I conducted a competitive analysis of NPR MusicBBC Sounds, and SoundCloud.

The goal was to identify best practices and gaps that could inform KEXP’s “Save My Set” feature, ensuring it felt effortless for users to capture music discovery moments while listening live or revisiting past sets.

  • Strengths:

    • Rich contextual information for songs played during live and recorded broadcasts

    • Detailed show pages and past playlist archives

    • Strong focus on curation and storytelling around music

    Weaknesses:

    • No in-app save function for songs - listeners must use external tools or write them down

    • Navigation to past playlists can feel buried

    Takeaways:

    KEXP can build on NPR’s contextual depth but add the missing personal library function, making it possible to both learn about and save a song in one place.

  • Strengths:

    • Seamless integration of live radio, past shows, and podcasts

    • Ability to follow favorite shows and DJs for easy access

    • Robust search and categorization for past episodes

    Weaknesses:

    • No dedicated song-saving feature tied to live playlists

    • Users must manually seek out tracklists after listening

    Takeaways:

    The follow/favorite model works well for long-form content, but there’s an opportunity for KEXP to apply similar quick-access behavior to individual songs instead of just shows.

  • Strengths:

    • One-tap “like” system that saves tracks instantly

    • Ability to create and curate personal playlists easily

    • Social features that encourage discovery through likes and reposts

    Weaknesses:

    • Primarily on-demand streaming - lacks true live set context

    • Likes can become cluttered over time without advanced organization tools

    Takeaways:

    SoundCloud’s one-tap save function is fast and intuitive - a model worth emulating - but KEXP can differentiate by adding contextual grouping (e.g., saving within the framework of a specific DJ set).

Opportunity Identified:
Current platforms either excel in curation and context (NPR, BBC) or offer frictionless song saving (SoundCloud), but none combine both for a live DJ + playlist archival experience. The “Save My Set” feature has the potential to uniquely merge these strengths: a single-tap save action integrated into KEXP’s existing playlist feed, tied to the rich contextual storytelling of live radio.

User Flow

The main objective of creating the user flow was to map the listener’s decision-making process from the moment they heard a song they wanted to remember to successfully saving it in the KEXP app. My goal was to understand the most frictionless path from hearing a song → saving it → revisiting it later, without breaking the immersive listening experience.

By visualizing how users would move through the app, I was able to pinpoint:

  • Key interaction moments (e.g., tapping “Save” while listening live)

  • Opportunities to confirm and reinforce the save action

  • Where users might hesitate (e.g., “Where did my saved songs go?”)

Using interview data and testing patterns, I mapped two core flows:

  1. Playlist Builder - Saving songs during a live DJ set in real time

  2. Exporting the Playlist to Spotify or Apple Music

This structure informed my wireframes by:

  • Ensuring each screen had a clear single purpose (e.g., “Save song” vs. “View saved library”)

  • Keeping navigation intuitive and anchored in the current KEXP app patterns

  • Prioritizing core actions like Save early in the user journey

  • Minimizing the number of taps to save a track

The user flow helped me turn a fleeting listening moment into a repeatable, simple in-app action, laying the groundwork for a smooth, purposeful feature experience.

Liking a song

Exporting

Lowfi Wireframes

Home Screen

Add song to playlist

Playlists

Export playlist

Design Evolution

Wireframes

I started with low-fidelity sketches to explore:

  • How a “Save” icon could live unobtrusively alongside existing song data

  • Contextual save options

  • Minimal copy to keep focus on music, not menus

Early feedback and testing showed a need for:

  • Clear visual confirmation when a song is saved

  • Consistent placement of the save icon across live and archived views

  • Direct navigation to “Saved Songs” from the home screen

  • A more obvious export playlist button

Revisions & Refinements

Following user testing, several adjustments were made to address usability issues and improve clarity in key interactions. The changes focused on making core actions, like exporting sets and adding tracks to playlists, more intuitive and less disruptive to the listening flow.

Export Button - Improved Recognition

Before: Users struggled to quickly locate or understand the export function due to an ambiguous icon and placement.
After: The export button was redesigned with a clearer, universally recognizable icon and improved contrast, ensuring it stands out in the interface.
Ties to Testing: During testing, multiple participants hesitated or hovered before using export, indicating uncertainty about its function. The clearer icon reduced cognitive load and increased confidence in performing the action.

Before

“Export To” Prompt - From Pop-Up to Bottom Sheet

Before: Exporting triggered a floating pop-up modal, which broke the sense of continuity and covered too much of the screen.
After: The interaction was shifted to a bottom sheet design, creating a more modern, mobile-friendly experience that kept users anchored in the current view.
Ties to Testing: Users described the pop-up as “interruptive” and “jarring,” particularly during live listening. The bottom sheet approach was better received, as it allowed for quick action without losing context.

Before

High-Fidelity Designs

Because this feature was integrated into KEXP’s existing app, I followed their design system for typography, spacing, and iconography, ensuring:

  • Visual consistency with existing playlist elements

  • A distinct yet familiar “save” icon that didn’t compete with playback controls

  • Clear, high-contrast feedback states

Final feature elements included:

  • Save icons for songs

  • Confirmation states that reinforced successful saves

  • A “Saved Songs” library, organized chronologically by date added

After

After

Impact of Changes

These refinements directly addressed friction points surfaced during user testing, particularly around recognition over recall and minimizing interruption - two core usability heuristics. As a result:

  • Users could find and use core functions faster.

  • Task completion times for exporting and playlist management improved.

  • The listening flow remained more intact, aligning with participants’ desire for a seamless, non-disruptive music experience identified in the affinity map.

Visual Design & Visual Consistency

For the “Save My Set” feature out goal was to maintain the app’s established look and feel so the feature would feel native rather than bolted on.

The new screens borrow directly from the app’s existing visual language:

  • Typography, color palette, and spacing were matched precisely to the original UI to create seamless transitions between old and new screens.

  • The bottom sheet design for export replaced the earlier pop-up approach, making it more mobile-friendly and consistent with other in-app interactions.

  • Iconography for the export and playlist buttons was updated for higher recognizability while staying stylistically aligned with the existing icon set.

This alignment was intentional, by mirroring established visual patterns, users could intuitively navigate the new “Save My Set” flow without a learning curve. In user testing, participants reported that the feature “felt like it had always been part of the app,” confirming that the visual consistency supported both usability and adoption.

Hifi Mockups

Prototype

Export complete

Liking a song

Exporting

Home Screen

Add song to playlist

Playlists

Export playlist

Usability Testing

Usability Test Objective

The goal was to validate the feature’s clarity, discoverability, and speed, specifically:

  • Could users find and use the “Save” function without breaking their listening flow?

  • Did users understand where to find their saved songs afterward?

  • Did the save confirmation feel reassuring and consistent?

Wireframe Testing (Maze)

  • Participants: 5

  • Tasks: Save a live song, save to a past playlist, export playlist to Spotify

  • 100% successfully saved a song to a playlist

  • 80% found the saved songs library

High-Fidelity Testing (Maze)

  • Participants: 5

  • Same tasks as wireframe testing

  • 100% task completion

  • 90% said they would use the feature regularly

Feedback Highlights:

  • “I like that I can save it without leaving the set.”

  • “The confirmation pop-up makes me feel sure I didn’t miss it.”

  • “This is way easier than screenshotting or Shazaming.”

Validated through testing:

  • The need for instant visual feedback when saving

  • The benefit of keeping the feature passive and background-friendly

  • The importance of library placement in primary navigation

Final Thoughts

“Save My Set” fills a key gap by letting KEXP listeners easily capture live music discoveries without interrupting their experience. Designing for immediacy and low friction was essential to fit the live radio context.

This feature strengthens user engagement and deepens connection to KEXP’s curated content. Future enhancements like streaming integration and better organization will make it even more valuable.

This project shows how a simple, user-centered feature can greatly improve loyalty and satisfaction by meeting real listener needs.

Impact & Lessons Learned

What Worked:

  • Designing for low disruption maintained the magic of live listening

  • Leveraging KEXP’s existing design system made the feature feel native

  • Adding confirmation states increased user confidence

Challenges:

  • Balancing feature visibility without cluttering the UI

  • Keeping interaction consistent across live and past playlist contexts

  • Ensuring quick performance

Lessons Learned:

  • Even small features require deep attention to context of use

  • Visual consistency drives discoverability in familiar apps

  • Designing for the “I’m busy doing something else” mindset is crucial for live media

Next Steps:

  • Enable tagging or custom labeling for songs

  • Explore a “Save entire set” one-tap feature

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