Tunes2Go

Imagine you want to unwind by traveling to someplace that’s either familiar or new. You look through your Spotify playlists to set a mood, but you realize that you want to find new playlists. You open Tunes to Go to receive playlists that others in the area recommend. When we were first brainstorming ideas, we wondered if there’s ever been an idea that’s never been explored before. Once we realized that it would be hard to create an original idea, we decided to extend existing applications that we all enjoy, such as Spotify. Then we came up with the following: Why don’t we create a music experience that’s interactive based on a user’s location?

Now, this is an entertaining idea, but why did we decide it would benefit others? Well, we felt this would be able to provide the opportunity for Spotify users to bond through the power of music. And the best way users can get to know new people is to explore new places. Sharing playlists through the use of geolocation bridges the gap and joins those ideas together.

In our first pitch, we advertised our idea to our professor and teacher assistants by going in depth with the research we put into our idea. From there, we explained further in the deck that we wanted to bring the following ideas to life with Tunes to Go:

• “Pokéstop”-like bundles of songs/playlists are placed in order to reduce clutter and only reveal when in range.  Incentivizes discovery and interaction

• Key social aspects like profile info, follow or blocking as well as who are the authors of each playlist are also made known here. Although anonymity is also an option

• Car mode is also available for ease of access and the safety of the driver if they want to interact. Friends feed filters music only from people they follow and Default allows recommendations from strangers

Our idea was approved, however, we were told to also make sure to provide an interactive experience for our app since music itself is a personal form of expression and a way that many people can bond or communicate through.

We chose to implement this recommendation into our design by providing a comment section for users to be able to recommend each other songs to add to the playlist and express their opinions on the playlists. This is to allow users to be able to bond with people who have posted the pin points through conversation. We also want to be able to allow users to react to certain playlists with emojis or upvoting/downvoting so they can rank playlists as well.

Once we completed our prototype testing, we asked our participants to answer a post survey discussing what they liked and didn't like. From the questions we asked, we learned the following:

• How well do you think our prototype simulates the experience of using Tunes to Go in real life?​

• Was there any vibe that was missing or any playlist that did not match the environment?

• If Tunes to Go had a feature that allowed you to upvote or downvote playlists/songs, would you use it? ​

• What did you least like about Tunes to Go?​

And from these questions we got answer that gave us more direction to develop towards:

• Allowing users to add their song choices into an interactive playlist

• Allowing users to have an Anonymous mode 

• Adding an Upvote/Downvote function → hypothetically speaking, if a user downvotes a song on their end, it will be skipped/greyed out for them when they listen to the playlist

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Our group conducted Secondary User Research.

This was done through conducting stakeholder interviews of real people that were in our target demographic and reviewing literature we combed through on google scholar. We found that users are motivated to listen to music/seek new music based more off mood and activity in a particular location rather than the particular location itself. Our findings in the literature were that enhancing location based sharing responsiveness, simple user interfaces, using and improving GPS navigation to enhance trust can help building a stronger community and help facilitate social interaction. 

Our app focuses on gps navigation, real-time location tracking, music player and data, and social interaction and profiles so we put focus on brainstorming where the user can trust the functionality, privacy, and entertainment gain when using our app– we want to create a positive experience that intuitive and interesting. Taking inspiration from contextual listening in art exhibits and a story-telling music sharing location-based app, we want to immerse the user into the emotions that another user experiences through music. With better GPS navigation and tracking constantly being improved, like Google maps and Pokemon Go, we aim to create a smooth and fun experience of finding pins of song playlists scattered around a location

For our initial idea, we want to piggyback off of Spotify to host our idea, but for the sake of creating a low-fidelity prototype we decided to implement our idea through the use of Figma. Using 30 participants, we mimicked the use of our idea by creating a map. From there, participants would be able to hop onto the Figma file and travel to different locations. In each location, there was a link where users can interact with premade playlists -- each with their own vibe. We also made use of the commenting function on Figma to be able to create interactions.

After understanding the user feedback we received for both prototypes, we designed a high-fidelity interface through which users would engage in the social interactions we've computed. Our high-fidelity prototype has 5 key features. We were directly inspired by Pokémon Go's "Pokéstop" feature.  The pin points on the map represent locations with playlists that match the environment. Users will be able to interact with pin points that they are located near. Once users interact with the pin point, they are shown different playlists that are inspired by different moods that are appropriate for the particular location. In this case, the moods are exactly the same as the ones we used in our prototypes for La Jolla Shores. We implemented Spotify’s current ‘like’ vs. ‘hide’ features to help users curate the collaborative playlists to their liking, as expressed in prototype 1. We also recognize that allowing users to ‘hide songs’ rather than downvoting them will ensure that no user feels judged or discouraged from adding songs if others disagree with their recommendations. We also included an anonymity mode so users could recommend moods/songs and react to playlists without judgment. This feature is meant to help the users that expressed how they felt shy or unsure of themselves when collaborating on playlists.