A different approach to music personalisation — Spark, by BBC Sounds
This case study was part of a design challenge by D&AD New Blood 2019. I am not in any way affiliated to BBC or any other companies or individuals mentioned in this article.
Challenge
To develop BBC Sounds’ current offerings for younger audiences (18–35 year olds).
Time frame: 3 weeks
Overview
BBC Sounds bring together the BBC’s live and on-demand radio, music and podcasts into a single personalised experience. It provides one-tap access to the latest episodes of your favourite BBC podcasts and radio shows while introducing you to new audio from the 80,000 hours of content available. It is designed to learn from your listening habits and promises a unique experience for every individual.
My Role
UX Design | UI Design
Research
The first step was to analyse the main competitors and get acquainted with existing BBC Sounds products. I created a user flow to better understand how their products are being used.
I wanted to use the current pain points that the users have as a starting point to develop BBC Sounds’ offerings. As I did not have direct access to their target audience, I went on to the app store to look at reviews. While many praises BBC Sounds for having a wide range of content, one of the major pain points of the app was that users have trouble finding the content they are looking for, citing the lack of content categorisation on the app.
Another pain point that most people encounter is the lack of metadata in the programmes, making them unable to search for it properly. Since I can’t do anything about that as an outsider I’ve decided to ignore the pain point for the purpose of this project. The proposed idea for this project is based on the assumption that every programme comes with an extensive metadata.
Competitor Research
The main competitors of BBC Sounds are the popular music streaming services like Spotify, Apple Music, Google Play Music, Deezer, and Tidal. As BBC Sounds is a free service, I’ve decided to focus my attention on Spotify, as they are free to use as well as currently dominating the target age group. Researching on Spotify’s success, I’ve identified a few key characteristics:
1. KISS — Keep It Simple, Stup*d
Spotify made listening to music simple. When it first started, people were still fumbling around with CDs or paying iTunes for each song on their iPods. Having access to almost any music in the world sounds impossible. Spotify’s simplicity in its music experience even reduced the piracy problem that was plaguing the music industry, as it is easier to stream music on the platform.
2. Personalisation…Delivered
In July 2015, Spotify released Discover Weekly, a playlist comprising personalised new music for people to discover. It turns out to be such a success that even Spotify surprised themselves. Prior to release, Spotify had a Discover page which helps users identify new music they might like but haven’t yet heard, but hardly anyone was using. The inside-theory was that the variety of content on the Discover page made it difficult to use. Barry Schwartz, an American psychologist, says that too many choices “…produces paralysis rather than liberation. With so many options to choose from, people find it very difficult to choose at all.” When content is served on a platter, it’s much easier to be consumed.
3. Data Driven Experiences
There’s no doubt Spotify is a data-driven company. Their data-driven marketing campaign “2018 goals” (alternatively “2017 Wrapped”) created headlines, providing a humourous twist to big data. Its Discover Weekly feature, as mentioned above, is a great demonstration of how big data or algorithms can provide a very human experience.
4. Collaboration Driven Experiences
Being one of the first music platforms to have Facebook integration, Spotify isn’t shy to collaborate with other apps or brands to improve its brand experience. Its more notable partnerships include Uber, where people could curate their own playlist for the car ride, and Starbucks, where people could find out and save the music playing in their favourite coffee shop.
Target Audience Research
I first focused on the behaviours of music consumption of young people and found out that young people are an unfocused audience. In this new age of music consumption, they hold no loyalty to any particular music streaming service nor music taste. They are constantly plugged in, listening more frequently and streaming in more places. BBC Sounds just needed an edge to win the target audience over.
One thing I realised while doing research on Spotify is that they, and other major streaming services, personalise recommendations based on listeners’ favourite genres or subgenres. However, I’ve found a study conducted by Ypulse that shows that while 74% say music defines who they are, 85% of young people say their music taste doesn’t fall into one specific genre or category. They stream different kinds of music based on where they are and why they are listening.
As someone who keeps a journal for my day-to-day tasks, I wanted to know if any similar methods are used to help young people plan and manage their days. As it turns out, 73% of young adults aged 18–34 rely on digital calendars. It came as a no surprise as millennials are the first digital generation, but it made me wonder whether it is possible to integrate music listening with our calendar data, allowing audio content to be recommended based on the context and motivation for listening.
Key Goals
- To make BBC Sounds easier for people to find what they are looking for.
- To push personalisation further by making it more accurate.
Persona
I created a user persona based on the insights gathered from research, as the ideal user for the new proposed feature.
Proposed Idea
Spark is a new BBC Sounds feature that prioritises the context of listening. It integrates BBC Sounds with your calendar and location information to learn from your routine and past listening habits to give personalised recommendations based on where you are and why you’re listening.
With machine learning technology, Spark aims to recognise your listening motivation every time you tune in to improve the diverse moments of your life.
Wireframes
I created wireframes on paper, to experiment and figure out the best way to present the Spark feature and the onboarding process, also creating a “no-activity” fallback which I’ll explain more below. The screens have to be intuitive for the user so I decided to keep it simple with just a few elements on a screen.
I tested the designs on my brother and picked out the versions where both of us think are the most effective.
Final Prototype
Finally, after several iterations, these are the final screens and interactions of the new Spark feature. I’ve designed the feature based on existing assets on the BBC Sounds app, so it looks cohesive to the rest of the app.
Onboarding
The most important feature in the onboarding process is ensuring the least number of clicks people needed to connect their favourite calendar app. I went with four main calendar apps, to ensure a higher success rate of integration.
Spark Screen
I wanted the Spark feature to be the first thing people see when they open the BBC Sounds app, to have the right recommendation delivered so they don’t have to take time browsing. However, I reserved the familiarity of the app and the freedom to browse by moving existing features below the proposed feature.
“No Activity” Fallback
As calendars are usually not completely filled, I’ve created a “failsafe” for when that happens. Here, Spark will prompt users to select their activity based on where the user is.
On the BBC Sounds Website
I’ve taken the final design and made a version for the web so that the feature is available for both mobile and desktop for a seamless experience.
Reflection
I started this design challenge as my own personal goal to be able to see through a project directly on my own (without guidance from lecturers or supervisors).
What can I do better?
- Validate assumptions in a more direct manner (interviews).
- Usability test of the prototype with users.
I made several assumptions for this project, partly due to the lack of direct access to the target audience (18–35 year olds in the United Kingdom). Ideally, I would like to be able to perform interviews and usability testing on target users to ensure they welcome and accept the new feature.
At the wireframe stage I was trying out different layouts to present the feature and a lot of them just didn’t look right, I then realised I should have stick to the design system that has already been established for a more cohesive look.
As this is my first project I performed UX research on after taking video courses online, I’ve gained familiarity with the research process, but also pretty sure I’ve just scratched the surface.
