Social-Music & Satisfaction
How a browsing-free, social approach to music, solves an aggravated modern-word problem
Imagine a friend who absolutely loves music. Let’s name her Tanya.
After a tiring Monday at work, she starts her commute back home, and all she wants is some good music to play in the background, without the hassle of choosing what to listen to. She goes to one of the playlists in her library, and starts playing it on shuffle. This works for her sometimes, but today, 2 songs in, a thought pops up in her head: “Why do I keep listening to the same music over, and over again? How do I find good music outside my library?”
This is the first seed of dissatisfaction: the feeling of being confined, compounded with the desire to explore. When we do not have many choices, we often experience discontentment because we feel jailed in our limited options.
Will having more options lead to a better experience? This is exactly what most major tech companies thought, and that’s exactly what drove them to create personalised feeds powered by intelligent algorithms. Maybe having more options will lead to a better experience? This is exactly what most major tech companies ponder upon all the time. And what did they do? They came up with the then groundbreaking idea of personalised feeds, tuned by their super-intelligent algorithms.
10 minutes, 3 songs, and 0 loves later, Tanya decides to go to her feed to find something to listen to, and encounters the classic curse of our modern world: choice overload. She encounters so many tempting options on the feed that she can’t even decide where to start! After scrolling through for 5 minutes, and somehow getting a track to play, she finds herself constantly thinking about whether she chose the correct playlist, or not. What if the other playlists on the feed had better music?
This is the second seed of dissatisfaction: having so many choices, that we are always thinking about whether we made the right decision, rather than actually enjoying what we have at the moment.
Here, we just saw the musical case; this dissatisfaction problem is much more pervasive. Any industry with an abundance of options is facing this problem right now. Music, social, food, travel, you name it. If this problem is so important, why have we not solved it by now?
We believe it’s because of the faulty assumption that more options, and just algorithmic personalisation, lead to a better user experience. However, in reality, satisfaction and options do not always go hand in hand. In fact, they might even be inversely correlated to each other.
Fulfilling experiences stem out of satisfaction, not options.
Over the past 3 years, we have built a browsing-free, social-music platform, to turn this insight into reality. There are 3 fundamental cornerstones to our solution, and they are reflected in each feature of the software Lishash ships:
1. A truly satisfying digital experience has to be browsing-independent.
2. We need more degrees of control, not more choices.
3. Music & Social are inseparable.
The Let All Go Button: start musical journeys effortlessly.
For instance, all Tanya needed was the browsing related heavy-lifting taken away from her. However, the current browsing centred solutions make this simply impossible! By definition, you have to choose something, before anything even plays. Now, imagine being able to just tap a button, and a personalised mix of your favourite tracks, and completely unheard music starts playing. You don’t have to scroll through any feeds, the hassle of maintaining playlists is not required, and there is no decision paralysis. That’s exactly what Lishash’s “Let All Go” button allows you to do.
Moreover, right after your session starts, a reinforcement learning algorithm takes over. If you skip tracks quickly, it learns that you are looking for something different, and if you love them, it narrows down on music with very similar characteristics to what you are loving. And the learning speed is not a week, a day, or even a few hours; the algorithm adapts to what you want in real-time!
Filter with Lishash: control, don’t choose.
With the let all go button and the reinforcement algorithm in place, we have already solved the daunting problem of starting musical journeys, even when we are not sure what to listen to. However, our listening habits are way more complex than just that; sometimes we do want a lot of control, and don’t want just the algorithms to take all decisions.
To keep herself pumped on a busy Thursday afternoon with an important deadline, Tanya wants to listen to some loud, happy music that’s not rock despite it being her favourite genre as she isn’t in the mood for it right now. She knows she can’t find a playlist satisfying these constraints and immediately opens Lishash and uses the filters there.
In Lishash you can filter any combination of genres, languages, artists, emotions, loudness, speechiness, and almost all important music traits. You can even block music features that you do not want. Tanya starts by applying valence (happiness), and loudness filters, and blocks the genre of rock. After loving a few songs, she stumbles upon a funky jazz track that she had not heard for a very long time. She decides to add a filter on the artist (The Comet Is Coming) as well, and sets the mode to discover which exclusively plays tracks that she has never heard before.
It is this feature that truly sets Lishash apart; it allows you to let go of all control or it gives you infinite control — depending on what you want. This is definitely one of the most important pillars of Lishash’s satisfaction solving process.
Social-Music: human intuition augments AI.
Furthermore, at Lishash, we believe that music is not an island; it is irrevocably intertwined with people, and with social. We all have an innate desire to share music with friends and to listen to recommendations from people we care about.
When Tanya sets the layered filters, Lishash ends up playing Space Carnival by the same artist. It reminds her of her friend, Akshay, who loves jazz and she immediately wants to share the song with him, and tell him about her experience with the song. This leads to her wanting to listen to jazz music that Akshay loves. The social aspects of Lishash allow you to share music with friends you know will like the music, you add a note or a message to the music you share and personalise it, and each song creates its own thread. Moreover, along with the filters she has already set, Lishash allows to add filters on a friend too. As soon as Tanya adds Akshay’s filter, the algorithm tunes to only play tracks shared by Akshay, that match the session filters.
Group Mode: an unprecedented real-life, social-music phenomenon.
Currently when we think of social music, the first thing that comes to mind is listening to music together with friends online, but a social music experience can (and should) be so much more! In Lishash, we augment the above online social experience, with a real-life, offline group session. Even though we listen to music in our own times via streaming, the majority of our social music listening still happens offline with friends.
It’s finally Friday night, and Tanya is a free bird now. She and her friends are going for a party, and are all set to blast some music that they all love, but that’s anything but effortless. Remember how difficult it was for her to choose what to listen to for herself in her weekly commute? Now compound that challenge with 4 very different people with wildly different music tastes, all trying to listen to music together at the same time.
To solve this problem of amplified choice overload in a group setting, Lishash has a group mode where the libraries of all members are imported, the intuitive algorithm knows what the likes of each member are, and all you have to do is press the let all go button. This gives you a hands free music experience, the music sets the mood and tempo of the conversations. Alternatively, you can apply filters in this mode to set the mood that you are going for. The possibilities are endless here.
Satisfaction and choices are inversely correlated. We are probably the most resource rich, yet the least satisfied generation to live. A part of the problem is that technology heavily influences our behaviour, and currently it is optimised at feeding us more choices, which can start a vicious loop of discontentment, and endless browsing.
Breaking this cycle, requires a fundamental behavioural shift: a browsing-independent approach, that just does not give you control, but degrees of control. Something that’s not completely reliant on algorithms, but has human intuition mixed in.
At Lishash, it is our mission to make this a reality. Become a part of the journey at www.lishash.com.