Snapwave Originals — An Introduction — Part I
Inspiring stories at the intersection of music and photography.
We started Snapwave Originals to share inspiring stories, insights, and research findings at the intersection of music and imagery. There’s a host of stories on the way from recording artists, photographers, visual creatives, designers, PhD researchers, brands, and creative engineers sharing their perspectives and experiences. Follow us to stay tuned!
To start, I’ll tee off by sharing my personal story and insights as we begin to peel back the onion.
Music and images. For the last 3 years I’ve been exploring the connections between these two mediums with an intense curiosity.
While there are inherent differences with one being auditory and one visual, music and images have so much in common with how we viscerally experience them, and in the ways they complement each other to create nothing short of magic.
Music evokes emotion. Images evoke emotion. When you combine the two, it creates emotional synergy, where the sum is greater than its parts.
Both music and images are also artifacts we collect. We collect them in our memories, in our hearts, and in our digital lives, so we can access them any time, to relive them over and over again. In this way, both are experiences driven by nostalgia.
First, and probably as no surprise, I’m a total music nerd. Since I was a kid, music has always served as my guiding compass through life. It’s shaped countless moments, helps me regulate my mood, and has connected me to people in my life whom I hold most dear.
My earliest music memories include driving around Chicago with my dad in his 1985 blue Oldsmobile, listening to Satisfaction by The Rolling Stones. I used to sit right next to him in the front middle seat so I could tune the FM dial. Pretty sure that’s illegal now.
Ingrained in each of my fondest memories that involved music, are the images in my mind that I see whenever I reflect back on moments where that music first impacted me.
“Music memories” such as these are the reason why sitting on a porch at dusk in the summertime makes me want to hear Neil Young’s Harvest Moon. Or whenever I’m snowboarding on a blue sky powder day, the soundtrack of that moment is Get Innocuous by LCD Soundsystem.
Because of the way music latches onto memories, we often use songs to direct our emotional compass. Whether we want to feel empowered, relaxed, understood, or muster the courage to jump off a cliff, we can use music as a vehicle to get there — it’s aspirational in this way.
We also each have our own unique image associations tied to songs based on our subjective life experiences. Therein lies the central point of my curiosity, which has guided my entrepreneurial journey for the past few years.
For instance, can a specific song objectively fit certain contexts based on people’s perceptions and experiences? Example: My friends and I are sitting at dusk as the summer sun sets over the horizon and I put on Harvest Moon by Neil Young. Will this moment become a music memory for my friends and will they associate the song with a summer sunset from this moment onward?
Based on the exploding trend of mood and activity-based playlists in the music streaming space over the past few years, it seems there’s truth to the now commonly heard maxim — “context, is the new genre”. And with the hundreds of music fans we interviewed, 80% said they pick music based on their mood.
Even so, if there’s an expertly curated “songs for summertime sunsets on a porch” playlist (that’s a mouthful), where curators meticulously handpicked every song, there will always be people who feel those songs don’t fit, based on their subjective perceptions and experiences.
But can a specific song objectively fit certain contexts enough, based on a significant sample size? This is where it gets interesting. What if we could learn that 70% of 1000 people across cultures agree that Harvest Moon is a perfect song for that summertime sunset moment. What kind of platform and technology could bring forth these insights — not only improving our understanding of linkages between music and context, but also to ease the process of finding the right music for the right moment?
Birth of a product
Since we naturally categorize our world to make sense of it, perhaps for something as intangible and emotional as music, we need a categorization medium that is also intangible and emotion-driven. The obvious choice to me –photography.
These questions lead to building an image-based music discovery app called Moodsnap in 2013. This was around the time when Songza and 8Tracks (both great IMO) were gaining steam delivering human-curated mood and activity-based playlists.
Our hypotheses — to simply things further and make the discovery experience emotion-driven, what if we could simply show people a beautiful photograph that captures a moment, and crowd-source people’s song associations around that image? Like taking the concept of album cover art and flipping it on it’s head. What if we gave people the tools to say, “ok, here’s the album cover…now what should be the soundtrack?”. Are words describing and categorizing music even needed? Or is the image alone enough?
The Moodsnap app was launched on iOS in September 2013. We licensed roughly 50 beautiful and diverse images from photographers. Some images were more abstract, some captured an expressive moment, while others captured an environment-centric scene (see examples below). We seeded each photo with a handful of songs that we thought captured the feeling of that image well, and published them. Any user in the Moodsnap community could then add their song contributions to those images via Spotify, to build a collaborative station around “what that image sounds like.”
What we found after 2 years, thousands of users and song contributions later, was that music fans either thought this was the greatest thing ever, or they couldn’t relate to it.
I believe extreme reactions are a positive signal. Tepid responses equal death. We knew we were on to something.
We learned that the people who couldn’t relate to the songs associated with the images, typically had less adventurous musical palettes in terms of genres. They also had firmer expectations about what that image should sound like, so when they’d hear a song paired with an image that sounded different than what they expected, they were disappointed.
The people who loved Moodsnap were self-proclaimed visually oriented, emotion-driven people. They also typically had more adventurous music tastes spanning an array of genres, and enjoyed thinking about the synesthetic, emotional and creative connections each song in the playlist had with the associated photo — trying to see with the eyes of the song’s contributor.
Moodsnap was our attempt to make the process of finding music for moments, as easy as tapping an image that feels right. In the end, the subjectivity of the songs people associated with each image, was a chasm too far to cross for the masses.
Images may not be the right medium to drive music discovery, but how about images as the medium to drive music engagement?
We spent the first 4 months of 2016 pursuing that question in Project Music – the U.S’s premiere music-tech accelerator – and have been pouring our lives since into a new product that will shed light on it.
To be continued…
Snapwave Originals — Inspiring stories at the intersection of music and photography. If you’d like to submit a story, email hello(at)snapwave.co.