This is the second installment in a series of posts about the various social signals that we built into Pragli. We measure each signal with two metrics: Clarity of Intent (COI) and Invasiveness to Privacy (ITP). More about these metrics here.
I listen to Spotify religiously while I work. And from my conversations with other folks, I'm certainly not the odd one out. People listen to music all the time while working to focus or relax.
More so than that though, listening to music can be a valuable social signal to communicate your status to your team.
We released our Spotify integration a few months ago and have seen high usage from our users. In this post, I’ll discuss how the integration works and evaluate it on the two dimensions that we discussed in our first post: Clarity of Intent (COI) and Invasiveness to Privacy (ITP).
How does the Spotify integration work?
Users authenticate via Spotify OAuth and give Pragli permission to view their currently playing song. The integration then subtly shows the Spotify icon on my avatar when I’m listening to music.
If my teammates hover over the icon, they get more information about the artist and song that I’m listening to.
Clarity of Intent: What important information does this convey?
Whether my teammates are listening to music is a fantastic indicator as to whether they are available for a chat. If they are listening to music:
- They are likely not on an important call with a customer or family member.
- They could potentially be deeply focused on a task, but if there is an urgent task that I need from them, I can likely safely contact them.
- If I know my teammates’ music preferences given certain circumstances, I can capture additional signal. I normally listen to music without lyrics when I focus on deep engineering work but listen to hip hop for more repetitive marketing tasks.
I once worked with someone who obsessively listened to Jessie Cook during intense work sessions. Whenever I saw that “Mario Takes a Walk” was playing on his laptop, I would never bother him. I’ve seen similar patterns of music preferences among many other software engineers.
Interesting insights also arise from the combination of social signals. In Pragli, we fade in or fade out users’ avatars given that they haven’t touched their keyboard/mouse or we haven’t detected their face in the last 15 seconds. If a user hasn’t been detected but is listening to music, their avatars look like this.
This implies a few things.
- They are likely taking a break from their desk to take care of a personal task
- They are listening to music on their phone
- Most importantly, if I need to grab them for an urgent conversation, they likely have access to their mobile phone to contact them
Invasiveness to Privacy: How invasive is this social signal?
Let’s face it. People have embarrassing tastes in music, and I’m certainly not an exception.
But save for songs with a strong political bent or explicit lyrics, sharing my Spotify song preferences doesn’t carry a high privacy risk. The invasiveness of this social signal is pretty low (low ITP).
Spotify works surprisingly well as a social signal for our users. The most important value add has been showing users whether their teammates are not in an important meeting with customers or other teammates.
Clarity of Intent: High 🔥7/10
Invasiveness to Privacy: Low 🔥 3/10
What is Pragli?
I built a virtual office for remote teams to frictionlessly chat and feel present with each other. We use various social signals to provide remote teammates on Pragli the confidence to start conversations with their coworkers.