The listening time trap

My biggest gripe with most music business conferences is that I hardly ever bump into engineers, designers, or product managers. If they’re there, they’re presenting their company rather than talk about the work they do, like many other music professionals. There’s marketing talks, A&R talks, talks about bookings, management… Where are the design talks?

Part of this frustration is personal: when going to a conference, I want to learn from people. While music conferences help me build perspective, they hardly help me develop as a professional.

More importantly, I believe the people who have some of the biggest impact on the modern music landscape often aren’t actually part of the conference. It would help the whole business to better understand them, their goals, their motivations.

They’re the people who decide upon the interfaces through which we experience music and connect with creators. They decide upon algorithms. What feature goes in, what doesn’t. And they’re largely invisible.

How decisions get made in tech companies

Tech companies set themselves up for rapid growth. Either in terms of users, staff, or both. In order to do so, it’s important people inside an organisation have a framework for autonomy. They have to be able to understand the company’s goals at the top-level, and what that means for their team specifically. They should be able to derive goals from the top-level goals themselves.

This type of grass-roots level autonomy helps the velocity and quality of decision-making compared to old school top-down chains of command and approval.

One of the most popular frameworks at the moment is OKR: objectives and key results. A team decides what they want to accomplish in a certain timeframe (objective: “shape a delightful social experience around music”) and then defines ways in which they want to measure their performance on the objective (key result: “active users share music 5 times a week”).

Once everything is set, the time period is kicked off and the team works together to try to accomplish their objective. They might use data about the service, in-person interviews with users or potential users, and the advice from stakeholders around the company.

There is one metric so important, that you will almost always encounter it when spending some time in a digital entertainment company. Either as a “key result” or as a “health metric” to see how well the company is doing.

The most important metric in music

One popular concept in optimizing a company for growth is “One Metric That Matters“. It means giving company one metric to focus on improving during a given stage. This may be “customer lifetime value” (CLV): how much revenue does a user bring in as long as they use our service?

For many music streaming services, CLV will be composed of various factors. Does a user upgrade to premium or do they stay on the ads platform? How much are advertisers paying for ads? How long does a user stay with the service before ‘churning’ (leaving, and not returning)?

There is one metric that has arguably had more influence on music than any of the above: how do you make sure you get more ad revenue per user on average? How can you tell that a person is enjoying their subscription and are unlikely to unsubscribe (churn)?

Listening time.

How many hours per day, week, month, does a user spend listening to music on our service?

It can be a good health metric, and it can have a rather direct relation on revenue growth when applied to the ad-based free tiers of services.

So designers, engineers, and product managers get to work and try to figure out how to optimize the amount of time people spend listening to music on their service.

The never ending push for listening time

In come tools for curators to optimize their playlists: and out go songs that lead to skips. How many skips away from the pause button are we? Let’s not risk it.

Out come the algorithms which continue audio playback after an album or playlist finishes playing, which populate users’ home feeds with music they’re most likely to listen to at this time of day, which create context on artist profiles by showing the ‘related artists’ users are most likely to click on and listen to next.

What it also does is strip music of context. It removes music from circulation that is not optimal for performing on this metric. It values art based on metrics.

What happens when people listen to more music?

One could do academic studies on the above subject (and if you have done so, please get in touch with me), so for the sake of this article I’ll give a few examples of what happens.

  1. Theme-based playlists and other features that make the friction of choosing something to listen to smaller. Indecisiveness = lower chance of playback = less listening time.
  2. Decreased familiarity with the artists one listens to. Listening to a higher number of artists means that on average people will be less familiar with each individual artist and their music. This does not mean that people’s familiarity with their absolute favourite artists is necessarily affected. However when they don’t know which of these artists to tune into, they might go for option 1 and just pick something theme-based, put it in the background, and listen to hours of music from anonymous artists, because the user was never confronted with their names.
  3. Decreased importance and awareness of context. Think of a feature like Spotify’s Discover Weekly. A great tool to get people to come back to the app every week and listen to something, perhaps even explore some new music. The challenge is that it presents music stripped of any context. It’s just a list of tracks based on what you’ve been listening to. Recently, that’s sent me into 80s dark wave and industrial, but I honestly have no idea about the landscape. Who were the important artists? Where did they come from? Who inspired them? What subgenres, microgenres, and adjacent scenes exist? What does the subculture look like? All sacrificed for convenience. (I actually think there are interesting business opportunities here, now that the music streaming landscape has matured in many countries)

All that, because of a business decision to focus on a metric, and hundreds of thousands of small decisions by thousands of designers, engineers, and product managers that then influence the future of music styles, scenes, and the way artists connect to fans.

Why focusing on listening time is inevitable

I love this age of music and although the last section may sound pessimistic, I’m actually excited by the ease of access of music and all the experimentation that exists now. I’m excited by how easy it is, relatively speaking, to build up a listener base these days.

The hard thing about the world we’ve created is that with infinite free media (which I consider a good thing, inherently) we’ve opened up a massive competition for attention. The amount of music people would listen to used to be as large as people’s disposable budget for music. Now, for $10 / month or even $0, we can listen to music 24/7 and never hear the same song twice.

This is the landscape in which companies have to build their business models, and the landscape in which the music industry has to identify business models. With advertising-based models it’s simple: you lose attention, you lose the revenue. With subscription-based models, it’s similar.

Music competes with podcasts, video game streamers, tv shows, cat videos, and unfunny pranks. Either on one platform like YouTube, or spread out over various platforms (Apple Music competing for attention with Netflix, for example). This competition for attention, unfortunately, has become a rule of the web.

The part on which we can work together is the how: how do we hold people’s attention? How do we connect them to what they care about? How do we generate revenue around that?

What do you think?

I’m curious to collect more perspectives. Add on by penning your thoughts on Medium, LinkedIn, your blog, or as a Twitter thread. Email me or ping me on Twitter (@basgras) with a link and I’ll include it in next week’s newsletter (sent out 18 Nov, 2019 – 4pm Berlin time).

Bonus

You made it to the end. Here’s a video of every time Mark Zuckerberg said “more”, “growth”, or mentioned a growth metric.