Gustav Söderström
speaker
294 appearances
1 recordings
1 series
first heard May 2025
last heard May 2025
Gustav Söderström’s voice in public audio — every appearance, attributed to the second.
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Appearances
So if it's too easy to change people in a conspiracy theory, it's probably not true. So I think that's something very powerful. Good explanations need to be very hard to vary. So this is something I've tried to instill in my org. And I think there's an interesting meta point here, which is people ask me as a product person how much of product development is magic and how much is science.
And I try to be provocative in saying I think it's exactly 100% science and 0% magic. And people get provoked because it implies... that there's no skill. I say it to provoke. What I mean is that certainly people are going to have pattern recognition in this neural network. They've seen a lot of examples. That's what we call seniority. And people have seen a lot of things.
They're going to get instinctively to the right conclusion faster than others. So that is valuable. And I want lots of seniority. I don't discard seniority. And it brings you a lot of value. You can save a lot of time, a lot of mistakes. But the reason you call it magic is because that person can't explain it. It isn't actually magic. It's just science.
It's just you are not smart enough to explain yourself. If you could think even further and explain it and come up with an explanation for what you see, the way David Dodge does, it's so much more valuable for the company. If you have a theory, instead of saying, no, Patrick, my intuition is this. You're not smart enough to understand it, so I'm not going to tell you. Just do what I say.
Maybe I'm right, maybe I'm wrong, but it's not very helpful for you. When I leave the company, you're going to take over. You're like, I have no idea why they did that. You have to develop your own intuition and your own pattern recognition. But if I come up with an explanation, which is I think the psychological behavior of people, you know, it's like Kahneman's loss adversity or prospect theory.
I think people value losing something one and a half times the value of getting it. So therefore we should not just launch feature and test it because it's 1.5x hard, more expensive to remove it. Then you have a theory and it can spread across the company in a week. And now everyone has that.
So I really want to force people in my company, even if we see something working in an A-B test, I try to tell them that I don't want to launch it until we at least have a theory of why it works. Even if it's super clear, there's a lot of pressure to launch it because there's engagement value and monetization. But I want you to at least have a theory.
Because then over time, the company builds up a consumer theory. And if you have a strong consumer theory, then you can predict things that were very unlikely. What David Deutsch also says is that pattern recognition... will iteratively get you more on the same path, but it's never going to jump all the way from the geocentric to the heliocentric model.
Only an explanation can take you to quantum physics. Entirely unintuitive. No pattern recognition gets you to maybe it's a wave and a particle at the same time.
What's an example internally of a great explanation that then led to the geo to heliocentric type of jump? What's an example of how that actually played out? I think a good example...
that is public is the free tier that I told you about. We only had a paid mobile tier. You actually paid to get mobility on Spotify. Now smartphones are scaling. Users don't have a computer. We need a free tier. The competition that was YouTube, they were foreground on demand with video. The pattern recognition, the obvious thing would have been to... Say, let's do that. It's proven.
But what we did instead, and specifically attributed to a person named Charlie Hellman, was to reason around it from first principles and say, okay, let's look at our usage of Spotify. If we limited our license to the same thing, it only works in the foreground. As soon as you look at the screen, the music stops. How much of the listening is in the foreground?
Turns out back then it was 9% or something. So you have 91% of the use case being in the background.
probably want to get something else the user need there is probably background listening and then you look at the app store is there a way to listen to music for free in the background in the app store the closest thing was pandora but that was radio you could not listen to your favorite songs so then we said we would like a consumer product where you can listen to your favorite songs with your phone in the pocket for
forever for free. So the problem with that is that's almost a premium use case. If we just launch that, it's going to cannibalize our premium tier. So what do we do? Then we looked at the premium usage and we saw that premium users, about 50% of the time, they were shuffling their playlist.
They were using on-demand features, searching and clicking and playing specific songs 50% of the time, but they were shuffling playlists 50%. So then we thought, what if we take this that seems to be something that even when you have on demand, you voluntarily shuffle. It's a big use case. We give that away for free.
That should mean that none of the premium users convert back to free because they still want their 50% on demand. But you're giving a lot of value away. for free. So we tried to model a consumer need, reason around it, came up with this shuffle background here that was very, very, very unintuitive. Even the people inside the company said that's a terrible idea.
But we trusted the data, and I was even skeptical of it myself. I was like, look at this on demand. Shouldn't we try time caps? A lot of people just want us to try long, free trials. But the problem with the free trial is, even if Nokia, I think, Nokia comes with music, they tried a year-long free trial.
But even then, the user knew that if I start investing in Playlist now, a year from now, my Playlist investment is going to disappear. So they never started investing. So we went with this shuffle tier, and this is what made growth explode. And to this day, that's our differentiation against the other services. It's the only way to listen to music for free forever with your phone in your pocket.
So that's an example of theorizing and explaining rather than pattern recognition.
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