Episode 15: Building Growth Through Gaining The Right Type of Streams

Ever wondered how fanbase building actually works and how you can feed it? Get ready to uncover the secrets behind Spotify's sophisticated recommendation algorithms and learn how to leverage them to skyrocket your listener count! From understanding the structural mechanics of how Spotify uses user data to craft personalized listening experiences to the often overlooked role of external platforms like internet radio and blogs, this episode is your ultimate guide to mastering the world of growth through audio streaming.

Join me, Jonny Amos as I break down the complexities of Spotify's system with easy-to-follow insights, revealing how machine learning and content-based filtering work together to suggest your music to the right audience. Plus, discover practical tips on identifying potential fans based on their appearance and habits. Packed with valuable advice and strategic know-how, this episode is essential listening for any music creator aiming to elevate their career and grow their audience effectively with the right kind of streams. 

Transcript

Speaker 1: 0:02

The Music Business Buddy. The Music Business Buddy. Hello everybody and welcome to you. You're listening to the Music Business Buddy with me, johnny Amos, podcasting out of Birmingham in England. I am the author of the book the Music Business for Music Creators, available in hardback, paperback ebook on all major bookstores and online. I'm a music creator, a writer, producer with various credits. I'm also a senior lecturer in both music creation and music business. Wherever you are, whatever you do, consider yourself welcome to this podcast and to a part of the community around it. I'm here to try and educate and inspire music creators from all over the world in their quest to achieving their goals by gaining a greater understanding of the business of music.

Speaker 1: 0:58

Ok, so the focus of today's show is how to build growth on audio streaming platforms, with a key focus on gaining the right kind of streams. Now I can hear what you're thinking the right kind of stream. Surely, as many streams as possible is the best thing you can do. Well, yes, if you've got loads and loads and loads of monthly listeners, then, yes, it doesn't really matter so much. However, there is a specific kind of model to use in order to scale up a listener base, and that's what we're going to focus on in today's show. Okay, let's hone in on Spotify, and for two reasons. Number one, because they have the largest market share of music audio streaming and secondly, because they have the most sophisticated recommendation setup in their algorithm for finding new listeners for new music. For many years now, spotify's goal has been to move listeners from the free platform to the paid platform, and the way in which they achieve that is by making a unique listener experience. But they can't achieve that until they know what that listener likes, which is why they crowdsource data from that listener in order to build a bigger picture of what they are into and therefore what they might like to listen to next. Okay, so how do they actually do that? Well, allow me to try and fit into the next 90 seconds how that works. Are you ready? I'm going to go quick. Here we go.

Speaker 1: 2:31

In order for Spotify to serve your music to new listeners, they have to understand who is already listening to you, what their habits are and who else they listen to. That information is then cross-referenced against similar profiles of people that have similar tastes. Further machine-based learning is then used to generate recommendations for users. User data can be such things as listening history, playlists likes, saves, skips and behavioural preferences. This information is then further cross-referenced against an advanced form of content-based filtering, which effectively removes human interpretation as to what the music actually is. So they're looking for advanced set of metrics that tell them a little bit more about the characteristics of the song. This could be vocal delivery, style, it could be mood, speech ability, dance ability and other things. The idea of this is that it analyses the actual music rather than how the music has been received. This further informs suggestions and recommendations and, finally, an advanced form of web scraping takes place in order to understand what the artist is doing outside of Spotify. This is why internet radio and blogs and things like that that people often overlook are actually important. Those things are being analysed to inform, for recommendations and suitability.

Speaker 1: 3:45

Ah, breathe, johnny, breathe. Ok, I tried to simplify that in a succinct manner. Of course, there's a bit more to that, but those are the basic headlines, right, and sometimes it's. You know how frustrating it can be sometimes to sit through like a 20 minute YouTube video with a bunch of ads and stuff and really all you need to know is an information piece that lasts about 90 seconds. That's what I tried to do there anyway, let's move on. Okay, so it's important to try and understand who might be interested in your music. Now you can go really, really, really detailed with this, but you don't have to. So a detailed example would be you know, being able to walk down the street a busy street, lots of people around and actually being able to walk down the street a busy street, lots of people around and actually be able to pinpoint, just on appearance, the kind of people that might be into your music based upon their style, their clothing, etc. Right, if you can do that, you're onto a winner. If you can't do that, it's okay. There are other ways to achieve this. A much more kind of basic example would be to understand where your music fits, and I'm talking about not just the genre and the secondary genres, but also the mood. Once an understanding of that is built, it means that you can then pitch correctly.

Speaker 1: 4:55

Now, spotify have some tools built into their Spotify for Artists app that allow for further discoverability of your music. However, they all fall in line with the things that I said inside the first four or five minutes of this podcast, which is an informed understanding of who your audience is. Now, if we take marquee and showcase, for example. If anybody's not heard of those two before, they are tools that you can use within Spotify to further align your music with a larger listener base. However, they build their understanding on who to serve that music.

Speaker 1: 5:26

Two, based upon who's already listening. So you have to have a particular threshold. I think for market, you have to have something like 5,000 listens in the last 28 days, or something like that, or a thousand followers, something like that. I think. For showcase, it's more like a thousand streams in the last 28 days. Those numbers are interchangeable, right, so don't quote me on those. That's roughly the ballpark. Now, the idea there is that they can't do that job and target the right people unless they already understand who's already listening. Otherwise, they do an inaccurate job. So there are things that we have to do in order to be able to align our understanding of where our music fits before we can hit those thresholds, and then the algorithm starts to work for us. So what can you do?

Speaker 1: 6:07

Here we go Create some playlists that include your music and also music that is similar to you. It doesn't have to be things that you like. It doesn't have to be things that inspire you. It has to be music that is similar to your songs. Share that to social media and tag the artists. Update those playlists every 7 to 14 days. Identify your most successful song to date. It doesn't have to be your favourite song. It's probably not going to be the one that you like the most when performing live. It just has to be the one that has the highest listener to stream ratio and the highest save rate. Work that song. Doesn't matter if it came out a year ago, two years ago doesn't matter. Work it into as many third-party playlists as you possibly can and continue to build its growth, even whilst you're releasing other music. It will act as a lead song and an anchor point in the algorithmic world to attract new listeners. Complete your bio properly. This is a really, really big one. It's really overlooked. Just put in.

Speaker 1: 7:03

There doesn't need to be a life story just who you are, where you're from, what you do and what your plans are going forward as, as an artist, engage with social media in a way that doesn't just mean that you're selling something. Every time you've got a new single, you post about it. Yeah, I get why. I get it. But if you engage with more accounts, even if it's just comments, likes, etc. It will feed your visibility on your social media, which helps you stream in. Encourage followers on your social media to actually listen to your music on specific playlists that you put in front of them. So, instead of them just finding you through your catalogue or clicking on your latest single, actually include playlists that you're either added to or that you have created for them to listen to your music on. Get your music featured into as many blogs and forums as possible. You need people talking about you to enhance visibility. You need people talking about you to enhance visibility.

Speaker 1: 7:56

Understand with pinpoint accuracy exactly what your genre is and what mood your song is supporting, and then pitch it to third-party playlist platforms such as SubmitHub and Groover, and really do your research on which ones you think are suitable and then go ahead and pitch. Consider using Spotify Ad Studio, which is an advertisement platform that allows you to easily create and manage Spotify audio advertising campaigns. There's a particularly new feature on there that allows you to track the growth and the flow of your streams and gives you the ability to target listeners by location, demographic and listening needs. It will also provide you with a set of analytics and feedback, which enables you to understand the audience better. Take advantage of the Spotify code system, which is effectively a sort of QR code system that enables you to promote instant access to a particular song. People use them on print, people use them on websites, social media, and it can increase your streams.

Speaker 1: 8:44

Examine artists that are similar to you through radio and then visit their profiles and scroll down to the discovered on section. You'll need to be on a computer to be able to do this. When you see the discovered on section, you'll see playlists that they're listed in where people have found them. Submit to those playlists. Okay, if you combine all those things and then you repeat them across multiple singles over several months, you'll start to build some data on who is listening, where they're listening from, etc.

Speaker 1: 9:12

Now it is at this time that, hopefully, there is an eligibility status change in order to be able to engage with discovery mode. If you haven't reached that point yet, you have to keep going with the previous steps. Once you reach discovery mode, it enables you to be able to find new listeners through Spotify's understanding of their own algorithmic space. It means that people can be defaulted to your music through radio, through Spotify mixes and through autoplay. It is at this point that you start to gain a little bit more traction and visibility and start to become a lower risk act in the eyes of the algorithm.

Speaker 1: 9:50

The stage beyond that is, then, what I referred to earlier, by using the tools such as Showcase and Marquee. In particular, marquee, in my view, has just become a lot more useful in the last sort of six to seven months or so, because you can actually target new listeners. Previously, it was set up in a way for you to re-engage with listeners that have already crossed your path. Now there's set up in a way for you to re-engage with listeners that have already crossed your path. Now there's a new tool on there that will enable you to target new listeners based upon who the profile of your listeners are. Okay, there's a lot of information there. I hope you're still with me.

Speaker 1: 10:24

Okay now, have you noticed I've not even mentioned editorial playlists yet? I haven't mentioned them on purpose. They are perhaps the holy grail, right, the gold dust that many people try and reach, but what I would say is this there are ups and there are downs. I have seen a lot of artists become very despondent about their streams after they've been on a huge editorial playlist because you have this giant spike that goes all the way up with listeners and streams and then it comes all the way back down again.

Speaker 1: 10:58

Now we're in an age of passive streaming. We all know this right. So you know streams are streams, they're data. You can use them as leverage to get sponsors or a better booking agent or whatever right? We know that there's not a huge amount of money to be made in streaming. We know this. We all know this be made in streaming. We know this. We all know this. However, how we use that streaming data is very important, but we can't grow on it until we understand who is listening.

Speaker 1: 11:21

Now it's therefore, yes, it's fantastic to have editorial support. It's what artists and labels all over the world gun for every single day, and I get why, but it's not always the answer. Follower rate from editorial playlists is actually fairly low when you consider how many listeners and streams are generated from this. This is the age, again, of passive listening. We know this. So the answer is perhaps in algorithmic growth.

Speaker 1: 11:46

Now I'm talking about Release, radar Radio, discover, weekly On, repeat, daily Mixes all of the algorithmic playlists that actually align you with growth. It enables you to understand where your growth patterns are coming from. But in order to reach the threshold of good algorithmic growth, it has to be largely informed by the growth of user curated playlists and ads. Okay, so that's an overview of trying to gain the right kind of streams. Now that's all well and good, I know, and it's a lot of work. I'll try and make it sound easy, but I know it's not. It's a lot of work, but there's also another aspect to this, which is the wrong kind of streams, and that's what we're going to be looking at in the next episode. So until then, thank you for being here. Thank you for tuning in. I hope this has been useful on some kind of level. Catch you again soon and may the force be with you.