Episode 16: The Dangers of Gaining The Wrong Type of Streams

Ever wondered how well-meaning support from friends and family could be sabotaging your music career? In this episode of The Music Business Buddy, I unpack the surprising pitfalls of the "wrong kind of streams" and how they can distort crucial data on platforms like Spotify. Join me, Jonny Amos, as I break down why these seemingly innocent acts of sharing might actually hurt your chances of reaching genuine fans and influencing algorithmic recommendations effectively.

But that's not all— I also deep dive into the subject of artificial streaming and dip into the basic mechanics of Spotify Ad Studio when compared with Meta advertisements. Learn why meticulous planning is essential to avoid wasted resources and how market saturation in regions like the UK and US is driving Spotify to expand into new territories. Whether you're an emerging artist or a seasoned pro, this episode is filled with insights to help you navigate the complex world of music streaming and data accuracy. Get ready to enhance your understanding of the business side of music creation and make smarter decisions for your career by avoiding the wrong kind of streams.

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Transcript

Speaker 1: 0:02

The Music Business Buddy. The Music Business Buddy Hello everybody, a big warm welcome to you. You're listening to the Music Business Buddy, with me, johnny Amos, podcasting out of Birmingham in England. I'm the author of the book the Music Business for Music Creators, available in hardback, paperback, ebook format. I'm a music creator, a songwriter and a producer with a variety of 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 this community. 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: 0:53

Okay, so this episode kind of follows on from the last one. The last episode before this talked about gaining the right kind of streams and gave a view on how growth is actually created on a platform such as Spotify. Now, in today's show, we're looking at the wrong kind of streams. It might seem like a really strange thing to say the wrong kind of streams, but it is a thing, it exists and we're going to break it down right now. Ok, let's start off with something a little bit more simple, but also quite an odd thing to talk about, and that is the idea of friends and family sharing and streaming your music. Now, there's a very natural and understandable inclination for family and for friends to want to support their loved ones Right when they create and release new music. Now, on a basic human level, it's lovely, isn't it? But on an algorithmic level, it's actually quite a problem. Now, often, a creator's family are sharing and streaming the music because they love the person, not their actual music. Now, it goes without saying that that's not always the case, of course, but the problem is often that the friends and the family of the creators are not the natural fans of that music, and this can lead to what I refer to as distorted data. Now, spotify, for example, like other streaming platforms, they're keen to try and understand who is listening to your music and by building a profile of each listener's interests and collaborative filtering, which I referred to on the last episode, enables a more accurate understanding of how to present music to new listeners. So you can see how that actually is kind of a problem.

Speaker 1: 2:26

Now, it's a weird thing, isn't it, to try and say to your family and friends oh, I've got some new music out, don't share it Like. I don't hear many people saying that and it seems like a hurtful thing to say, but it is a thing on a very minor scale. It's a problem. We're going to get into a much deeper problem in a minute, but is an issue now. Let's imagine someone's logged into your netflix, right, and they've watched maybe a couple of films or tv shows something. And then you come back to it and you look at your recommendations and they've kind of slightly altered. That is a much more basic level of how system recommendation works. It's become distorted. You're not interested in those programs because you didn't watch the things that came before. It Now apply that on a huge mass scale of data. That is why family and friends overly sharing your music is actually a bit of an awkward issue.

Speaker 1: 3:17

Now, in the last episode I talked a little bit about Spotify Ad Studio, which I actually endorse. I actually think it's a really really good system, providing that you know how to use it. It's really easy to get wrong. It's a little bit like meta advertisements If you just do it lazily and don't set up a campaign properly, you could spend money and yield nothing out of it. And Spotify Ad Studio is kind of comparable to that to a certain extent. Now let's just think about it like this right spotify ads target people who are listening on the free version of spotify now in the uk. In the us and I'm going to draw some really really large, broad inferences when I say this the uk in the us market is almost at saturation point. The number of people that have moved from the free platform to the premium platform has kind of plateaued in its development over the last year or so, which is now why spotify are trying to repeat the success that they've had in the UK and the US in other territories such as Asia, africa and Latin America. Now, with that in mind, it could be argued that actually targeting UK listeners and possibly even US as part of an ad campaign is no longer as beneficial as it would have been four or five years ago due to market saturation point, and therefore it might actually be more beneficial to fall in line with what Spotify are trying to do, which is to move people from free to premium in other territories. Therefore, they might be the wrong kind of streams. If you're targeting UK and US Now, I might be way off with that, but I'm willing to gamble that actually a better risk would be to try and fall in line with what the platform are trying to do and increase the number of people in Latin America, in Africa, in Asia, from a free platform to a premium platform and therefore it would be more beneficial to target those listeners in an ad.

Speaker 1: 5:16

Okay, now onto the main point of today's podcast artificial streaming. It's a major problem. It has been for a while now and things are getting slightly better, but only a little bit. So let's try and understand it a little further. Okay, so think of editorial playlists as a boost, an organic boost, of real listeners. Now think of algorithmic growth as the key to victory in creating, sustaining and building an audience. Artificial streams are the vacuum of that audience. Now we're surrounded by such a wide array of adverts that guarantee a certain number of followers that can be bought or a certain number of streams. Anywhere you ever see anything like that, it is a bot, because even the sharpest of editorial playlists out there cannot guarantee any kind of number of streams or any kind of number of streams or any kind of number of followers. So any service that promises that, I promise you, is fake.

Speaker 1: 6:20

Spotify and also many other platforms, including distributors, are trying to do as much as they can to clamp down on artificial streaming. Now, artificial streaming, you know it, it's a bit of a strange subject, but it's largely carried out by streaming farms, which are basically locations with many digital devices, each of which has its own independent login to stream a particular song. Now, there are a few ways to detect it, some of which I don't fully understand, but are patented algorithms that are perhaps owned by distributors that are working to try and combat this growing problem. But one of the easier ways to look at whether or not your streams have been affected by a streaming farm or by a botted service is to see if there is a small, unusual town in a faraway country perhaps, that has generated a lot of streams. That is a telltale sign and, still today, one of the mechanisms used by many DSPs to try and track artificial streams.

Speaker 1: 7:24

Now, there's two kind of major damaging factors in place for the artist here. Right, one is reputation, you know. So that's a damaged reputation with a DSP or damaged reputation with a digital distributor. That's a problem, right? But I think there's an even bigger problem than that, and that is that it can lead to some very, very distorted data, which is actually really hard, if not impossible, to recover from, because it infiltrates and dilutes statistics on listeners, locations, save rates and a whole host of other data. Now, if you contrast back to the previous episode before this, where we looked at the right kind of streams, we looked at how growth is gained, now if halfway through a campaign, an artificial booster is put in place, it's like a zero reset because all of those right listeners, those right streams get mixed up with all of the bots and it dramatically slows down growth rate because it leads to some very confusing data.

Speaker 1: 8:23

Remember, we're dealing with algorithms here. There's not always the human sense, of common sense in algorithms, so anything that can slow algorithmic understanding is not good for an artist or their song. Fake streams won't only damage the algorithmic potential through a lower engagement rate, but they also confuse the recommendation algorithms by feeding very, very misleading information and data about who your audience actually is and what other artists they're listening to. Through its collaborative filtering mechanism, behave like real fans and the algorithms will have difficulties in understanding who the artist's proper audience is, which ultimately restricts visibility, traction and growth. Now I know how tempting it might be to look for that sense of validation of reaching a particular threshold maybe 10 000 or 100 000, 250,000, however many streams. That gives a sense of validation to the artist that something's working. But it's not working if those streams are paid for in an artificial method.

Speaker 1: 9:29

Now, it's all well and good me saying that, and, however true it is, it doesn't make it easy for music creators to be able to know who to pay who to work with. It can be very, very difficult, and this is why I often like to refer people to centralised platforms that have their own mechanisms for detecting and weeding out the kind of playlists that you don't want to be involved with. So I'm talking about places like Daily Playlists, groover, submithub. They have their own mechanisms to protect that from happening. Now here's a gray area for you. Right, it is against the terms and conditions of spotify to pay to be on any playlists. They don't want you to do that. They don't want anyone to do that. However, they don't always do a whole lot to actually regulate third-party companies who you can pay for them to then pitch your tracks. There's the grey area Now.

Speaker 1: 10:22

This can lead many music creators to feel somewhat confused and scared about what they can pay for, or what they should pay for and what they shouldn't, and it's very, very difficult to try and navigate those very, very, very muddy waters sometimes, but we have to use common sense at times. If something, as I mentioned earlier, is guaranteeing a certain number of streams, it will be fake. Now, that's not to say that you shouldn't be investing financially in a playlist campaign. There's nothing wrong with it. Artists all over the world do it. Loads of labels do it. There's absolutely stacks and stacks of labels that pay good money to promote songs on playlists.

Speaker 1: 11:03

Now, I don't mean by doing anything illegally, but I'm talking about hiring particular professionals to carry out ad campaigns or to carry out pitching campaigns to playlisters.

Speaker 1: 11:15

There's nothing wrong with that, and so it's just about trying to get the balance right between what is going to get you in trouble and what is going to yield results. Now, I think by the time we reach the early 2030s maybe even before then we'll have probably figured this out by then and it will be much easier to manage. Right now, in the mid-2020s, it is difficult to manage the difference between what we should pay for and what we think we would like to pay for now. There's no shortcuts to this, and if an artist is in it for the long run, they'll want to get the right data, and getting the wrong streams leads to the wrong data, which creates an inability to further develop growth. So tread carefully in these digital waters, my friends, because it is very confusing to try and get the right steps to move forward. Hopefully this episode has helped in some way. Thank you for being here, everybody. Until next time, may the force be with you.