Two Hidden Data Points That Predict Podcast Growth (& Tell You Exactly How to Accelerate It) | Podcast Discovery

A podcast listener's decision to click play boils down to a small number of touchpoints.

Most prominent are your show title, artwork, and episode titles. But while these (and other) touchpoints have always had a significant impact on listener acquisition, we've never had a way to track it.

Until now.

In 2024, Spotify rolled out a new discovery dashboard, giving us as creators a new set of metrics to understand how listeners flow through our listener acquisition funnel.

The best part is that if you know how to interpret the data this dashboard provides, it gives you a map of exactly what you need to do you improve your listener acquisition and grow your show.

Here's what you need to know.


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Resources

Spotify Conversion Rate Benchmarks Report
How a Podcast Cover Art Redesign Helped Growth Mindset Psychology Grow 45% in One Month (+2,000 Downloads/Episode)

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More on Podcast Analytics
While podcast analytics might appear to be stuck in the stone age compared to platforms like YouTube, Google Analytics, and many social media platforms, there's a lot creators can learn about how to improve their shows and their marketing... if you know where to look.

Beyond podcast downloads, metrics like listen time, consumption rate, Spotify's podcast discovery dashboard, and more give us clues about the issues facing your show—and often tell you exactly how to navigate them. Which mean understanding your podcast analytics & metrics, and how they compare to industry benchmarks is an essential skill for marketing and growing your podcast.

About Podcast Marketing Trends Explained
Podcast Marketing Trends Explained is a podcast about data-driven podcast marketing, growth, and monetization. In every episode, we take a peek under the hood of one data point from the Podcast Marketing Trends Report and dig into what it can tell us about how to market our shows better, and grow them faster.

On the show, we'll explore podcast marketing strategies, growth tactics, podcast listener psychology, how to create a better podcast, how to use a podcast to market your products and services and grow your business, and broader marketing trends to help you grow your audience and stay ahead of the competition.

The show is hosted by Jeremy Enns from Podcast Marketing Academy and the Scrappy Podcasting Newsletter, and Justin Jackson from podcast hosting platform Transistor.fm.

Get in touch: jeremy(at)podcastmarketingacademy.com

Creators & Guests

Host

Jeremy Enns

👨‍🏫 Helping scrappy founders & marketers hit their next growth milestone @podgrowthschool📈 50M+ Client downloads✍️ Sharing daily podcast growth tips

Host

Justin Jackson

⚡ Bootstrapping, podcasting, calm companies, business ethics. Co-founder of @transistorfm (podcast hosting).

What is Podcast Marketing Trends Explained: Data-Driven Podcast Growth Strategies?

It's easier than ever to launch and produce a podcast. But it's never been harder to grow one.

On this show, we break down and explore what the data says about what it takes to market and grow a podcast in 2025 to help you make smarter decisions about your show, grow faster, and earn more.

Together, cohosts—and longtime podcasters, creators, and marketers—Jeremy Enns (Podcast Marketing Academy) and Justin Jackson (Transistor.fm) explore topics like:

How do you define success for your podcast?
What are the most effective marketing strategies, tactics, and growth channels for podcasts?
What does the data say about how to structure your show and episodes?
Which social media channels should you focus on as a podcaster?
How do you stack up to other shows?

Using the data uncovered by the annual Podcast Marketing Trends Report, our goal is to make sense of the numbers and turn them into actionable insights that you can use to create a better show and market it more effectively.

You can find the latest report at podcastmarketingtrends.com.

Jeremy: 00:01

Spotify wants people to engage with content, and so they are trying to match users with podcasts. If they show it to a thousand people and none of them click into that, that's now a signal to Spotify saying either we're showing this to the wrong people or something about the show is not worth promoting.

Justin: 00:15

This is such a paradigm shift from the way episode consumption used to work. It's gonna be way more like YouTube. How do we grab people on the homepage versus how do we bring back our regular listeners?

Jeremy: 00:28

You can optimize all the internal things. You can create an incredible show. But if you're not getting people to click play into the show in the first place, all of that work doesn't really matter that much. So, Justin, in the back half of 2024, Spotify rolled out this new feature in the back end of the Spotify for Podcasters kinda dashboard. And most people didn't really pay much attention to it.

Jeremy: 00:52

They kinda missed it, but it was something that actually got me super excited, and it's something that I've been literally waiting years for. It's been on my podcast wish list for as long as I've been in podcasting. And I'm wondering if you have any guesses what that new feature might be.

Justin: 01:05

A vocal fry intensifier.

Jeremy: 01:10

It's not that. Any other, thoughts?

Justin: 01:13

Podcast auto tune. If you wanna hear all your podcasts sung to you.

Jeremy: 01:17

Definitely on my wish list, but that was not the feature that was released. I'll give you one more chance. You got, one more guess at what this feature was.

Justin: 01:24

Okay. If you really love podcast tangents, there's, like, an AI podcast tangent, expander so you can get more tangent. You could have a whole episode that's just one big tangent.

Jeremy: 01:37

% tangent. No no content whatsoever? Okay. That would that was also not the feature. I'm gonna save you the the pain of any more guesses.

Jeremy: 01:45

It was their new discovery dashboard that they rolled out. So pretty boring compared to all the feature recommendations that you made. Spotify, if you're listening, take note of these. Roll these out, please.

Justin: 01:55

That's right.

Jeremy: 01:56

And so, essentially, the discovery dashboard is a tab that's nested within their overall analytics platform. And what it does is it allows us, for the first time, to actually see conversion rates of people who saw the podcast to people who showed interest in the podcast to people who ultimately went on to listen to the podcast. And for me, this is just a huge game changer for how podcasters are able to approach the craft of packaging their shows and creating their shows. And so this is something that, I would love to spend some time digging into and tell people a little bit about why this is such a big deal.

Justin: 02:29

Yeah. I think it's worth looking at for sure. When I first saw it, especially if you have a marketing background, all we think about is funnels. And so seeing this actual funnel view and going, oh, wow. Like, now we can actually visualize how many people saw the show somewhere and then how many showed interest and then how many actually listened.

Justin: 02:51

Whereas before, maybe you could get this, like, you know, sometimes people would run overcast ads and they'd get some of this information, but this is very interesting.

Jeremy: 03:00

So, obviously, you and I are marketing nerds. But for the, you know, 99.9 of people who are not, we should probably start with just talking through, like, when we're talking about conversion rates, what are we actually talking about? Like, how would you define a conversion rate?

Justin: 03:13

Conversion rate is, you know, how many people saw the ad and then how many people actually clicked the ad. So in that case, the conversion rate would be you know, you've got a hundred people who saw the ad, 10 people clicked. That's a 10% conversion rate from saw the ad to actually clicked. And then we would even go one step further and say, okay. Of the 10 people who clicked, maybe one person bought.

Justin: 03:37

Well, that's again another 10% conversion rate on that side. So you're just calculating how many people actually took action based on the bigger group.

Jeremy: 03:48

And so you kind of, with your language there, you mentioned, you know, how many people saw the ad. And so, really, conversion rates are the one of the ultimate metrics in advertising where especially if you're doing any kind of digital advertising where you're putting an ad, let's say, on Facebook or Meta or Google or YouTube or wherever else, and you see, okay. This ad got a hundred thousand impressions. This many people, you know, watched it. On YouTube, you can see how many people watch this percentage of the video or click the link and then went on to buy.

Jeremy: 04:11

And so that's a world where, you know, conversion rates are the bread and butter of any kind of advertisers, analytics. But they also show up a bunch of other places. You can go if you use Google Analytics or Fathom or any of these other analytics platforms. You can see how many people went to your home page, and then you can kind of even trace them around how they went throughout the other pages of your website. And so depending on what your goal is with people, you can kind of, use conversion rates to track the effectiveness of your overall system that you've created.

Jeremy: 04:38

So you can get hyper hyper nerdy in in the marketing, analytics world here. And, basically, if there is anything that you can measure, on route to getting people to take results, there is somebody tracking the conversion rate of how people are are moving through that system. And so you can kind of think of it as this funnel where people start a large number of people start at the top and a smaller number of people trickle down to the bottom, which is essentially what Spotify has now given us.

Justin: 05:02

Yeah. And I would say that these conversion rates on their own are generally not that helpful. I think the big gift you've given the podcast community is that you've collected all this information and allowed people to compare their rates to the rates they're seeing in their Spotify dashboard. So if you just go in and look and go, okay. Well, that's my conversion rate.

Justin: 05:25

Is that good? Is gonna be your next question. You've basically answered that for them in this report that you put out.

Jeremy: 05:33

Yeah. And, we're gonna mention this page that I put together, which you can find at podcastmarketingacademy.com/spotify-benchmarks. And so, you can find that there. That'll be linked in the show notes as well. We're not gonna go into all the data because there's actually quite a bit on that page and there's a bunch of helpful resources on how to diagnose what your conversion rates are and what to do based on on how you're kind of scoring there.

Jeremy: 05:53

But, yeah, with most conversion rates, it's, you know, you look at it and you're like, is this good? I don't know. You can always measure against yourself. And so I think that's a good starting point to say, okay, my conversion rate right now is 10%. Let's get that to 15%.

Jeremy: 06:05

And and how do I do that? And we'll we'll look at some of the ways that you can in this episode. But I think to start out, it's probably helpful just to talk through a little bit of the data that Spotify actually gives us. And so there's really kind of a handful of core categories or stats that they give us, and then we can kind of infer or do some calculations to get, a little bit more beyond that. So what are some of those those analytics that Spotify is giving us now in the discovery dashboard?

Justin: 06:31

Alright. So at the top of the funnel is people you reached, and this is the number of distinct people who have seen this episode on Spotify. So I'm guessing this includes, you know, you land on the home page and there's a bunch of cover art there. So that would get counted as people you reached. You're scrolling through search results.

Justin: 06:52

If you zip by a, you know, some cover art there, that gets included. So this is a fairly big bucket. This is actually kind of funny. Can I if I just a tangent here is people you reached is a little it's more like your cover art appeared on a page that people were looking at? It doesn't mean that you reached them.

Justin: 07:11

Doesn't mean they saw it. Doesn't mean they paid attention to it. It just means you were there for some period of time. And this is actually the one metric where they don't give us any sort of rubric for what distinguishes a reach. Like, do they have to have pause on the screen for five seconds or twenty seconds?

Justin: 07:32

So this is the big bucket at the top. It's important to know. It's gonna be helpful once we know the conversion rate. But

Jeremy: 07:38

My assumption is that this is the unique number of users Spotify delivered your show to on their screen. Who knows if they if they didn't scroll down to see it, but it was on their home screen. If they had scrolled, does that count? I I think the other interesting thing here is a lot of times when we're talking about conversion rates, we're talking about impressions, and Spotify does give us that stat, but this is actually unique individuals. And so the calculus maybe changes a little bit if you are used to thinking of conversion rates in terms of absolute impressions.

Jeremy: 08:07

This is a little bit different. This is unique individuals who were shown your podcast who then went on to take some further action.

Justin: 08:11

So That's right.

Jeremy: 08:13

People you reached with number one. The second one that we've got here is people who showed interest. So what does Spotify give us a definition for interest here?

Justin: 08:23

Now this is where it gets kinda saucy because this is the number of distinct people who have gone to the episode page, added this episode to a playlist, or played this episode on Spotify for zero seconds or more. So in terms of, like, the value chain here, we've gone dramatically from people who may have seen your cover art to they've actually clicked through and said, oh, that episode looks interesting or, oh, I should add that to a playlist or, oh, I should actually play this episode. So going from people you reached to people who showed interest, that is a very interesting number.

Jeremy: 09:03

Yeah. And then the, final step in the chain here is people who streamed. And what is this is, you know, one of the maddening things. Apple's got their definition of what counts as a a streamer play. Spotify has their own.

Jeremy: 09:14

What is Spotify's definition that they give us here for a stream?

Justin: 09:17

So that's anyone who played the episode on Spotify for at least sixty seconds. You know, I I used to have a podcast called six seconds where every episode was only six seconds. So I wonder if I would not get mine counted here. It's like sorry. My stats would be nothing, because it

Jeremy: 09:38

You need that, that tangent expander tool. When Spotify gets that in, then here we go. We're cooking.

Justin: 09:44

So, yeah, to get anybody to listen for any period of time is a meaningful so this is still very top of funnel, I would say, though. They could add another section here that is, like, how many people made it at least 70% of the way through the episode.

Jeremy: 10:01

Yeah.

Justin: 10:01

But it's still interesting to see the conversion rates along each step here.

Jeremy: 10:07

Yeah. And they do so Spotify does give us a chart that charts your follower count. And so you could potentially try and correlate some of this a little bit, but they don't attach it to this actual funnel here. Probably because a lot of people listen to a show and then they end up following it some amount of time later in the future. And so it becomes a bit murky onto, you know, the chain of events here.

Jeremy: 10:28

Mhmm. But that is, you know, something that you can look into, in your own Spotify dashboard as well. So those are the, essentially, the three analytics, the data points that are included in the funnel. So people you reached, people who showed interest, and then people who streamed. And so those give us these kind of two different conversion rates, which is the what I'm calling the awareness to interest conversion rate.

Jeremy: 10:49

So people who were aware of the show or at least it was delivered to them who showed some kind of interest in it and then the interest to stream conversion rate. And so people who took some initial click into the show and then listened, for sixty seconds. But they also give us, a couple other other analytics here, which are disconnected from the funnel, but also play an interesting kind of role in our understanding of how our show is doing. And the main one here is the impressions. And so we mentioned before that in the funnel, we're talking about individual users.

Jeremy: 11:16

Here, when they're talking about impressions, they're saying, okay. How many times was either the show or any one of your episodes displayed to somebody? And so what we can calculate with that then is we can actually see how many times on average on a per user basis Spotify showed your show to them. And so you you can see in some of the shows that I have the data for, some shows were shown something like 15 times per person on average, whereas other shows were only two times per person. And so we don't necessarily know why that happens, but you can do some of these calculations and and see how Spotify is promoting your show to people.

Jeremy: 11:49

And so that's the the one thing we can kinda calculate and infer from the data. The other thing is we can calculate the overall conversion rate. So people to streams, and so they give us these two conversion rates, the awareness to interest and the interest to stream. And then we can take the overall of those, how many people who, were shown my podcast ultimately went on to stream sixty seconds. And so that's the the data they give us here.

Jeremy: 12:11

And the the one other thing, that we didn't mention is under the impressions, they actually break that out into four different, locations within the app. And so the first is Spotify home. So that's in the home screen. If you click over to the podcast tab, then there is the search. And so, obviously, if you're searching for a phrase and shows get recommended and come up, that's gonna be there.

Jeremy: 12:28

Then you have the library, which is if you use Spotify, it's in your left hand sidebar. That's your library there. And then the final one is other. I assume that that might be some episodes had a recommended episodes at the bottom of them. And so I'm guessing that is probably in that category, and maybe there are other things where Spotify shows, podcast to people, that are not in any of those prior three categories.

Jeremy: 12:51

So

Justin: 12:52

Yeah. I'm wondering if some of that is clips and other of their beta features as well.

Jeremy: 12:57

Right. So you mentioned before that, you know, this data isn't really all that useful if you don't have any benchmarks. But if you do, I'm curious, like, what does knowing your conversion rates in relation to a established benchmark allow you to do as a creator?

Justin: 13:15

Well, I mean, having the average the way that you have it in that report, I think, is actually really helpful. Because if your conversion rates are just way lower than the average, then something is wrong. That could even be the show itself. Like, you've got a fundamental problem. So I like these things because sometimes people are putting a lot of effort into a show, and there might be a fundamental problem they're not seeing.

Justin: 13:44

So I think if you could compare it to, you know, an average benchmark that's already interesting, and then for yourself, it gives you something to improve on. So now let's try some experiments and see if we can increase the number of impressions and then increase the impression to interest conversion rate. And over time, you can try to get lift. And it gives us a little bit of insight also into the black box that can be these recommendation engines and, you know, how are they promoting my podcast or not promoting my podcast? It gives you something to look at.

Justin: 14:22

All of these things that we sometimes say, you know, like, people will say, well, adding a video to Spotify will give you lift. Well, you can test that out. Like, add video and see if video episodes get promoted more than audio only episodes. So you can have a hypothesis and then test it out.

Jeremy: 14:42

I think for me, the thing that I was most excited about was the diagnosis that it allows us to do. Mhmm. And so I think in podcasting, there's this kind of, like, plausible deniability that you could kinda put your head in the sand and say, no. No. No.

Jeremy: 14:55

My cover art's fine. My show title's fine. My episode titles are fine. I don't need to worry about those. And, like, that's not the reason I'm not getting more clicks into it.

Jeremy: 15:02

And you could do some really manual testing with this. And so, you know, one of your tricks that you've mentioned a lot of times is going to a conference and just, like, pulling up, you know, your cover up, maybe a list of competitors or doing a search and asking people, you know, which would you click on and and seeing, you know, which one they pick. Mhmm. You can do that in a bunch of different ways with a bunch of different variables, but that's not really that easy to do all the time for all of us. And the thing about a dashboard like this is that it is unbiased by how we ask the question or things like that.

Jeremy: 15:27

And so it's like people that Spotify thinks should be interested in our show. I think that's the important thing to note here too is that Spotify wants people to engage with content, and so they are trying to match users with podcasts. And so if they're showing our show to someone, based on the data they have, they suspect this person might be interested in a show like ours. And so if they show it to a thousand people and none of them click into that, that's now a signal to Spotify saying, like, either we're showing this to the wrong people or something about the show is not interesting and not worth promoting. And so I think that this analytics dashboard now allows us to actually pinpoint some of the potential issues.

Jeremy: 16:04

And we're gonna talk a little bit more about how to diagnose specifically, based on, you know, high and low conversion rates on either the, awareness to interest or the interest to stream. But maybe to start off, let's dig into some of the the benchmarks here. And so I got about a hundred people to submit their Spotify dashboard data. This was a range of podcasters. Some have millions of impressions in Spotify in a thirty day period.

Jeremy: 16:26

Some have basically, like, a hundred or 200 very low numbers. So we've got the whole range of vastly different types of podcasts, different purposes. So it really covers the spectrum here. And, what are those kind of benchmarks that, this group kind of surfaced here?

Justin: 16:39

So in terms of awareness to interest, 8.6% was the average conversion rate. So I saw something and then I clicked on the episode to check it out. And then from interest to stream, 63% was the average conversion rate. So I saw it. I went to the page, and then I actually clicked play and listened for sixty seconds.

Jeremy: 17:05

Any initial reactions to those numbers?

Justin: 17:08

I actually have a few other questions. My my guess is that folks with less traffic overall and just, like, less streams overall, my guess is that their data will be different and could and could actually be wildly skewed in either direction. So if you have a hundred fans that listen to your show and they're very committed, you might get, oh, I I had a 20 people have awareness about an episode, and then 95% of them click through on the episode, and then another 90%, you know, actually listened. It it it's gonna really depend on how big your audience is already. As I looked at some of the bigger shows, I definitely saw higher awareness to interest conversion rates up into the 30% range.

Justin: 18:03

So that's interesting too. So I think it's a nice place to start. Like, if you're getting way below 8.6% for awareness to interest, Something might be wrong. And I think if you're getting way less interest to stream, the interest to stream conversion rate actually seems quite high to me. Meaning Mhmm.

Justin: 18:23

Spotify has probably tuned this fairly well that if you actually show interest, you're highly likely to click play. That was a lot higher than I thought it would be.

Jeremy: 18:34

What stands out to me is how much of the battle for winning over a new listener is kinda won and lost at that awareness to interest stage. And so you can kind of optimize all the internal things. You can create an incredible show. You can really hone your show description that's in your listing and your episode titles. But if you're not getting people to click play into the show in the first place, all of that work kind of doesn't really matter that much.

Jeremy: 19:00

And it's not to say it doesn't matter to create a great show. People can still talk about it word-of-mouth and there's all these other things. But from a discoverability standpoint of getting people to see the show to go to click play, I think that this really puts the emphasis on the show title and the, cover art of the show. And so that's this this number that is way lower. And it's like, okay.

Jeremy: 19:18

If you can get somebody to click in, here, the average 63% of people, you know, the odds are that they're going to click play and stream an episode for sixty seconds, but less than one in 10 people are actually clicking into a show when they see it. And the other thing, again, this is people. And so when we look at some of the shows, individual people are shown a podcast on average multiple times. And so if people are seeing that show multiple times and not clicking play, you know, that's something to to take into account. There's a whole bunch of stuff that we

Amit Kapoor: 19:47

just don't know about how this is calculated on Spotify's back end. And so it could

Jeremy: 19:47

be that that impressions per back end. And so it could be that that impressions per Spotify user are inflated by people who subscribe to the show or follow the show, and then they see, you know, dozens of episodes. And Spotify only shows the show one time to people who it thinks it might be interested, and they don't click play. So we don't really have a window into that. But I think to me, that's the really the big thing of, like, the thing to focus on, the highest leverage, that you have here in this system is focusing on title and cover art.

Jeremy: 20:17

Because if you can get that number up, then you're kind of rolling downhill at that point.

Justin: 20:22

I do think there's still a there's a fundamental like, I always say that product is marketing, and I can see a certain type of podcast doing better in these scenarios than others. And so I for a certain type of show, these stats will be very interesting and helpful. And I can also see a certain type of show where this just doesn't really apply as much. And you could try, you know, tweaking all these things, which I think are important to cover art, titles, descriptions. But there's a fundamental kind of mismatch between this kind of discoverability and the way your show is structured or the topic or whatever.

Justin: 21:05

For example, like, a an interview show that is highly dependent on the guests and the, name recognition of a guest. You can imagine that if you're really into, Billy Idol and a Billy Idol podcast episode shows up on your home page, you're gonna be much more likely to click through and listen to that. So, yeah, there's some other factors there that I think are worth keeping in mind as we move forward.

Jeremy: 21:31

The other thing that's kind of interesting is, you know, I looked at of the high impression shows. And so there was about 10 or 12, something like that, that that were getting over a hundred thousand, impressions in the previous thirty days. And so Spotify in their dashboard, they only measure the kind of from today back thirty days. You can't filter by past dates or anything like that, which is a little bit frustrating. But, we'll take what they've given us for now.

Jeremy: 21:52

And so these shows, a hundred thousand impressions over the past thirty days, there were some interesting data here. And, again, this is not to say that every show should be comparing themselves to this because not every show has the potential. Like, our show is never gonna get a hundred thousand impressions in Spotify because it's so incredibly niche. Like, there is not the audience out there to be delivered those impressions. And so one of the things that

Justin: 22:13

put, interview with Billy Idol in one of our episode titles.

Jeremy: 22:16

Maybe. And we had that, tangent expander too and the auto too. We just crank everything up, the vocal fry, all the effects up to 11. There we go.

Justin: 22:24

Vocal fry.

Jeremy: 22:25

So, like, one of the things with high impression shows was that, 70% of the shows were kind of broad audience, which actually makes sense. Like, if you have a mass appeal show, there's a larger pool of people to tap into. And so this is not to say that every show should try to appeal to the biggest audience possible. Like, that's actually the hardest show to market. But if you are a solid show or a great show in that category, your ceiling is way higher than a show like ours or any other huge show.

Jeremy: 22:52

The other thing that was a little bit interesting here was the show purpose. Now I define these based on what I could see from the descriptions and the titles and things like that, the episode titles. And so I categorized 60% of the high, impression shows as pleasure givers. And so there are things that they're, like, not useful in a way of, like, a practical problem solver type approach. And so that is up almost 30% or 27% higher than other shows in the the kind of main category.

Jeremy: 23:23

And so, 60% of shows were actually just things that people are listening to to unplug or unwind their entertainment. They're just like, you wanna just, you know, immerse yourself in something, which I think is, again, more indicative of mass appeal shows. And so, the the second most popular was problem solving type shows at 35%, but, really, 60%. They were more entertainment kind of pleasure giver type shows. And then the last thing that was interesting about the high impression shows, was that 45% of them were solo shows, which I thought was quite interesting.

Jeremy: 23:52

And this was, 14% higher, degree of solo shows than the general audience or the pool of all the shows here. And so interview was second with 30%, and then the rest were split between, 10% co hosted, ten % narrative, and there was one daily news show that was a a tiny percentage as well. So some some interesting trends there on the high impression shows, but I actually don't think that's what's worth paying attention to. I think it's much more the conversion rates, which are where you can kind of improve you know, given the potential audience that you have, you can kind of attract more of them back to your show.

Justin: 24:26

I would also say, like, I'm looking at my stats for an inactive show or a show where we don't publish very often. And the these stats are definitely more interesting to people who are publishing regularly. If you have, like, a a serial show that's been out for three years, maybe it'll be interesting. I I you know, you should still look at it, but it it seems like a lot of this even in the decisions they've made to kinda highlight impressions in the last thirty days, this is very focused on people who are actively publishing Yes. Within a thirty day window.

Jeremy: 25:04

So we've kind of talked a little bit around you know, we have these benchmarks, and we can kind of diagnose some of the issues. And then the next step is to actually run some experiments. And so I know we've talked about this in season one of the show, some potential experiments that you could run. But how would you kind of approach, using these conversion rates to test different hypotheses and and kind of pull different levers that, you're able to with your show?

Justin: 25:28

Yeah. I mean, when we do podcast marketing tear downs, we almost always focus on podcast title, podcast cover art, and then description, episode titles, whether or not there's a teaser episode. So my guess is those are really the levers you can pull outside of what topic you've chosen, outside of, you know, some other things. But I think if you're just looking for a nice benchmark, like, oh, well, we we've had this cover art for three years. What happens when we change the cover art?

Justin: 26:03

Does anything happen? And this is a nice way to test against that. You already have a, benchmark to test against because most of us haven't changed our cover art in a long time. Most of us have not changed our title in a long time, description, etcetera. So those are some of the levers I think you can pull here and see if you can get some lift.

Jeremy: 26:23

Yeah. And I would just like if you are thinking about doing an experiment, I would just put yourself in your listener shoes and open up Spotify and just go to the home tab and think about, okay, here are the shows that show up here.

Amit Kapoor: 26:34

Mhmm. What

Jeremy: 26:35

is there that is present to me that is influencing my decision? Anything that you can see on that screen, if you can change that, that is something that is going to influence listener behavior or potential listener behavior. And then you click into a show and you look at the screen, you say, okay, what are all the different elements on the screen that I have control over? And you say, okay, well, once they click in, then I can edit my description, I can change my episode titles and I can, you know, upload a teaser episode and, you know, the teaser episode probably, like, I think if there is a lower barrier to entry to getting somebody to listen to anything on your page, and so a teaser episode that's two minutes is a much lower barrier to entry than a sixty minute episode. Or if all the episodes are sixty minutes, that's probably also going to get more people to stream an episode, probably that episode.

Jeremy: 27:20

And so opening up Spotify and just seeing what you have there and then going into the back end and playing with those things, is is basically kind of the the approach here.

Justin: 27:29

I wanna note that this session is interesting paradigm shift from the way episode consumption used to work, which is you used to just get a chronological feed basically of what's new. And my guess is a lot of people were scrolling through episode titles bait on, you know, the what they were already subscribed to, and then they're like, oh, what seems interesting? Or and this resulted in, you know, a lot of kind of esoteric, cute titles that were kind of, like Yeah. Inside jokes and things like that. And I can see your approach in an algorithmically driven world.

Justin: 28:06

And I I don't know if we've mentioned this, but, like, the Spotify homepage is by far the biggest driver of impressions. And so if that's true, way more than search or library, if that's true, then, whereas the old world was the library first. Right? It's like, what's in your library? You're scrolling your library.

Justin: 28:26

Now it's what am I being shown on my home page, and what is kind of, like, grabbing me in that moment. So it's it's gonna be way more, like, YouTube style thinking here. How do we grab people on the home page versus, you know, how do we bring back our regular listeners or those kind of

Jeremy: 28:46

questions. It is, worth noting here that some of the numbers, in regards to where the impressions happen. And so, what we see based on the, data that people submitted to me, and I compiled this, the Spotify homepage accounts for basically 65% of all impressions. And so well over half of all the impressions that people have of a podcast in Spotify come on the homepage. And then the fairly distant second is search at 26%, which I thought this would just be way higher.

Jeremy: 29:14

I thought the majority of it would be through search, but actually, this is Spotify. On the homepage, it shows both shows that you have already subscribed to or engaged with in the past, but also recommends new shows. And so some of those are going to be from your library even though it's not in what Spotify designates as the library, the sidebar. Mhmm. And some of them are recommended.

Jeremy: 29:33

And then, the library is at, 9% essentially of impressions happen in that library tab. And so I I'm curious. Again, we just don't know what user behavior is on Spotify. Like, it could be that many people treat their home tab as their library.

Amit Kapoor: 29:49

Mhmm.

Jeremy: 29:49

And so they go there and they just click on their episodes from there. Like, I mean, I I don't really use I use the library for music and Spotify. I don't listen to podcasts and Spotify. I use my library all day every day to find albums and artists and, you know, anything else. And so it could be that people treat it that way for podcasting as well, but their whole at least on desktop, their whole UI is very geared towards that home tab.

Jeremy: 30:11

Like, the the sidebar is kind of hard to navigate. And so it it wouldn't surprise me if, you know, partly home is a little bit like the traditional feed just with more recommendations built in.

Justin: 30:22

Yeah. I I mean, this is what we're seeing on YouTube as well. It used to be that you would go to your subscribed tab first and then just see, oh, what new videos are there from the people I subscribe to. One thing I will note is that the long tail so if an episode has been out for a while or a show, hasn't published an episode in a while, search is a much higher percentage of discovery. I've seen up to almost 50% can be, search based.

Justin: 30:53

So people are looking for past guests. People are looking for a topic. You're gonna see in the long tail way more search, but home is still king by far.

Jeremy: 31:03

Yeah. And the one other thing that I wanna mention on that note regarding episodes is that the overall analytics that show up in your main Spotify analytics dashboard, you go over to the discovery tab, that is for your show as a whole and all the episodes within it. And so it could be an impression of the show being recommended or an individual episode, but you can also look at the exact same dashboard within any individual episode. And so you could look at those and they'll show the same funnel and you'll be able to see, hey. Some episodes have a much higher conversion rate from awareness to interest or interest to stream, and you might be able to pull some additional insights out of that of which episodes are maybe outperforming others.

Jeremy: 31:41

And maybe that gives you some insight into, oh, maybe I should, you know, do more episodes on this topic or maybe my title was really good there and maybe I've stumbled onto something that I wanna replicate. And so there are two ways to kind of use this data or or view it. Yep. So let's maybe close this out with some best practices when it comes to experimentation because I think it's one thing to say, okay. Like, we know what some of the variables are and now let's, like, make a bunch of changes and see what happens.

Jeremy: 32:05

What would your approach be to actually running a more controlled experiment that actually gives you some useful data?

Justin: 32:11

Yeah. You only wanna change one variable at a time. If you change too many things, you don't know what change actually created a meaningful effect. So what we're trying to minimize is the number of variables at play. There's always gonna be other variables like, you know, you might have a big guest one week.

Justin: 32:31

You can control that, but here's the variables you can change. So, you know, if you're gonna add or change a title tagline, that would be one thing. Does that help? Mhmm. Does that not help?

Justin: 32:44

I think you had a case study where someone went from, like, mindfulness podcast to mindfulness psychology, and there was a big lift or something like that?

Jeremy: 32:55

Yeah. So this was one of my clients, Sam Webster Harris. He actually has the name Sam Harris is his first and last name, but he's not that Sam Harris, which we have a discussion on this that I'm gonna share one day. But he actually thinks that hurt his conversion rate because people clicked in thinking this was the other Sam Harris and then were disappointed. Oh, this isn't that Sam Harris, so they left.

Jeremy: 33:12

And so he thinks that that was actually a bit of a a headwind that he's had to work against. But he yeah. His old show, was called the Growth Mindset Podcast, and he changed it to Growth Mindset Psychology. And he also so he did a he committed a couple of, flaws with his experiment here, which he acknowledges that he was actually working on a bunch of stuff. And so he had been tightening up his episode titles for one already, but then he changed the name of the show to growth mindset psychology.

Jeremy: 33:39

Andy changed the cover art, which was a subtle modernization of the cover art. Like, it wasn't a complete overall. He actually did a big overall first and it tanked his his numbers. And then he Interesting. Course corrected and was said, let's actually just make the existing cover art a little bit cleaner and more modern and less amateur looking.

Jeremy: 33:56

And he ended up adding over 2,000 downloads an episode, within about a month, and then it kept growing from there. And so, like, that is, you know, a couple small changes to that packaging that had a huge impact on his show. And so, you know, that's not gonna say that that's gonna every show is gonna see those results. He was already getting some traffic and some impressions because he has a long running show that is was already doing pretty well. But it is interesting to see how the cover art can both hurt or, drastically increase the downloads.

Jeremy: 34:22

And so that's this kind of principle in action here of of doing experiments and seeing, you know, what what works and what doesn't.

Justin: 34:28

Mhmm. So let's say people wanna set this up. My guess is the first thing they'll do is take a a literal screenshot of their existing stats. Because there's no way of, like, bookmarking your existing stats or running an AB test inside of the Spotify dashboard. So you're gonna have to manually screenshot your existing stats.

Justin: 34:48

Anything else in terms of the setup that people should know?

Jeremy: 34:51

Yeah. I would screenshot that or put it in spreadsheet, and I would just write yourself a hypothesis on, like, what is the variable I'm testing, what do I think is going to happen, and then check back in thirty days. And so I would probably run this on a thirty day window because that's what Spotify gives us. And so we say from, you know, whatever, January 1 to February 1, I got, this many people were showing my show. This was the conversion rate, at each of the conversion rates, and maybe I look at impressions as well.

Jeremy: 35:16

And then I say, okay. From I'm gonna make the change at February 1, and then I measure from February 1 to March 1. And I see, okay. Was that any different from January? And the other thing to keep in mind is when we're talking about limiting variables, it's saying, like, okay.

Jeremy: 35:28

Let's change the the title or the tagline of the show, but then also let's keep everything else the same. And so I'm gonna publish the same amount of episodes. I wanna try and control that to make sure that, you know, I'm actually comparing apples to apples.

Justin: 35:40

Yeah. You're right. Like, this is the time to just keep consistently doing what you were doing before. So if you're publishing every week, just keep publishing every week. Don't drop a, like, a bonus episode in there because that'll that could throw things off.

Justin: 35:53

Just, like, if you're once a week, just keep publishing once a week and then try to compare that over a a thirty day window.

Jeremy: 36:01

Yeah. I think the last thing that I would just add on the experimentation front is assuming that you don't actually know anything. And I think that this is a mindset that I never really understood. I I thought, like, Facebook ads experts were just wizards that they just knew how to write the copy and do all the targeting and set up all this technical stuff on the back end to be able to just make ads run profitably or get people to your podcast or email list or whatever. And what I know now after having been in marketing a lot more is that basically every Facebook ads expert goes in with some assumptions that they are almost certain are gonna be proven wrong.

Jeremy: 36:35

And so you'll often hear people in this world talk about, you know, this kind of two to three month window of optimizing the ads. And, again, this is something that I thought was about training the algorithm, but what I now know is that it's about you as the person running the ads, testing different things and just slowly pruning until you get to, oh, this is the thing that works best. And so you run, you know, six different headlines and you have six different graphics and you slowly whittle it away until you're like, okay. Out of all the permutations that are possible, this is the thing that is performing best, but I'm gonna keep testing that as well. And so you just see this so often if you do AB testing with headlines or you come up with everybody's, I think, had that episode that for some reason, that one got a bunch of downloads.

Jeremy: 37:13

So you got all this feedback on it and you're like, why that episode? I don't I just don't understand that. And so this is true for all of these kinda different variables that you're playing with. And so going in and just thinking, like, the way that I'm going to get better and improve my conversion rates is just testing things constantly. Small tweaks here and there.

Jeremy: 37:29

And over the years, the months and the years, it's actually going to improve slowly but surely to the point where now you're hopefully outranking all these benchmarks by quite a bit. Mhmm.

Justin: 37:38

I would also recommend that people add other qualitative sources of data to this. So one thing I've just started doing, I I just started a new podcast on the trailer episode and the bonus episode that we've put out. I encourage people to go sign up for the email list, and I say, I'm gonna send you an email right away with some questions. And eventually, I'm going to use that automatic email to ask people, hey, how did you find the show? What drew you to the show?

Justin: 38:08

What brought you here? And I think adding in those qualitative answers to what you're seeing on the quantitative side here will be helpful. It's gonna help you check your assumptions. Maybe you're used to just getting answers like, oh, I had a friend tell me about it and I went and checked it out. Maybe you start getting answers like, oh, like I saw it on the Spotify homepage and the cover art looked interesting.

Justin: 38:30

Well, if you've recently updated your cover art and then that qualitative response just starts showing up more and more often, I think you can start to say, okay. These activities are really correlated. Like, I changed the cover art and we saw Lyft, but now, anecdotally, people are actually telling me that that's what made a difference.

Jeremy: 38:50

So for anybody listening, if you do start experimenting with any of these variables, looking at things like the title, the cover art, your show description, episode titles, teaser episodes, all of these kind of external and internal packaging elements that will influence, these conversion rates, both the awareness to interest and the interest to stream, we would love to hear about it. So send us an email. You can find the email in the show notes for this episode And, personally, I would be fascinated to see what people are playing with and how that is impacting your discoverability in Spotify.

Justin: 39:20

And there's a whole other part of this discovery screen that we didn't talk about, which was sharing links where you can actually create a link to an episode or a show and then track how many people visit that link. So if you're promoting it on social media, we'll talk about that in the future. But just so you know, there is this other link tracking piece of this that's also interesting.

Jeremy: 39:40

So there is a lot more information on this Spotify discovery dashboard if you want to look at even more benchmarks and data. Again, you can find that at podcastmarketingacademy.com/spotify-benchmarks. And there's also a bunch of recommendations on how to diagnose, you know, the different kind of conversion rates or combinations of, you know, a high awareness to interest come combined with a low interest to stream or any of the other variables and how to think about, like, what might be the problem and what do you do about it. So again, podcastmarketingacademy.com/spotify dash benchmarks. And other than that, I think it's time to crank up the, tangent extender and maybe the, the auto tune and play ourselves out.