Where to Start With Advertising Attribution in Podcasting with Pete Birsinger and Cameron Hendrix

Jeff Umbro: This week on Podcast Perspectives, how do you know if the ad that you just bought in a podcast is working?

Cameron Hendrix: It's a much easier business to operate when there are, you know, more folks out there evangelizing the fact that you need data to measure podcasting.

Jeff Umbro: Welcome to Podcast Perspectives, a show about the podcast industry and the people behind it.

I'm your host, Jeff Umbro, founder and CEO of The Podglomerate. Today on the show, we're chatting with Pete Bersinger, founder and CEO of Podscribe, as well as Cameron Hendrix, founder and CEO of Magellan AI. Both companies measure how effective your podcast ads are using prefix and pixel technology. In essence, you can see how many people heard your podcast ad and then went and purchased your product on a website.

That's actually a very new and novel thing in the podcast industry, and it is what is helping the podcast industry to expand with a lot more brands. Historically, one of the larger companies in podcast measurement tech is called Chartable. Chartable is sunsetting as of this week and may have already sunsetted by the time you are listening to this show.

Part of the reason that I wanted to have Pete and Cameron on was to discuss what happens next and what alternatives and opportunities there are for publishers today who want to continue to use this technology. We hope that it's helpful and please reach out to us at listen@thepodglomerate.com if you have any questions about what you should be doing as a publisher.

Pete Birsinger: I'm pete, the founder and CEO of Podscribe. We provide measurement, verification, and research for all of your podcasting and, more broadly, now, audio needs.

Cameron Hendrix: I am Cameron. I'm one of the co founders at Magellan AI. We are a platform for advertisers and publishers to accurately measure podcast performance and scale audio campaigns, trying to make sure that, you know, we're helping advertisers understand, you know, what's performing well and where they can scale and where they go next.

And so we can ultimately all grow the industry together.

Jeff Umbro: You guys run measurement companies that also like have a bunch of tools that are derived from those measurements. Is that, is that accurate?

Cameron Hendrix: I think that's like a fair, you know, statement. I think like the, I think measurements, like it is, it's a pretty broad term, right?

So there's like measurement in terms of like actually looking at like download data and that's one aspect of it. There's also a measurement in terms of like, we, we prior to adding attribution, you know, as a feature set, you know, we were going back to 2017, like starting to identify ads in podcasts because back in the, back in the day, you know, we were working with a network that was actually tracking, like literally had a spreadsheet that they just like would pass around and like add names to the list whenever someone heard a new advertiser on podcasts.

Like there was like no visibility in the market as like who was active. So I think there is, you know, an aspect of, of measurement to that as well. But you know, worth pointing out, like we, we try to think about like different sources as like, in one case, like kind of being public and another case being very confidential for the advertiser.

Pete Birsinger: Both us and Magellan AI, we We only, you know, we didn't start with the measurement, the attribution side of things, like Cameron's saying, I think his, you know, their competitive intel was pretty revolutionary at the time, there was nothing, nothing else remotely like it whatsoever, and we started a bit there, maybe a bit more of a focus on the, the error check side of things for the buyers versus the research. But you know, we started, you know, not an attribution at all, but then it became clear two, three years ago that there was now a huge hole in measurement with Podsights being acquired. And just, you know, and the more we got into it, the more we sort of, I guess, really found was that nobody is really, there's still a lot more to be done in measurement.

I wouldn't say brands are like, we nailed our podcast attribution. It's so solved. Like even now, I don't get that impression from people. So it's good. There's still a lot more work to do, but I would say the foundation that we have of air checks and research, I think has helped us for sure, and I assume probably Cameron as well, build a better measurement product because when it's all integrated, it's nice. You don't have to go to three different dashboards to see things. You know, the system knows which episode had your ad.

So there is, there are definite advantages to having them being integrated.

Jeff Umbro: So essentially it's like the data collection from the measurement turns into transparency and reporting for like the different folks who want to use your services. Who are those folks? Am I correct in saying that it would be like podcast publishers and podcast advertisers or just advertisers and publishers in general?

Cameron Hendrix: Yeah, I mean, I think it, it is podcast publishers and advertisers, you know, I think there's different aspects of the data that each of those different, you know, types of companies lean into. So advertisers obviously looking at the market and trying to figure out where they should spend dollars and, you know, accurately understand where they've, you know, what's performed for them and, and where they should double down.

On the publisher side, you know, understanding, you know, where advertisers are spending dollars is really important. And as well as kind of getting into, you know, the weeds on, on measurement to make sure that they're, the product that they're bringing to advertisers is really high quality as well. So yeah, it's, it's definitely like both, I would say industry wide, right, in terms of like, there's a use case for everyone in the industry, the use case is typically a little bit different when we see them come to Magellan AI as to like what they actually ultimately want to get.

Pete Birsinger: When we get clients' data for the measurement and the campaigns they give us, we do keep that separate and we do have like a separate research database, you could say, so, you know, when the client's giving us their campaigns, they don't have to worry, oh, this is going to, you know, just go out the other end and me and Podscribe, Podscribe's research for all the other advertisers.

The research is computed in a bit of a different way where we monitor the top shows and put the research out there. But yeah, I think it's still, the research is certainly, you know, quite a useful product both for buyers and sellers. I think obviously, you know, as a seller to find who's spending where, perhaps to vet shows you may be acquiring, I think those two things are quite useful.

But for buyers too, just to see what their competitors are doing and to make sure the show they're buying on to see are the advertisers that have found this show renewing, you know, are they, have they been buying or just a lot of them trying at once and quitting, or more recently to, to see the, the ad load. We put out a piece earlier this year with, with Oxford Road indicating, you know, as ad load goes up, you know, as a greater portion of an episode is ads, performance goes down, which is probably not the most shocking conclusion ever, but there was a definite relationship. So I think maybe that's entered a bit more on buyers' minds as they look at podcasts. So we'll show that data point. So, useful to a variety of folks.

Jeff Umbro: Yeah. Well, it's very funny to me because I, it's like the, oh, with great power comes great responsibility because you guys have access and provide access to the buyers and the sellers to this mound of data that hopefully most people are like understanding what they're looking at.

And as a publisher and a seller myself, it's kind of funny because I'm, I love the tools that you guys both provide. It's very useful. It's also terrifying because sometimes like, you're like, am I going to, you know, match up to what I'm seeing here? And I don't know if you guys have thought about this very much, but like, what's the difference between Magellan and Podscribe?

Like what would make a good client for either platform as opposed to the other?

Pete Birsinger: Magellan has been a bit more focused on publishers historically, like a bit more focused maybe on the research side of things. We had, at least from my perspective, more focus on the air checks and the, the verification side of things.

So a lot of our clients have, I think we're maybe a bit more skewed honestly towards the, the buyer side, just because of our history with the verification, so I think there is sort of one, one piece there. I know, you know, Cameron's, they've got a great research platform and that's like historically, you know, been, been pretty revolutionary on, on their side of things.

I would say too, what I've heard in other cases is in some cases, maybe we're, a bit more, or, you know, willing perhaps for better or worse to do custom, custom work for, for clients, depending on who it is, which I think is a pro and a con. I think in some cases, maybe it means we have slightly too many features or some of them, you know, don't, you know, some of them maybe aren't as like maintained or well announced as others, but we may be able to be more flexible.

Cameron Hendrix: So going back to 2017, when we launched, right, I was literally like having to convince the biggest folks in the industry to like take a call with me and to like, look at this thing that we've made and like, it was not obvious that like, you know, there was necessarily like the right, an opportunity there.

Like when you look at media markets overall and just like how things evolve, like IAS and DoubleVerify exist, right? And they co exist and compete and are direct competitors. And, you know, we, Magellan AI, like compete directly with Podscribe. So I think that it's actually a good thing, you know, for the industry and honestly a good thing for, I'd rather be in a business. It's a much easier business to operate when there are, you know, more folks out there evangelizing the fact that you need data to measure podcasting.

So I think that's like, you know, I always get asked like, well, you know, Podscribe, you know, what do you think about like, you know, where they fit in the industry and I'm always like, bring it in. Let's do it. Like, this is like the water's warm. This is awesome. And I think it's, you know, only going to continue like as the industry grows.

Like we had an opportunity early on to move partially because the industry was small and now it's growing. And I think as it grows, we'll see bigger players start to look at this space and get a lot more, you know, serious about, you know, podcast advertising as a channel, which means that, you know, you know, Pete and I are going to be like competing even more with each other and with bigger players, but, you know, I guess going back to the kinds of companies that, that work with us.

So I think we've focused on, you know, partnering with brands in the context of helping them like scale campaigns. So we, I think it's really important to, you know, accurately attribute like podcasts, which means like not over attributing, but also not under attributing results so that you can identify what you should be, you know, what kinds of podcasts you should be spending more on, where you should be going next.

Jeff Umbro: What is the like value add for somebody working with your company? How are they like specifically using these different softwares?

Pete Birsinger: For buyers, I'd say it's essential intelligence to make sure you're getting what you paid for and to know how your campaigns are performing for you.

Jeff Umbro: And then you can use that, those learnings to determine like, you know, I want to iterate and do this. I want to do more of that, less of this. As a publisher on my end, we get pixels from one or the other or both all the time. So on the sales side, Cameron, like what's your elevator pitch?

Cameron Hendrix: Yeah, elevator pitch. Well, you know, you gotta know where, what's running where and, and how to effectively understand performance. So publishers trust Magellan AI to grow ad sales and drive content acquisitions, make ad ops efficient and ultimately measure performance of their campaigns so that they can articulate the value of their advertising to their clients.

Jeff Umbro: It's also like every podcast publisher, right?

Cameron Hendrix: It is. It's pretty, pretty wide adoption. We were again, for your, you're very lucky to be as early as we were in the space. And I think the other really, again, fun thing about podcasting is that people tend to talk to each other and listen to each other and I don't think there's a, I think it creates this like.

Interesting space for companies like ours and companies like Podscribe to come in and like learn about people's challenges. And, you know, there's a lot more openness it feels like, I don't know, maybe it's because we're in an industry where we all talk to each other and listen.

Jeff Umbro: It's also very new. I feel like we're all building the plane as, as it flies.

But if you're explaining this to like a kid in high school, like how would you say that your services actually function?

Pete Birsinger: So say you're BetterHelp and you're trying to find your ad that ran on The Daily, hypothetically. What we'll do in that scenario is we will transcribe every episode of The Daily, and then we'll label ads in our transcripts there.

And then if we find a BetterHelp ad that matches roughly where their campaign is, we'll match it to their dashboard. So that's how we do the transcription and the air check side of things. And for, in the case where the episodes may be changing their ads, we have, what we do is we take a snapshot of the episode.

So we'll download it, oh, on Monday, and we'll retry it on Wednesday, and then Friday, just so we take a snapshot at multiple times and transcribe each of those. So then people can see, is the ad going in and out, or maybe it was in this version, but not that version. So that's how that, that side of things, thing works.

But on the measurement side, which maybe people are more interested in now, it works largely by matching IP addresses. So podcasting for better or worse does not have as much data as other channels. So for instance, if you're Google or Facebook, you likely have the person's email, you know, you know more about them than they probably know themselves.

But in podcasting, all that we can really see, or anybody can really see, is the IP address. So say Jeff, you download an episode of The Daily and we're, we're tracking that. All we'll see is, oh, here's Jeff's house, his home IP address. Then if you, Jeff, go to betterhelp. com, say in the next week and you're also on your home wifi, then, oh, same IP we saw get exposed to the BetterHelp app and then go to the website.

So by and large, it is on household matching. That's kind of the bulk of the, the cases.

Cameron Hendrix: The kid in high school is like an AP, AP class. He's like, Air checks.

Jeff Umbro: He's like, Oh man, I love data. Cameron, I presumably Magellan works in a very similar fashion. I just picture a world where there are some people who hear that and they're like, that's terrifying.

That is way too much information to give these guys. And then also a world where somebody is saying like, Oh, how the hell are they making any kind of decisions based on just that? Is that accurate? Do you ever have those conversations? Like, is this the happy medium that we all just have to accept? What, what are the other solutions that people are using in other industries?

Why can't we do it? And like, is this good enough?

Cameron Hendrix: Prior to pixel based attribution being an option for folks, you know, the people were a lot more reliant on vanity URLs, promo codes. Those continue to be tools in an advertiser's toolbox. I mean, I guess post purchase survey as well. I think the data that we can bring to the table with pixel based attribution just helps, you know, helps contextualize that a lot more.

Like the problem is like setting up a business in general is hard. And so we've seen, you know, many examples of, you know, sometimes advertisers can be, it's, it's hard to set it up right. Right? So like, you'll have an exit intent pop up that, you know, shows up with a promo code, even after, you know, someone has arrived at a vanity URL, like, you know, that's a small code change, but it has big impact in terms of metrics that you actually measure.

So when we look at like pixel based attribution, it tries to, you kind of get a little bit more of a normalized sense because you're able to, you know, do that linkage, but I think taking a step back and thinking about other industries, like I like to think about, like TV as an example, you know, like again, for our high school friend, we've got, you know, you're sitting on your sofa, you turn on TV, you know, probably you're, you're a cord cutter, maybe.

The conversion happens on a device. Like you, you hear an ad on the YouTube TV and you go to a device and, and that's sitting in your hand or at the same time you're watching and you go to the website, right? Like that's a effectively a response or a conversion event. So like industries like TV are having to solve challenges the same way that we are, you know, in podcasting.

I think the other interesting thing there, you know, a while back, and I guess to some extent still, there's like, uh, cookiepocalypse was like a very popular phrase to see in media. And I think the fun thing is, like, as, as much as cookies haven't entirely gone away and it seems like we went to the brink and then kind of came back a little bit, podcasting has never really had the full advantage of cookies, the same way that like, you know, Facebook and Google, they've been able to like do a lot of more direct linkage between someone clicking an ad and then like immediately having that browser navigate to that spot. Podcasting has always had the challenge of like the conversion happens on a device typically that's different than the device where the exposure happened in some cases.

So I think the good news is the overall kind of media measurement industry as a whole outside of podcasting is having to look at solutions that podcasting has had to get comfortable with for a while, and that actually will help overall, like drive growth in the market because marketers will come at it.

And instead of being like, what is this thing? They'd be like, Oh, I had to think about this when we bought TV. And I had to think about this when we bought this other channel. And it's going to be a little bit easier for them to digest.

Jeff Umbro: So I think now everybody who's listening, our high school buddy, like he understands kind of like what we're all talking about.

So now let's like bring in some real world examples. And Pete, I want to start with iOS 17 because this is something that you had a lot to do with. I know Cameron, you also had a lot to do with. Pete, would you please explain briefly like what happened in September of last year and leading up to September of last year and then like what the impact of that actually was?

Pete Birsinger: The net effect is that there was a change within Apple Podcasts that made its listeners less often mass download the back catalog of shows. It had to do with what your settings were, with if you had auto download enabled, and then you, you know, turned it back on, like, after you had enabled it, disabled it, it was kind of like, would you download then all the episodes in between?

So in effect, though, for at least the past two, three years, maybe longer, I'm not exactly sure when this behavior started in Apple Podcasts, but it had been going on for a while. And so the effect was that people would see, and we'd see this too, that Apple podcasts had typically a higher frequency, maybe like the same amount of listeners as Spotify or other platforms, but just a noticeably higher frequency.

Jeff Umbro: So you're defining listeners as like unique IP addresses, and frequency is like the number of downloads from each of these IP addresses. Is that, is that mostly accurate?

Pete Birsinger: Yeah, exactly. That's exactly. So then on certain campaigns, and usually these were run of show campaigns where the ad, you're not, the advertiser wouldn't just be buying the most recent episode they would say I'm buying they would buy a hundred thousand impressions across the full back catalog of a show of a show's episodes. So what we would see happen is you know maybe 20, maybe 30, maybe slight maybe a bit higher percent of impressions in that run of show buy would be going to say like a really small percent of listeners, like two, three percent.

It was sort of weird because it was like, Why is the advertiser sending you know a sizable portion of their campaign to dislike, you know, seven people? You know, maybe it's a few more but a very small number of people, and what what it turned out to be was that there was this sort of weird Apple scenario where if you toggle on and off your auto download settings in some cases, you would just download a ton of a show's back catalog episodes.

And then if the advertiser was doing a run of show buy, well, then that person would get 200 ads if, you know, depending on the show's back catalog size.

Jeff Umbro: Presumably they're not listening to the ad and like acting on what they're hearing and.

Pete Birsinger: They could, they could listen, but odds were probably low that they weren't, the odds were a lot lower they were listening than to say just the most recent episode that they downloaded.

Jeff Umbro: Pete's trying to be very political here and like safe.

But you, you, you can assume that most people are not listening to those ads and buyers were spending money on the ads that people were not listening to in many instances.

Pete Birsinger: Well, and to your point, actually what really made me think something was up because some people were like, Oh, it's noisy IPs or it's people on an airplane or, you know, something they're like, don't worry about it.

But what kind of really made me look closer and have more confidence to, to say more things was that we compared the performance of those impressions say that those 30 percent of impressions going to 2 percent of listeners. We compared the performance. How many, how many conversions are coming from them compared to the rest and we saw those impressions dramatically underperformed other impressions.

So, I was like, all right, well, even if we, hypothetically, it was all these people on an airplane or whatever, you would think they would still be converting, you know, a bit. So, the performance, yeah, to your point, was actually really what made us more confident that something, what was up there. The advertisers, you know, they, they weren't the best impressions for them to be buying on.

So then when Apple made the update to make people less likely.

Jeff Umbro: They did this because you and a coalition of people like brought this to their attention. Correct?

Pete Birsinger: Right. Right. I'd say Bryan Barletta was certainly perhaps the most vocal, far more vocal than me, and Brittany at BetterHelp was involved, and a number of publishers or, you know, involving Sharon at Omni was, you know, talking to Apple. So yeah, I think there was a lot of, there were a lot of people.

I think the only thing I'd really say we, I know we played a sizable role in was sort of surfacing the data to, to, to buyers to say like, are you aware this is happening? I think we could make your impressions more efficient if there's, there was some way to fix this. So then, yeah, I think to, so then Apple was like, okay, maybe, maybe this isn't the ideal change and maybe they did it for their users' bandwidth.

Maybe they were trying to say maybe, you know, this person doesn't want a hundred, you know, episodes of this show on their phone, all of a sudden it's a mass download.

Jeff Umbro: I've heard it explained as like, at one point that was a feature back before everybody had like wifi everywhere that they went, but it was just a dated feature that like could potentially be viewed as a bug today.

So what was the result of all of that?

Pete Birsinger: The result was a great thing for advertisers, not so great for a number of publishers short term. I think long term it will come around for the publisher. So now typically for run of show buys, when an advertiser is buying across all the episodes of a show, we, we don't see the concentration nearly as much.

The impressions are spread out much better than they were before. And interestingly, a lot of buyers, especially our direct response ones would always say, Baked in is way better, DAI, you know, is terrible, doesn't work, blah, blah, blah, which when we looked at the date, it was, it was, it did seem that way to us too, but with this update, I think actually it's come a lot closer and in some cases has even flipped, which is good news because I do think there is no inherent reason DAI should be worse than, dynamically inserting an ad, there's no inherent reason it should be worse than baking an ad in, so I think there was this perception rooted in true performance that was holding the industry back from embracing this technology that actually can really help publishers monetize better. So now I think things, adverts, people are, people's perceptions I think are kind of catching up to that.

So, great for advertisers in terms of performance and publishers.

Jeff Umbro: There's a huge conversation around like baked in versus like dynamically inserted ads versus faked in ads. And, and we're not going to talk about it on this episode because it would take us all day. The crux of what Pete is saying is that, historically, buyers have not wanted to run dynamically inserted ads as much as they would have liked to have done like a faked in or a baked in because it didn't perform as well. And with this update, like they are performing a lot better because presumably there's less like junk downloads that are going into them.

This change in some cases I've seen had a like very significant, yeah, like impact on many publishers. I've seen anywhere from like 20 to 50 percent of downloads getting cut off from these things depending on the show because it's adversely impacted older shows or shows that publish more frequently, and that means that publishers are going to make less money and like maybe have to make decisions based on like that new reality.

And then the second side of that is that long term buyers are going to spend more money because they're more confident that their ads are going to actually work, which is excellent. Cameron, I know we just took up a lot of time, but is there anything that you want to like add to that? And I'm also curious about If you were involved at any point in like, you know, that whole conversation.

Cameron Hendrix: In terms of like buyer confidence, I think, I think we still, you know, the, the reality is like, to some extent it's like confidence coming from the fact that like we caught, you know, one issue with downloads, right?

Uh, but you know, because we caught the one, it's like you, like, you know, you look at data and you're like, I caught the one thing. So I feel pretty good about this. The challenge is that advertisers and, and you know, and people who come to the cha, come to the channel who are like fresh to the channel, like are still looking at like, they, they don't really. There's the perception that's like, listen is what matters. The fact that someone is like actually hears an ad, right.

And like, that's been one of the challenges in the space is that like, there's, there've been efforts to like, kind of support or adopt effectively like kind of play markers that like cause someone to know if an ad was really delivered to some extent, some of the streaming, you know, DAI, Dynamic Ad Insertion technology, like address some of this, but like the, the, I think all that's to say is, I think there are.

Probably still some, you know, confidence, you know, boosters that like we will ultimately go through. I think the, the taking a step back, right? The thing that changed was like the, the kind of dollar amount that advertisers were spending, you know, on, on those podcast ads, because some of those impressions were, you know, effectively like caused by this, you know, feature or bug in Apple podcasts.

The, the thing that did, you know, what did not change was like the actual like outcomes, right? Which is part of what pixel based attribution helps you, you know, measure in the first place is like the actual like purchases and leads and other metrics that you might care about as an advertiser.

Jeff Umbro: The measurements shifted, but the actual like number of, of folks who in reality were listening did not change at all.

Cameron Hendrix: Right. So the ROAS changed, right? The percent, you know, return on advertising spend, which is honestly great for advertisers, right? Like it's, you know, more, more bang for their buck, right? But, um, but yeah, like the, the whole, and then part of the power that I think, you know, we, we and, and Podscribe bring to the table, Magellan and Podscribe bring to the table is the fact that you can measure conversions and, you know, feel confident that you can link up exposure, you know, on podcast ads to conversions and look at the absolute level of dollars that you're getting back from podcasting as a channel and decide whether that makes sense for you to continue investing in, you know, based on Lyft and based on these other metrics that, you know, we deliver, you know, to advertisers.

So, and going back to like, you know, I think we, we were back involved as part of the IAB Tech Lab and as part of like working with Sounds Profitable and, and Bryan Barletta, big shout out for basically pushing this through. I think ultimately the, you know, interesting, like I said, the industry itself, like came together to solve this problem.

And I think it is, it does increase, you know, confidence overall, but I think we still have a ways to go to make sure that people understand that, like, what they should be caring about is outcomes, as much as they care about, like, obviously the, the metric that trades.

Jeff Umbro: The big reason I wanted to have you guys here is to talk about everything that we already covered, but like the, the crux of it was really just the idea that Chartable is sunsetting.

When this episode comes out, that will be like right around the corner. So even when people are listening, that may have already happened. First of all, why Spotify purchased Chartable in 2022, they took a lot of the great features that they loved, and so like, in your opinion, why did they purchase the platform, and in your opinion, why are they now shutting it down?

And then we'll talk about what comes next.

Pete Birsinger: I think they, they made a real power play two, three years ago, however long it was, to buy both of the two more or less leading attribution companies. I think they, you know, figured to some degree, all right, we're just going to bring in house all the main attribution and all of the, you know, key advertisers are going to mostly have to run through us.

So we're going to get tremendous amount of data in the space and, you know, on all these other shows and publishers that aren't even ours. And it'll be a great legion for new advertisers. And I think perhaps another thing they thought was, you know, they, they kind of really needed a in house analytics solution for, for their internal strategic plan.

So maybe that could have been even the biggest reason of them all, perhaps. And perhaps it was because I think what a lot of buyers have noticed with SpAA and Chartable is just the rapid dilapidation of the products in the support teams. I think there's like one per, you know, there's not a lot of people over there still doing much with them.

And I think buyers have really noticed that. I think free is, is great. Like, sort of like Cameron was saying earlier, I think it's great having SpAA out there because it brings buyers, it gets buyers a little bit comfortable with the space in a free setting and, you know, maybe there are some bugs and no support, but like, you know, still, it gets people in the space and using it.

Were you going to say something, Jeff?

Jeff Umbro: I was just going to say SpAA is Spotify Ad Analytics, formerly Podsight, so changed the name.

Pete Birsinger: Right. I think they did perhaps see a bit more of a recoil from buyers and publishers over the solution's not being independent in that Spotify was in a way grading their own homework if you're buying on Spotify and then they're also telling you how well it performed, I think there was a bit of recall there and also from other publishers who didn't perhaps love the idea of sending Spotify their data on their shows, which how they performed, how many downloads. I don't think there was a lot of that was widely loved by other publishers. So there's definitely a I think a bit of a, that I think that may maybe surprised them.

I don't know. Maybe they were fully expecting that, but it seems like where they're really powering away is taking the internal tech and repurposing it in some shape or form for their own strategic ambitions, perhaps to be a bit, a bit like a YouTube with its own, you know, measurement and things. So, but yeah, I think it, Chartable had a good run.

Jeff Umbro: They did. And you guys at Podscribe are also going to, or have, launched your own solution for like, podcast to podcast attribution and podcast to web attribution and your version of SmartLinks. Did those exist before Chartable's sunset?

Pete Birsinger: They've been around for about a year and a half, I would say, both of them.

So they have been around, I would say, our main focus has been advertiser attribution for this time, but they have been there, and now with this surge of, you know, demand from the Chartable sunsetting, we have now slotted, like, a number of upgrades and additions to them to make them more reliable, more robust, add more analytics to them.

So they've been around for some time.

Jeff Umbro: You two are going to have a really great Q4.

Pete Birsinger: Yeah, no, but so we, they've been around, but we have a number of things planned that some of we've already released a number of updates to them to put a fresh face on, you know, be prepared for anybody who wants to give them a shot.

Jeff Umbro: And what's the plans for the future of the platform?

Pete Birsinger: Well, I think there's still a lot of room for improvement and measurement. With just podcasting and streaming audio, you talk to so many brands and I mean, a lot of our clients, maybe they've figured it out more than other people, but I think there's still a lot better we could do with it to grow confidence in the industry and measurement, a lot more ways we could slice it.

Incrementality has become a really hot, hot thing recently, very convincing to people. So we have, we have a solution for that and continuing to improve that. And then I think spreading out a bit to adjacent channels, say, CTV, we're starting to do a little bit of it now, but I think what can really help podcast buyers convince their boss or company that, Hey, this isn't working is that they see also the overlap between the two and how podcasting is fitting in with other channels.

And if the more podcasting measurement can be put apples to apples with other channels, and it can be, it can be proven how effective it is. So we want to have more integrations with other channels to show podcasting on the same footing, because I think that that is really needed as well. So better improvement for audio and more integration with other channels to make it easier for people to compare it apples to apples.

Jeff Umbro: Would you ever launch a marketplace?

Pete Birsinger: No desire, no, no desire. An ad server that sits atop all the publishers, because there's no way right now, except major buy through the trade desk where the inventory may be limited to say frequency cap across all publishers, for example. Or to say, maybe you have listeners reached on one show and you want to not target them again on another.

There's not really a way to do that. So I think maybe down the line we're, we'll look, you know, what kind of solution we could assist with or be part of there. Because I think an ad server that sits atop another layer could unlock a lot for buyers, but I'd say that's a bit in a dream state still.

Jeff Umbro: Correct me if I'm wrong, but that would be kind of like AdsWizz before Sirius bought them.

Pete Birsinger: Right, I'd say in a way, but I'd say, imagine if a buyer could, it could have what's sort of similar to their Facebook dashboard where they could control all their buys through it and pause, switch creatives, frequency cap, say I want to do more here with it, it could give buyers like an unprecedented, unprecedented level of control.

Cause right now they're sort of at the mercy of the publisher ad servers to do this or that.

Jeff Umbro: Spotify tried to do that and it didn't work very well. I think that they're actively doing that actually. Like, you know, anybody can go and buy audio spots on Spotify.

Cameron Hendrix: Well, Spotify, clearly super important part of the ecosystem, big ambitions to, you know, make audio, you know, a, a, a channel, you know, that advertisers like come to and, and, you know, specifically through Spotify. So I think, you know, it was, uh, I, I don't have a crystal ball into, you know, the, the folks at Spotify were thinking back in, was it 2022, all the, the kind of pieces to this fell into place, or maybe it was late 2021 for Chartable and Podsights to become part of, of Spotify.

I think, you know, what's been interesting though, is as much as there's been some pushback around, you know, the measurement of ads, you know, using, you know, Spotify analytics among certain publishers. Like a lot of these publishers are still, we're still like relying on Chartable. So, you know, the number of folks who've come out of the woodwork who had, you know, you otherwise would kind of expect are, had maybe moved on in the past have had, had still really been like kind of plugged into that feature set, which I think speaks to what an incredible job Chartable did, like getting out there in the market, you know, with their offering and also what an incredible job they did by kind of building, and hats off to, you know, Dave and team at Chartable from the time, like building feature sets that were, you know, even, even after, you know, maybe not a ton of like upgrades and like recent, you know, months and years, and obviously heading into this deprecation effectively, still tools that people love and appreciate.

So probably the reality is like business needs change over time. And, you know, Spotify has clearly like, you know, rolled out Spotify Ad Analytics as a solution to replace a lot of the kind of pieces of, you know, Podsights and, and, and Chartable that, that they had, you know, seemed to have kind of re repackaged and, and redeveloped into that's that new product offering.

So I think it's probably something that was like, the writing was on the wall from the beginning. It's hard to say.

Jeff Umbro: We are in a really funny situation because to your point, like we have all been very reliant on this one tool. There are other platforms that exist, including Magellan and Podscribe that do many of the same things, but I've not found anything that does all of the same things.

And most of the publishers who are using Chartable, we're using it for some version of, of these like six features that they have.

Cameron Hendrix: I would also say all of the same things at the same price point. So I think there's a, you know, and, and, um, you know, there's, there's something to be said for that, right? And the fact that like the product offering that existed most recently was maybe not something that like was sustainable for the ecosystem overall.

Jeff Umbro: That's a great point. And I honestly haven't thought about it in that way. What Cameron is referring to is that Chartable was offered for free to anyone who used Megaphone, and for a pretty realistic price point for anybody who didn't, whereas most of the other services that are out there are, are somewhat based around bandwidth costs.

So like the bigger publisher you are, the more money you are going to spend. And as we just discussed for an hour, like it is pretty essential to be tracking all of the data when it comes to like your podcast to web or podcast to podcast attribution so that you can see like which marketing campaigns are working, whether you're a brand or a publisher.

There's a lot of people who are all of a sudden going to be paying a lot more money in 2025 than they were in 2024 for the exact same service that they also still have to learn and like reintroduce into their ecosystem. What are you guys doing differently when it comes to pod to pod attribution or, or like another Chartable feature?

Cameron Hendrix: The advantage is that like we have built the platform having a lot of knowledge from what other customers who've like used tools like Chartable have had pain points around. So we've been able to develop metrics like we took, so we take converted listeners, right? So basically the number of listeners that you're driving from a promo.

We break that into one time listeners and repeat listeners. So a one time listener is anyone who's accessing that, even if you access it over like a Tuesday, you started an episode on Tuesday and you finish it on Thursday, you know, we're calling it, that's a, that's a one time listener. A repeat listener is someone who's come back to multiple episodes, like at least two episodes of a podcast after being exposed to a promo, which is obviously a little bit more like subscription, like, you know, behavior change among like a listener. You're ultimately getting hopefully a longer term listener. And we're able to like measure that metric.

And I think that's something that like Chartable had like not done and we were able to kind of take a step further. And then similarly, like our replacement for SmartLinks, we call ListenLinks. So ListenLinks sit for us alongside podcast promos in a way that like was a little bit different so Chartable had kind of like a module for SmartLinks, a module for SmartPromos.

For us, we're kind of seeing it as like ultimately part of the same, you know, data deliverable, right? So you can take the same metrics like downloads and converted listeners, one time listeners, repeat listeners, you get those metrics from ListenLinks as much as you get them from the podcast promos. We put that data side by side.

Jeff Umbro: What is the future for Magellan?

Cameron Hendrix: The fun thing about podcast advertising and podcasting is that like there's no shortage of ideas. And I think one of the, one of the weird things maybe, I don't know, maybe it's normal, but one of the weird things about like this business in particular has been, there has been no shortage of things that I want to build.

I think if anything, like the list is longer than ever and we've built more than ever. So, it's, I think there's a lot of opportunity to continue to develop tools and you try to solve like industry problems when it comes to, you know, advertisers trying to spend dollars efficiently, publishers trying to measure the effectiveness of those dollars.

And a lot of that has to do with changes like in the ecosystem that are just happening, you know, outside of us, which is great, which is things like, you know, the rise of programmatic, like we rolled out a feature to identify programmatic ad campaigns. So programmatic ads have been around for a while as a smaller portion of the market.

If you look at like things like the ID revenue studies, but you know, programmatic, we're, we're kind of rolling out some technology that for the first time allows you to see, you know, what shows are part of, you know, SpAA, and, you know, what campaigns have run across those different kinds of solutions in the marketplace and on run of network buys and things like that.

So those kinds of changes in the industry have kind of caused us to like, you know, prioritize improvements, you know, around that. And then similarly on the measurement side, you know, we're really excited about tools like Reach Lift, which we launched with Wondery and the, the expansion of, you know, the adoption of understanding like reach and unique reach that each network brings to the table in the industry.

I think kind of taking a step back, right? Like the longer term where podcasting is going to be, is, is going to fit in among more channels that are today bigger like CTV and, and TV buying and, and, you know, even broadcast buying. And so we are, I think ultimately going to be looking at like ways to bring our tools to more channels to help advertisers who are in podcasting, who work with us today, scale and other channels as well. And I think it's like, you know, not, not a surprise. Shouldn't be a surprise really for anyone to hear that, right?

It's like, you know, like media tech companies tend to grow, right, by adding feature sets that serve their industry and also by adding, you know, support for scaling and other channels. And I think we'll, we'll kind of follow a similar path to what the giants who have come before us have done in terms of, of scaling, you know, our solution for podcasting and, and channels beyond that.

Jeff Umbro: This is very cool. I'm really glad that both of you were able to join the show today and thank you so much for the time.

Cameron Hendrix: Yeah, it's super fun. Thank you for having me and always great to chat.

Pete Birsinger: Really great to be on here. Appreciate you having me. Cameron, a pleasure as always. Good seeing you.

Cameron Hendrix: Always.

Jeff Umbro: Thank you all for joining us on the show this week. For more podcast related news, info, and takes, you can follow me on Twitter @JeffUmbro. Podcast Perspectives is a production of The Podglomerate.

If you're looking for help producing, marketing, or monetizing your podcast, you can find us at Podglomerate.com. Shoot us an email at listen@thepodglomerate.com or follow us on all social platforms @podglomerate or @podglomeratepods. This episode was produced by Chris Boniello, and myself, Jeff Umbro.

This episode was edited and mixed by Jose Roman. And thank you to our marketing team, Joni Deutsch, Madison Richards, Morgan Swift, and Annabella Pena. And a special thank you to Dan Christo and Tiffany Dean. Thank you for listening and I'll catch you all in two weeks.