As recently as a few years ago, most brands didn’t know if it was possible to track attribution from advertisements running on podcast audio campaigns. Over the next few years, more and more players entered the space to try and correct this misconception.
Today, it’s possible to run an ad on a podcast and see how many of the people who heard it went to buy something on your website. It’s possible to retarget an ad on LinkedIn about a course offering to someone who’s already heard about it on a podcast ad. If the CMO of your company is interviewed on a podcast, it’s possible to see how many heard this interview on Spotify or Apple Podcasts and then went to check out the company website.
So, What Is the Future of Ad Attribution in Podcasting?
In short, it’s now possible to use attribution services to track when and where ads are running and how effective those ads are, which in turn allows for a lot of insights to be applied to the day-to-day work of publishers, marketers, and advertisers.
All of this is made possible by a few companies in the podcast space who are enabling these tools. On a new episode of the Signal Award-winning series Podcast Perspectives, we’ve brought on the founders and CEOs of two of these companies – Pete Birsinger of Podscribe, and Cameron Hendrix of Magellan AI – to discuss these realities.
In this episode, we cover how this technology actually works and why a brand would want to utilize them, which tools podcasters can use in the wake of Chartable’s sunsetting, and some real-world examples of how these types of tools changed the entire podcast ecosystem.
Make sure to tune in to hear everything our guests have on their minds. If you enjoy this article, please subscribe to the show and our newsletter, and follow us on LinkedIn.
And if you want to learn more about podcast advertising attribution, be sure to check out our other article featuring our recommended attribution tools and techniques here.
Disclosure: This article may contain affiliate links. If you purchase something through these links, The Podglomerate may earn an affiliate commission, and you will receive an offer. The Podglomerate only advertises products and services we trust.
What is Advertising Attribution?
Advertising attribution in podcasting is the technique of identifying and adding value to user behaviors, such as clicks or conversions. Attribution is important because it helps advertisers figure out if their campaigns are a successful investment. For example, if a listener of our show Podcast Perspectives hears an ad for a brand during an ad break, we can track that anonymized listener behavior and see if they took any actions as a result of that ad, such as visiting the brand website or even purchasing their product. Alternatively, if we run an ad for another podcast on Podcast Perspectives, we can see how many people went to listen to that show.
Attribution is notoriously tricky, which is why it’s important to understand that this is not an exact science. However, the tools we have to track attribution are getting better.
If you’re interested in learning more about how attribution technology works, both for marketing and monetization, feel free to connect with our team at The Podglomerate here.
Top 5 Insights on Podcast Advertising Attribution
Look, we get it. The episode had too many tips to keep track of. Pun intended. That’s why we’ve picked out five “secrets” of advertising attribution in podcasting highlighted during our conversation.
1. Pixel-Based Attribution Improves Accuracy
Pixel-based attribution really matters to your campaign efficiency. Here’s why: In the episode, Cameron Hendrix emphasizes how pixel-based attribution offers greater precision in advertising attribution. And precision is always an asset in attribution.
“The data we can bring to the table with pixel-based attribution… helps contextualize [performance] a lot more.”
So what is pixel-based attribution? It’s a method that reduces reliance on tools like promo codes or vanity URLs, making campaign tracking more reliable and actionable. On the podcast side, you set up an RSS feed prefix or a DAI pixel to create a baseline of everyone who has heard the podcast episode or ad unit, and then compare that to the folks who have triggered a website landing page pixel. Where there’s overlap, you can assume a listener of the podcast took action on an ad. Platforms like Magellan and Podscribe handle all of the heavy lifting, and you as the end user can track user behavior, including conversions, clicks, and views.
2. Podcast Attribution is Evolving but Imperfect
Podcast attribution has transformed over the last few years, and is still changing. With this in mind, I resonated with Pete Birsinger’s explanation of the limitations of podcast attribution.
“All we can really see is the IP address… [We] match it to a conversion event, like visiting betterhelp.com.”
Ultimately, the data isn’t always available. But we can still construct a useful map of user journeys. Cameron Hendrix also added:
“Podcasting has always had the challenge of the conversion happening on a different device than the exposure.”
What he means is that some people may listen to a podcast on an app, but search for the product on a desktop. This would show up as a “Direct Search,” rather than being attributed to the podcast ad.
That said, this is not a new problem for advertisers. Despite its limitations, podcast attribution mirrors challenges in other media like television and radio.
3. Transcription and Air Checks Build Trust
For brands spending millions on advertising, it can be a full-time job tracking the fruits of their labors. Pete Birsinger described Podscribe’s ad verification process:
“We transcribe every episode, label ads, and snapshot episodes multiple times to track ad placements.”
Sounds tiring, but this effort matters. Publishers and advertisers can ensure ad placements are accurate and visible to their target audiences, thereby improving transparency and trust.
4. Ad Load Impacts Campaign Performance
Are there any downsides to having too many ads on your podcast? Pete Birsinger thinks there might be. In the episode, he reveals findings from Podscribe’s expert research on the impact of ad loads in podcasting:
“As ad load goes up… performance goes down. There was a definite relationship.”
Podcasters should be cautious about increasing the number of ads per episode, as it can reduce listener engagement and ad effectiveness.
It goes without saying that listeners may not enjoy listening to too many ads. As a publisher, it’s your job to find a balance.
5. The Surprising Result of the iOS 17 Update (DAI Campaigns are Actually Becoming More Popular)
In September 2023, Apple released the iOS 17 update, which provided “improvements to the way Automatic Downloads are handled” on Apple Podcasts. Prior to iOS 17, when an Apple Podcasts listener would unpause automatic downloads, the system would automatically download all unplayed episodes. After iOS 17 took effect, Apple Podcasts ceased downloading previous episodes and resumed automatically downloading new episodes. As you can imagine, this iOS update significantly impacted podcast downloads, particularly for podcasts that had been around for years with countless episodes in their back catalog.
With that said, the iOS 17 update also had a surprising result: podcast ads have become more effective. As Pete Birsinger shares, Podscribe data shows that DAI ads are now driving a higher amount of visitors and conversions.
“Our [advertisers] would always say, ‘Baked-In is way better. DAI is terrible and doesn’t work.’ And when we looked at the data [prior to the iOS 17 update], it did seem that way to us too. But with this update, I think it’s come a lot closer, and in some cases has even flipped, which is good news. 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.”
Don’t forget to listen to the full episode of Podcast Perspectives. Have questions? Interested in learning more? Email us to hear more about our services.
