Audio Alerts are a feature of Audiosear.ch that delivers email alerts to your inbox whenever a specific word or phrase is mentioned in a podcast. Maybe you’re doing research for a paper or a passion project. Maybe you’re using them as a Google alert for mentions of your own name (nothing wrong with that!). Here are six ways people are putting this tool to work for them.
Audiosear.ch will be winding down operations on November 28, 2017. As of that date, you will no longer have access to our API endpoints, the website, or features such as Audio Alerts, the Clipmaker, Buzz Score, and more.
We welcome you to contact us at firstname.lastname@example.org with any questions. We will do our best to reply in a timely manner based on the volume of emails.
We’ve loved watching the projects you’ve built with this technology over the past two and a half years, and we appreciate your understanding.
The Audiosear.ch team
Lex Conant is a long-haul truck driver and a voracious podcast consumer. This is how Lex listens.
You’re a long-haul truck driver. What is your route?
My homebase is central Indiana, and my route takes me anywhere from 600 to 700 miles from there. I feel like I’m almost always in Pennsylvania, but I also make it to Virginia, South Carolina, and other places. It all depends on where people need stuff.
Here at Audiosear.ch, we’re always thinking about new and innovative ways to surface the most relevant and interesting podcasts our users might be looking for. With our ever-expanding database of hundreds of thousands of episodes, that becomes a more and more difficult task by the day. We ingest thousands of shows of varying quality and popularity, but there are few metrics for quantifying that. We wanted to figure out how we could use publicly available data and social media to come up with a comprehensive, sophisticated, and intuitive way to quantify the “buzziness” of a given show or episode, thereby allowing us to generate better recommendations. What we came up with we call: the Buzz Score.
To understand why evaluating “buzziness” is such a difficult task, it’s helpful to understand a little of the history of podcasts up to now. In 2005, Apple launched podcasts as a new way to listen to radio-style programs by downloading them to your iPod (thus the name) and playing them later. This was before the iPhone and other smartphones were introduced, and cell networks wouldn’t be able to support streaming media for another several years, so the process was a bit clunky and podcasts didn’t quite explode onto the scene. Apple broke out Podcasts into a separate iOS app in 2012, thereby setting them apart to users as a distinct form of media.
Since then, Apple has made occasional but marginal improvements. Although many competitors have tried to overtake them, and Android users can only use rival apps to listen, Apple still dominates the market with over 55% of users listening on the Podcasts app. Apple Podcasts is great for finding a show if you already know what you’re looking for, but it’s not great for serendipitous discovery or surfacing less well-known shows that nonetheless deserve exposure. Developers who have built alternative podcatchers by and large haven’t been able to do much better with discovery, since Apple provides only a minimal public API for searching podcasts and user reviews and ratings have been the only metric for determining quality.
Despite the lack a significant push from Apple or other major distributors, though, podcasts have become more and more popular over the years, with 67 million Americans now listening to at least one podcast on a monthly basis. Given that Apple is still the main way people access podcasts, we decided to use the data they make publicly available as a basis for evaluating audience engagement — and by extension some sense of the quality of the show.
The most obvious metric seemed to be the star rating, which comes from user reviews submitted through iTunes, on a scale of 1 to 5. However, as we started comparing ratings, we realized that the vast majority were between 4 and 5, and especially above 4.5. This suggests that listeners don’t generally bother leaving reviews if they don’t like a show, and they are most likely trying to help the shows they love by giving them a high rating, especially if the host has asked listeners to do so. We decided to run this number through a mathematical function which expands the difference at the upper end of the rating scale. This allows us to make more meaningful distinctions between ratings that would otherwise appear very similar, such as 4.6 and 4.9, and weight them accordingly.
Number of ratings
We also wanted to factor in the number of ratings, which gives a sense of the audience size and enthusiasm, and, to some extent, how long the show has been popular. Since there are many shows with only a few ratings and a few with tens of thousands, we decided to boost shows that have at least a few reviews in order to not let them get completely overshadowed by the most popular ones.
We have also been keeping track of the positions of shows on the iTunes charts, and we wanted to incorporate that somehow as well. Since it is quite an accomplishment to make it onto the charts, we decided to count a show’s appearance as more significant than its highest position achieved.
Cultural commentary (in this case, on Twitter)
All of this is great for getting a sense of the overall quality of a show, but what about individual episodes? The iTunes API doesn’t provide any episode-level data, and there isn’t another obvious source for such metrics. We turned to social media to gather this information, scraping Twitter for episode recommendations and associating them to entries in our database. This allows us to bump up the Buzz Score for any given episode that’s getting a lot of attention. The more people are talking about it, the higher the score goes. This levels the playing field a bit for new or relatively unknown podcasts which manage to get noticed and become part of the social media conversation.
Of course, not every episode that gets a conversation going will be relevant to the average user. There are countless niche communities on Twitter and many podcasts that cater to niche audiences. However, we use many different data points to serve search results and recommendations, and the Buzz score is just one way to help users find a podcast they may have heard about or that they’re more likely to enjoy.
As the podcast industry has grown in audience size and value, producers and publishers have been eager to see better and more detailed metrics in order to better understand their listeners and give them more engaging content. Apple recently announced that they are doing just that, releasing a new producer portal with fine-grain analytics and user behavior data. With this new push by Apple and with other providers such as Spotify entering the field, we hope that the breadth and depth of publicly available data will expand so that we can continue to develop our Buzz Score algorithm.
Want to know your episode or show’s Buzz Score? You can check it out here.
Kerning Cultures is a podcast whose mission is to dissect the more complex narratives of the Middle East through stories. I spoke with one of the show’s co-founders, Hebah Fisher, about podcasting in the Middle East — how listening behaviors vary, the different types of stories that get told, and the role of the Western perspective. This interview has been edited and condensed.
Why did you and your co-founder, Razan Alzayani, decide to focus your show on narratives of the Middle East?
Audio storytelling pulls on the long tradition of oral history that we have in the Middle East. Many years ago, storytellers (called hakawaty) would gather people in a circle in the streets and tell long narrative, often historical stories of heroes and legends to entertain and educate them. That tradition hasn’t been completely lost, per se, but it’s no longer common. We wanted to modernize it and bring it to the current day to explore topics like society, culture, history, entrepreneurship, and current affairs through personal stories.
It started with a post in the New York Times Podcast Club Facebook group from a librarian looking for podcast recommendations to share with her students.
As the suggestions from other group members started rolling in, I began thinking about the relationship between libraries and podcasts more generally. Public libraries are these amazing social resources, providing everything from internet access, to books, movies, music, and community programming — all for free. Were they doing anything to formally incorporate podcasts into this media lineup? You can’t stock podcasts on shelves, but were there example of libraries that made podcast recommendations through newsletters, did shared listening events, or otherwise actively embraced this form of storytelling?
Podcasters take on so many roles to get our shows made: writer, researcher, editor, interviewer, host, social media manager, web developer, designer, marketer. But one job that I don’t often see discussed is community management.
Community managers turn people with something in common into real communities and keep those communities healthy. They are what make tight-knit subreddits on Reddit different from diffuse hashtags on Twitter, creating the conditions for participants to organize, interact, contribute, and feel invested in their community. I don’t think any podcast active today has a dedicated community manager, and I suspect a lot of producers don’t even think about hiring one—but every single one of us could use one. Community, specificity, and strength of engagement are what make podcasts so special. We must devote time to our shows’ communities to help them grow.
Jenny Luna works at Mother Jones on the show Bite, “a podcast for people who think hard about their food.” She does everything from pitching ideas, to booking guests, to promoting the episodes on social media and in their weekly Food for Thought newsletter, which goes out to all of their food fans and subscribers. The audience is wide — some folks may not listen to Bite, but will follow their food coverage. As part of that newsletter, Jenny includes a blurb about other episodes and shows related to food that the Bite team is listening to. But it’s not always easy to come up with new recommendations to share, and she found that rather than sharing new shows, she sometimes had to repeat the same ones in multiple newsletters.
Steve Henn is a co-founder of 60dB, an app that feeds you the best short audio stories about the topics you care about. Before creating 60dB in early 2016, Henn was a reporter at WAMU, Marketplace, and Planet Money. We talked to Steve about his goal of creating a new, better form of radio and how his relationship with audio has changed with his shift from the public to the private sector.
Tell me about your day to day role at 60dB.
My role here is to jumpstart the short-form content ecosystem. We’re doing that in a bunch of different ways — one, by working with institutions like The New York Times, Vox, and others that have incredible newsrooms, and produce content that is really well-suited to a platform like ours, and two, by investing in and working with the great journalists we’ve hired to produce our own content and adapt stories from existing print and digital outlets and to audio. I’m part product evangelist, part editor.
We’re 90 minutes into a two-hour recording session and I’m guessing I only have about 30 seconds of usable material.
I’m glancing back and forth from the clients to my phone, pretending to read along with the script, but I’m really just checking the clock. I’m not sure if it’s the grey weather, my choice of cookies over pretzels for snacks, or the way I’m folding my arms, but I can’t seem to find the right strategy to get the tape I need from them. I’ve re-written the script, used up all of my best dad jokes, and even held an impromptu jumping jacks session, but it’s all been for naught.
I need two minutes of solid, natural conversation between two clients about the history of an upcoming holiday, and we have 30 minutes to nail it before our allotted studio time is up. Simple, right?