The Future of Podcasting Will Be Driven By Data
When you run a small, passion-driven podcast, it's hard to collect enough data to know exactly what your audience wants. But podcast apps and directories are different. They've a lot of data, and you can bet they’re using it.
Individually, podcasters don't get to see a lot of data about our listeners. We get some download data and the most basic of “consumption” charts, but that's about it. In fact, many podcasters are hostile to the idea of collecting more data from our listeners, citing new legislation like GDPR in Europe and the CCPA coming out of California. And with Cambridge Analytica not all that far behind in our review mirror, we’re all aware of the need for better privacy protection. However...
This morning, I was reading an article about new “virtual restaurants” that are booming thanks to data. Though calling them “restaurants” is a stretch, as these establishments have no place for people to dine-in or even take payments from customers like a take-out stand. These are more kitchens than restaurants, and they are booming thanks to DoorDash, Postmates, Uber Eats, and myriad other apps that encouraging those of us with busy lives to have our favorite meal from our favorite restaurant delivered to us, skipping all of that pesky human interaction.
These apps are data-mining gold. Because of their huge volume of orders, they use data to identify holes in the market. This allows them to turn to Captain Burger Maker (totally made up) and suggest the need for a new location. But the suits at Captain Burger Maker can’t justify a traditional restaurant at that location, as it’s expensive and complicated to open up a new location.
But… it’s a lot less expensive and complicated to open a kitchen that the public will never visit. Much lower payroll. Much less complicated build-out. And no lobbying City Hall for their permission to erect a gigantic sign. By working in partnership with one (or more) of those apps, Captain Burger Maker knows exactly the size of the opportunity, have almost no risk, and can be a cash-cow the moment they “open” on those apps. Not quite instant success, but pretty close.
On yesterday’s program, I talked about some smart book publishers and how they’re working closely with Amazon to sell huge numbers of ebooks. But there are other super-smart publishers who pay close attention to what kinds of books Amazon users are buying, then quickly create content to fill that emerging need.
For these data-driven publishers, it’s not about scratching that itch to write the great Amerian novel or finally finish that manuscript they’ve been working off-and-on for years. It’s about using Amazon’s data on immediate sales trends and reacting at-speed to create content that will turn a profit.
Amazon likes profit too. So yes, you can bet that they are sharing this data with choice publishers who can fulfill the unmet needs of the Amazon consumer. Because impulse retail opportunity, much like nature, abhors a vacuum.
The tie-in to podcasting is fairly obvious. Most of today’s podcasters are making their podcasts because they’re passionate about their chosen topic and wish to share it with the world. They apply some solid best practices, maybe do a bit of a marketing push, and release their podcast to the world in the hopes that it works. And by “works” I mean they hope it reaches enough of an audience so they can “afford” to keep doing the show. So long as their passion-based rewards exceed the costs in time and money, they’ll keep doing the show.
But companies who facilitate the transaction between podcast producers and podcast listeners don’t have to rely on passion. Or on hope. Because they have data. Bucket-loads of data that provides insight on what people listen to. What people don’t listen to. What other shows people who listened to this show listened to. What people search on and find. Or don’t find. How much of a show they listen to and how often they check to see if there are new episodes of that show.
Apple Podcasts, Spotify, Google Podcasts… they all have this data. So do companies like Podchaser and Overcast. These companies are, either in effect or in name, data aggregators. And while some do a better job of others at protecting and preserving the listener behavior data they utilize to power their own engines, each of them is sitting on data that identify holes in the marketplace.
And just like food-delivery apps and book-selling beast Amazon, some of them are looking for smart and agile content creators to fill those gaps.
Last week, we found out that one of the Gimlet’s shows, Science Vs, is now taking small little snippets of their 20-ish or so minute episodes and boiling them down to or extracting insights out of five-minute clips, which are in turn published as a brand new show designed to fit in the “daily commute” feature of Spotify, blending them with music clips, news, and other bits for a contained but varied listener experience.
Gimlet didn’t stop making the longer-form show. They reacted to data and insights from Spotify (Spotify owns Gimlet, so it didn’t take much selling) to create something new that fills a need. A need identified by big data collected by the listening/discovery app. A need that didn’t exist two months ago.
Are you willing to get cozy with the “gatekeepers” throughout podcasting? Because I can promise you that big players see many opportunities for podcasting that don’t yet exist, and they’re going to need to partner with savvy creators to fill the gaps.
Of course, these players are going to be very choosy about who they decide to partner with. For all the privacy reasons you and I can think of, they’re probably not going to open-source their datasets. But that doesn’t mean indie-minded podcasters are locked out of the opportunity. Just by paying attention to announcements like “Shots of Science Vs” and playing Follow the Leader, you might find success.
It’s a foregone conclusion that these keepers of the data are going to start creating content based on that data. Or, perhaps more likely, they're going to start commissioning content based on that data.
If you were approached by one of these entities, would you change your show completely to better match the need evident in the data? Would you just cancel it and start over again with a brand-new show, laser-focused on that need? Or would you keep on doing your current show and the new show, especially if you knew there was an untapped market that a big partner could expose just for you?
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And if you are in business and need some help figuring out how big data could impact your podcasting strategies, get in touch with me, as I can help you with that. email@example.com or just go to PodcastLaunch.pro to see what we do.
I shall be back tomorrow with yet another Podcast Pontifications.