Joe Wikert's DisruptorFest

Here’s what book publishers can learn from the podcast model

Did you make the same mistake I did and assume podcasts are yesterday’s platform, that interest in them has plateaued (at best) and they’re not worth thinking about today? If so, here’s a short article that might help you re-think your stance. If you’re still not convinced have a look at the infographic in this article, paying close attention to the chart showing how podcast listening is on the rise.

What seemed like a fad that’s dying off is actually showing nice growth. I’m contributing to that growth as I now listen to a variety of podcasts during my daily work commute. As I leverage this medium I’m realizing it offers some very important lessons for book publishers:

Simple, easy subscriptions – When I discover a new podcast I’m interested in I literally click once to subscribe and the content stream comes to me. What could be easier? More importantly, what’s the analogy in the book publishing world? How do I “subscribe” to an author, series or topic? We all have our favorite authors. Wouldn’t it be terrific if a single click could initiate a subscription to everything they write in the future? That includes having samples of their new books delivered automatically to your preferred reading app/device.

Steady rhythm – Your favorite podcasts are usually delivered on a predictable schedule. Some are daily while others are weekly. This rhythm leads to anticipation, knowing that today’s edition will be loaded on your device at the usual time. This is another concept that’s totally foreign to book publishers. Books are released according to seemingly random schedules and some publishers are still even locked into the old “season” model. If you’re going to enable readers to subscribe to an author or topic as described above, be sure to produce a steady, engaging stream of valuable content for your audience.

Discovery – This remains one of the hot topics, always on the minds of book publishers. If you’re focused on discovery think about this question: How well do each of your products enable discovery of your other, related products? Some publishers still rely on back-of-book ads, even in ebooks. How about automatically delivering other, related content to your audience? A good example is how NPR promotes new podcasts. Yes, they advertise by plugging new ones in old, established podcasts. But recently I noticed they took the bold step of automatically downloading the first segment of a new podcast onto my device. I don’t recall opting in to that and it might irritate anyone keeping a close eye on their data plans but it’s a novel concept. I wasn’t going to seek that new podcast out and now all I have to do is click “play” to try it out, yet another example of one-click access and engagement.

If you haven’t been paying attention to the podcast marketplace it’s time to take a closer look. Subscribe to two or three that look interesting and see what other lessons can be learned.

Here’s how Siri, Alexa and other IPAs will revolutionize publishing

For the past several years I’ve been writing about how containers such as books, newspapers and magazines are slowly fading away. They’ll certainly be around for many years but their relevance will slip into the background as personalized, digital content streams become more important.

The more I think about the future the more I believe two other trends will have an even more significant impact on reading, learning and engaging with content: voice user interfaces (VUI) and artificial intelligence (AI).

Today Apple’s Siri and Amazon’s Alexa are mostly perceived as gimmicks. Tomorrow these intelligent personal assistants (IPAs) will become the gateway to a whole new way of consuming and interacting with content.

A few weeks ago I wrote about how these IPAs need to break free of their current apps and devices, becoming platforms to a broader set of content services. It’s great that Amazon’s Alexa can now be experimented with via the Echoism.io site, but how long will it take before these services realize their full potential, not simply serve as a way to ask whether or not it will rain tomorrow?

Ultimately, I’m convinced these IPAs will enable us to have conversations with the most knowledgeable experts we’ll never meet and who really don’t even exist. Think about that for a moment.

It’s one thing to ask Alexa questions like, “what was the score of last night’s Cubs game?” or “what was Muhammad Ali’s most famous quote?”. It’s entirely different when you treat the device like a trusted advisor or teacher by asking things like, “who was the best Cubs player of all time?”; in this case, the response can’t simply be retrieved from a reference guide as it requires a highly subjective answer based on gathering and interpretation of facts as well as a healthy dose of conjecture. That’s where AI comes into play.

The model I’m describing likely requires AI capabilities that are more powerful than today’s. In 2016 company like Narrative Science can take a baseball game box score and turn it into a two-paragraph newspaper summary; tomorrow these AI platforms will need to be able to tell more of the story as well as answer questions like, “how did Anthony Rizzo get to second base in the fourth inning?”.

Let’s apply this to a more interesting, lengthier use-case. Maybe I want to learn about electricity and electrical wiring for a home project I’m working on. I want to do this all via voice and audio during my daily commute to and from work. Today I could turn to a variety of YouTube videos, websites and books. Tomorrow I want to simply start with this request: Tell me the essentials of electricity.

The IPA then dives right into a tutorial, perhaps taken from one of those resources noted earlier (e.g., books, websites, etc.) The session is highly interactive though. Every so often I might ask a clarifying question like, “what’s the difference between the black wire and the white wire?” or “is a wire nut OK on its own or should I also wrap the connection in electrical tape?”, and the assistant provides the answers then returns to the lesson.

To contrast, in today’s world we’re used to thinking in terms of the document model and how search results are simply an intermediate step. That step might just be one of many the user has to proceed through to ultimately get their answer. In the IPA world of tomorrow the experience needs to feel more like a conversation with an old friend or instructor; the IPA selects the best path rather than relying on you to find the needle in the search results haystack.

All of this dialog presumably will go through the Amazon’s and Google’s of the world and the answers come back through those same gatekeepers as well. But ultimately consumers will insist on the dialog and answers coming from other trusted brands and sources. So one day I might start that electricity session by saying something like, “take me to the Home Depot channel” and then I can have my dialog within an ecosystem of more reliable, highly relevant content and responses.

In order to make this giant leap the content must either be richly tagged, thoroughly analyzed by a powerful AI platform or a little bit of both. Either way I’m excited about the new opportunities it represents.

Let’s take “Search Inside the Book” to a whole new level

Do you remember when Amazon introduced both “Look Inside” and “Search Inside” functionality for books? They were such simple yet revolutionary features at the time. Before Look/Search Inside it was impossible to do a simple flip test like you could at a brick-and-mortar store.

Fast-forward to today where we take Look/Search Inside features for granted, so much so that there’s been virtually no innovation on this front. I believe there’s a real opportunity here though to help consumers find what they’re looking for as well as significantly improve the overall content discovery and evaluation process.

Let’s start with a simple question: Why are Search and Look Inside both limited to individual books? What if my first problem is to figure out which book has the most in-depth coverage of topic xyz? Let’s say I want to do some research on the Pittsburgh Pirates, specifically looking for coverage of a former player named Dave Parker. How do I find the book with the most in-depth coverage of Parker?

The typical approach is to search on Amazon. The search results there are initially sorted by relevance and you might think that’s the end of the story. But all Amazon is really doing is searching the metadata associated with each book; they’re not searching the actual contents of the books to push titles with higher relevance to the top of the results. That means books with that name or phrase in the title often get pushed to the top.

Take a closer look at those search results and you’ll quickly appreciate just how ineffective the current Amazon solution is. You’ll need to skip past the first four results as they’re not books at all; I requested “books” only but the results reflect the challenges Amazon has with internal product types and definitions. Those are followed by a couple of titles that have nothing to do with Dave Parker the former baseball player but they happen to be authored by another guy named Dave Parker. This shows how much Amazon’s search prioritizes a book’s metadata; there are probably very few references to “Dave Parker” inside those books but these titles float toward the top of the results simply because of the author name. Next is a book about Dave Winfield, another former baseball player, which looks promising. The problem here is that it made it to the first page of results because the book’s co-author is Tom Parker, so when Amazon sees “Dave Winfield” and “Tom Parker” next to each other it thinks there’s a hit because of the former’s first name plus the latter’s last name. Ugh.

At this point you might think the solution is to go to Google Book Search. Take a look at Google's results and I think you’ll agree I’m no closer to finding the right book than I was at the start. To be fair, Google Book Search is a better solution than Amazon’s search but there are still some enormous holes. For example, although Google’s service is searching the book contents it’s still highly biased by the metadata. Just look at the author names of the first several titles in those search results and you’ll see what I mean. Also, Google is severely limited because their solution is tightly connected to their book preview service. That means Google will only show you some of the pages with hits, hiding many others and then completely cutting off your view once you reach a certain threshold.

What we really need is something like Google Book Search across an entire library, with full visibility into all the content, featuring an algorithm that’s smart enough to focus on true relevance and isn’t thrown off simply by metadata. The results would show two or three lines of the text surrounding each hit so the reader can appreciate the context throughout.

This uber-search would be powerful for some types of books and totally useless for others. For example, there’s absolutely no need for it in the fiction space but think about how useful it would be in non-fiction areas like business, science, technology, biography, cooking, etc. I see this as a service a publisher could place on their website, dramatically improving the current metadata-only search results you typically find.

In fact, this uber-search vision is a service my OSV colleagues and I are currently exploring with a third-party developer. Before we get too far along with it we wanted to describe it for the publishing community to see if anyone knows of a better solution that already exists. We haven’t found one yet but as we roll it out we’ll be sure to describe the process here so other publishers can learn from our experience and potentially embrace our solution as well.