Moonbeam: New Podcast App from Kayak Co-founder Paul English

The Rise of Podcast Discovery and the Launch of Moonbeam

Over the past year, podcast consumption has experienced significant growth. Paul English, the co-founder of Kayak and a seasoned tech entrepreneur, has become a dedicated, daily podcast listener himself.

However, a common frustration for podcast enthusiasts is the difficulty in discovering new content. Existing streaming platforms, including industry leaders like Apple Podcasts and Spotify, often lack comprehensive discovery features.

Spotify's Acquisition of Podz and the Need for Innovation

The recent acquisition of the podcast discovery application Podz by Spotify underscores the increasing demand within the industry for more effective methods of uncovering new shows.

Today marks the launch of Moonbeam, a new podcast discovery app developed by Paul English. It utilizes a combination of machine learning algorithms and human curation to deliver personalized recommendations to users.

Moonbeam: A Creator-Centric Approach

While similar to Podz in its creation of a content stream tailored to user preferences, Moonbeam distinguishes itself by prioritizing a creator-friendly environment.

Podcast hosts are empowered to select and feature specific clips from their shows directly within the app.

Furthermore, the app facilitates direct support for creators, allowing listeners to send tips to their favorite podcasters. Moonbeam itself does not take a percentage of these tips, though standard in-app purchase fees may apply.

English's Vision and Inspiration

“Podz represents one avenue for discovery, but I believe that multiple solutions are necessary to address this challenge,” English stated in an interview with TechCrunch.

“A key differentiator for Moonbeam is our integration of human editors into the process.”

English drew inspiration from the success of TikTok, a platform renowned for its sophisticated discovery algorithm. He frequently redesigns apps as a personal engineering exercise, having previously worked with Instagram and Twitter.

Leveraging Machine Learning for Personalized Recommendations

English aimed to replicate TikTok’s functionality within the podcasting space, creating an app that facilitates the discovery of new shows.

The “Beam” section of the app, analogous to TikTok’s “For You” page, presents users with short clips, typically a few minutes in length.

The algorithm learns user preferences based on their interactions with these clips, refining its recommendations over time.

The Power of User Clustering

“Machine learning has the potential to identify content that resonates with you more effectively than your personal network,” English explained.

“We might discover someone in Germany who shares your unique sense of humor, potentially differing from even your closest friends.”

“Machine learning relies on user clustering, grouping individuals who interact with Moonbeam in similar ways. By identifying users with comparable tastes, we can share podcasts they enjoy.”

Addressing the Challenges of Podcast Discovery

The effectiveness of apps like Moonbeam is directly correlated with its user base. In its initial phase – launched today – recommendations often focus on well-established podcasts.

However, given the vast number of podcasts available, the true challenge lies in discovering emerging creators who may lack the support of major production studios.

TikTok’s ability to propel creators to viral success overnight highlights the potential for a similar platform within the podcasting industry.

Future Updates and Enhanced Creator-Listener Interaction

Moonbeam is committed to releasing software updates every two weeks, introducing new tools designed to foster interaction between listeners and podcast creators.

The first of these features, already implemented, is the tipping functionality.

Soon, both fans and podcasters will have the ability to create and share clips on the app. Currently, podcast hosts can claim their show on Moonbeam’s website and begin creating clips, although the process is less streamlined than platforms like Headliner.

Building Direct Relationships

“We are planning to introduce a range of additional tools to connect listeners and hosts,” English added.

“Cultivating this relationship is paramount, and we aim to facilitate it directly within the player, eliminating the need for external platforms like Facebook.”

Moonbeam as a Podcatcher and Discovery Tool

Moonbeam also functions as a traditional podcatcher, allowing users to listen to full episodes and search for specific shows, even those not featured on their personalized “Beam.”

While numerous podcatchers exist, effective podcast discovery applications remain relatively scarce. Moonbeam aims to address this gap and improve the overall podcast listening experience.