The Present Future of Audio: Talk, Music, Video, Interactivity – a16z Podcast

a16z podcast has had two very interesting episodes on the past, present and future of audio. This episode goes deeper into understanding the trends, why audio as a content format looks promising and some great insights into Spotify’s journey of launching podcasts within the same app.

Here are my notes/summary of the episode.

Understanding Audio Vs Video TRENDS

  • Background vs foreground audio – E.g. music may be a background audio (music) or the main element (eg podcast). Video usually does not have such a concept
  • Active vs passive mode of content consumption – mode based framework to understand how audio or video is consumed
  • Audio is massively untapped – precisely because it can have both foreground/background or active/passive consumption. Unlike video which is mostly active consumption.
  • What all is audio – music, talk, podcast – multiple formats exist and new ones will emerge
  • Learn from the video evolution – Video is like a cheatsheet for what may happen/needs to happen in audio
Present Future of Audio Podcasts

Understanding AUDIO Trends

  • Uniqueify – A new term that the guest used to refer to what Tiktok did. If you just heard the Tiktok videos you wouldnt get it You have to look at the video to understand the uniqueness that the creator brought to it. This zone where the consumers start using the standard music/video and add their own uniqueness to it, opens up a whole new world of opportunities.
  • Tiktok is consumed one video at a time (? don’t know, never been on Tiktok). This is super helpful for the machine learning algos. Unlike a feed which has multiple posts that you as a consumer is exposed to simultaneously, Titktok product team knows exactly what you saw, for how long. What you skipped etc. The AI learns faster. Audio learns same.
  • Skipping and fast forwarding is a reality. Consumers tend to skip tracks in a playlist. If the first few seconds don’t sound exciting, they are on to the next one. Music creators have noticed this and its influencing what they create e.g. Songs used to start slow, would build up gradually. Not so much now.
  • Role of hardware – with airpods, home speakers there is a clear increase in the consumption of audio.
    • More consumer journeys (I listen to podcasts during evening walks) and content formats (audio books) are evolving.
    • Hardware is a strong signal. What situation are you in. Different jobs to be dine. It is used as a proxy to understand which job is expected. E.g. when the music (from the phone) is played on the car speakers, it is very different context from music on a home speaker. Spotify uses this signal to predict what you may expect from the app
    • Phone vs speakers. Phones are inherently more interactive. But the audio based interaction has opened up a new set of possibilities.
    • UI (interaction) and content – those are the two aspects of hardware signal that Spotify considers important
  • Impact of Covid – e.g. the Daily drive on Spotify was for the daily commute. With WFH that’s gone, how do we identify a different set of content for a similar regular consumption.
  • China leading the audio trend . Engaging with fans. Supporting a creator economy.
  • Audio creators will grow exponentially in future
  • Return on Discovery – what is the value a consumer derives from spending time in the discovery mode.

Why and how Spotify included Podcasts in the same app

  • Trade-off was between a clean-podcast-only-app with zero starting distribution vs existing app with phenomenal scale available on day zero
  • Data showed that music listening was significantly predictive of the podcast taste of consumers.
  • Build a super-app. Build something that serves that segment of consumers really well. Goes deeper into their requirements. E.g. podcast creators are hugely under-served. While multiple options exist, any platform that be the super-app for podcast creators has a good chance to scale (my assumption)
  • Steve Jobs( We know what is needed) vs Jeff Bezos (let’s see what sticks) approach to building podcasts. Spotify has an approach of Distributing decisions (find more) . Opinionated decisions. Run Experiments.
  • Build for one person. Different mindsets
  • Challenges around allowing different interactions within the same app e.g. users skip to next track in a playlist and jump 15 or 30 seconds in a podcast. One interaction, two different results depending on the context.
  • A new format of music+podcasting being launched where talk is interspersed with licensed music. Works well for both the music and the podcast creator. And it seems consumers were always used to this format, thanks to the radio.
  • Finding Signals – With 3 min songs and high levels of skip, music picks up signals (on consumers taste) very fast. Podcast is slow. really slow and will need other types of signals. E.g. hosts, guests, topics – what is the user really interested in.

Product and strategy lessons from Spotify

  • Algotorial – Discovery of content via a combinattion of editors and algos. The guest takes a great example of Songs to sing on a drive. A machine does not understand this. An editor, a human can. So the way Spotify built such lists was to get the editor to select 1000 such songs and then let the ML take over to find and recommend other such songs. Algo based scaling. Human powered data-wireframe.
  • Mood graph – Mood is one of the biggest vectors for the billion+ playlists on Spotify. People club and consumer music by their moods. (mood based advertising has been around for a while)
  • Fault tolerance is very different in discovery vs consumption modes. A user who is just browsing may be ok to find a good song after n skips. Not so much when she just needs the music. Hence finding which mode the user is in is critical. Also ML training is limited to the discovery mode sessions.
  • Product Management needs contrarian hypotheses. While ML looks at past data to predict a straight line ahead into the future. Any innovative company will continue to take contrarian views and run tests
  • Prioritization is critical. But needs to happen top down. At Spotify, the top bets are decided and rank ordered by Daniel. The logic is simple. In any big company, the CEO cannot keep track of clashes. But whenever there is a clash of projects, everyone knows which one is more important.
  • Subscription is a very strong signal. The customer is voting with their wallet. Much powerful signal than likes, comments etc.

Go to the episode but before that, what’s your take on the future of podcasting?

These are my notes of interesting Podcasts. The inferences I have drawn may not be what the host/show/guest intended for. So beware.


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