Overview

The session focused on the complexities of podcast measurement, emphasizing the challenges and potential solutions. Carl Weinstein, COO of Locked On Podcast Network, along with Matt Mallon, Kylee Young, and founder David Locke, discussed their unique approach to podcast measurement and advertising. They highlighted how their network aggregates content from over 200 daily sports podcasts, creating a large, engaged audience despite the niche nature of individual shows.

Dan Misner from Bumper later elaborated on the fragmented state of podcast measurement, criticizing the industry's reliance on downloads as a primary metric. He advocated for focusing on people and time spent listening, using verified listeners and watch time from platforms like Apple, Spotify, and YouTube to provide a more accurate picture of audience engagement.

Core Concepts

Fragmentation in Podcast Measurement

The podcast measurement landscape was fragmented, with no single source of truth. This fragmentation made it difficult for podcasters to get a clear and consistent understanding of their show's performance.

Key Points:

• Multiple platforms like Spotify, YouTube, and Apple Podcasts provided different metrics.

• Podcasters had to log into various dashboards to gather data.

• Changing hosting providers added another layer of complexity.

Examples:

• A podcaster might look at Spotify for podcasters dashboards, YouTube Studio, and Apple Podcasts Connect, each offering different metrics.

• Switching hosting providers required comparing data from old and new providers, complicating year-over-year analysis.

Quotes:

Fragmentation is a problem. What does that mean in podcast measurement? It means that there is no single source of truth.

This makes our measurement story a bit of a mess.

Jargon Overload

The industry was filled with jargon, making it difficult for podcasters to understand and compare metrics across different platforms.

Key Points:

• Different platforms used varied terms for similar metrics, such as downloads, listeners, plays, and streams.

• This jargon created confusion and made it challenging to aggregate data meaningfully.

Examples:

• Apple Podcasts Connect talked about listeners, engaged listeners, followers, and plays.

• Spotify for podcasters used terms like starts, streams, listeners, followers, and consumption hours.

Quotes:

Jargon is a problem. We as an industry love jargon.

These are not numbers that we can responsibly add together. This is a mess.

Overemphasis on Downloads

The industry's focus on downloads as the primary measure of success was misleading. Downloads did not necessarily equate to actual listeners or consumption.

Key Points:

• A download was simply a request for a file, not an indication of actual listening.

• This focus led to a skewed understanding of audience engagement and size.

Examples:

• A podcaster might see high download numbers but have no idea if those files were actually listened to.

• The IAB defined a listener as someone who downloaded a file, regardless of whether they listened to it.

Quotes:

A download is not a person. A download does not represent any consumption behavior whatsoever.

Asking your podcast hosting provider how many listeners I have is a scary thing because they're going to suggest that they know and they don't know.

Importance of Measuring People and Time

Shifting the focus to measuring people (verified listeners) and time (listen and watch time) provided a more accurate representation of a podcast's audience and engagement.

Key Points:

• Platforms like Apple Podcasts, Spotify, and YouTube offered metrics that were closer to actual people and their engagement.

• Measuring time spent listening or watching provided a better understanding of audience attention and engagement.

Examples:

• Apple Podcasts provided metrics on listeners and time listened.

• Spotify offered consumption hours, and YouTube provided watch time.

Quotes:

Please, can we pay attention to people and time? These are the numbers that we believe matter.

Total watch time is a wonderful proxy measure for the thing that many podcasters actually want, which is their audience's time and their audience's attention.

Challenges with Consistency Across Platforms

Different platforms yielded different results for the same content, highlighting the need for tailored strategies for each platform to maximize engagement.

Key Points:

• The same episode could perform differently on Apple Podcasts, Spotify, and YouTube.

• Understanding these differences was crucial for optimizing content and engagement strategies.

Examples:

• A 29-minute episode might have high listen time on Apple Podcasts but lower on Spotify and very different consumption on YouTube.

• Minute-by-minute analysis showed significant drop-offs on YouTube compared to more consistent engagement on Apple and Spotify.

Quotes:

Should we be publishing the same thing to YouTube that we are publishing to other places? Maybe not.

We regularly see shows that reach a lot of people on YouTube, but don't necessarily have the watch time to back it up.

Conclusion

The talk highlighted the complexities and challenges of podcast measurement in 2024. Fragmentation and jargon made it difficult for podcasters to get a clear picture of their show's performance. The industry's overemphasis on downloads was misleading, as downloads did not equate to actual listeners or engagement. Shifting the focus to measuring people and time provided a more accurate representation of audience engagement. Different platforms yielded different results for the same content, underscoring the need for tailored strategies. By paying attention to verified listeners and listen/watch time, podcasters could gain a better understanding of their audience and optimize their content accordingly.

Food for Thought

• How can podcasters better navigate the fragmented measurement landscape to get a clearer picture of their show's performance?

• What strategies can be employed to reduce the reliance on downloads as the primary measure of success?

• How can podcasters tailor their content to maximize engagement across different platforms?