If you want your podcast audience to grow, you need to do two things:

Find new people to try your show
Keep your current audience coming back for more

Practically speaking, both are essential for audience growth. Without a steady influx of new listeners, it's impossible for a show's audience size to increase. And unless you can build a solid base of returning listeners, you'll forever need to find new listeners to replace those who churn just to maintain audience size over time.

The ratio of new audience to returning audience over time can be an incredibly useful signal of podcast health. It can help you gauge the effectiveness of your marketing, the stickiness of your show over time, and the long-term value of your loyal audience.

But there's a problem...

Most podcast apps don't report on new vs. returning audience

At Bumper, we recommend measuring audience size in people, not downloads. Thankfully, publisher-facing dashboards like Spotify for Creators and Apple Podcasts Connect offer people-centric metrics. We typically refer to these as "verified listeners" because they're based on first-party data and correspond to unique user accounts and/or device IDs.

For example, Apple Podcasts Connect reports listener count over time:

Directionally, this can be incredibly useful, because it allows us to see how many unique Apple Podcasts users a show has reached on a daily, weekly, or monthly basis. The fictional show displayed in Apple’s example above, for instance, reached ~9,200 unique listeners over the last 60 days.

But that count doesn't tell us how many of those ~9,200 users were new first-time listeners, or how many were returning listeners who had previously spent time with the show.

Of the three major podcast consumption platforms that offer publisher-facing dashboards, YouTube Studio is the only one that reports on new vs. returning audience. Neither Apple Podcasts Connect nor Spotify for Creators offer this breakdown.

I've long wanted to know this ratio, and I've long been frustrated that the audio-first platforms don't offer it. The podcast consumption data Apple and Spotify provide to publishers and creators is anonymized and aggregated, so no individual listening behaviour is identifiable. Given this, I figured Apple and Spotify’s daily/weekly/monthly listener tallies were the best I'd get.

Turns out I was wrong....

New vs. returning listener ratio is knowable

Recently, Bumper identified a technique that allows us to turn a simple tally of daily, weekly, or monthly listeners such as this:

... and break it apart to show new vs. returning audience over that same time period:

This adds a whole new layer of context to audience size over time. Suddenly we can identify the weeks we saw many new first-time listeners, and the weeks we failed to attract new listeners. It lets us see how many of our weekly listeners are returning from previous periods, and lets us better understand changes in listener churn over time.

We're starting to build this metric into the Bumper Dashboard. So for the past few weeks, I've dug into new vs. returning breakdowns for all of Bumper's clients. And I've learned there are many interesting ways to use this data.

A barometer for marketing effectiveness

The most effective podcast marketing is designed to encourage people to sample a show by making a clear and compelling promise to prospective listeners. From there, it's the show's job to deliver on that promise, and be good enough to earn their time and attention. Put simply, no amount of marketing can force someone to love your podcast. That's your show's job.

So, if podcast marketing is primarily about driving sampling, and if, by definition, audience growth requires an influx of net new listeners, then the number of new listeners (per day, week, or month) can be a hugely helpful way to gauge the effectiveness of podcast tune-in campaigns. If you run paid advertising, or organize promotional swaps, or make collaborative episodes, or arrange guest appearances, one way to know if those efforts "worked" is by analyzing the number of new listeners gained while those efforts were in market.

Moreover, week-over-week or month-over-month comparisons of new vs. returning listeners can help podcasters understand whether the prospective listeners they reached with their marketing were qualified.

For example, if a weekly show sees a big spike in new listeners one week, but doesn't see a corresponding increase in returning listeners the following week, there's a chance many new listeners were "one and done." Perhaps the marketing that drove them to sample was mis-targeted, or perhaps the show itself failed to live up to the promise the marketing made.

Effective podcast marketing for a high-quality show should reach prospective new listeners who sample... then come back for more.

A diagnostic tool for audience growth challenges

When a podcast audience isn't growing, there are two common reasons:

Not enough new listeners
Existing listeners are churning

These are different problems. If a show isn't reaching enough new listeners, it probably has a marketing problem. And if repeat listeners are churning faster than they're being replaced, the show might have an editorial problem. Some shows have both problems.

If your audience is declining, you owe it to yourself to understand why, so you can intervene appropriately. Spoiler alert: marketing seldom fixes underlying editorial problems.

Speaking of declining audiences...

Don’t cater to a shrinking audience

Tom Webster of Sounds Profitable has written some great advice about podcast audience surveys and how to make the most of them. Alongside that, he offers an important warning about the dangers of relying on listener surveys when your show’s audience is shrinking.

Survivorship bias is a thing. Or as Tom puts it, it’s important to be aware of the possibility that you are “making fewer and fewer people happier and happier.”

If your audience is declining, those who remain are unlikely to tell you how to increase the size of your audience. As such, you may want to take audience survey results with a grain of salt. The same applies to metrics like average listen time. Increased engagement among a decreasing number of people isn't always sustainable in the long term.

A new vs. returning listener analysis can help identify signals of churn among returning listeners, and help avoid the trap of over-serving the desires and consumption patterns of a declining audience.

How to calculate new vs. returning listeners

Even though new vs. returning breakdowns do not appear in their dashboards, both Apple Podcasts Connect and Spotify for Creators offer podcasters the ingredients necessary to calculate new vs. returning listener breakdowns for themselves. To make the calculation, we need two basic ingredients:

A running tally of cumulative all-time unique verified listeners over time
Time-windowed daily, weekly, or monthly counts of unique verified listeners

From there, we can rely on the inclusion-exclusion principle to derive a breakdown of new vs. returning audience. Once you have the two sets of required timeseries data, the arithmetic is very simple.

A quick note for measurement nerds

"Wait a minute, Dan," you might be thinking to yourself. "You said that most podcast apps don't report on listener churn and retention. Didn't Chartable offer episode-to-episode retention metrics?"

Yes... sort of. Chartable and a handful of other measurement companies have offered episode-to-episode retention metrics. All of them are based on the IAB's flawed (and misleading) "listeners" number, which is in turn based on downloads. There are several issues with this. Firstly, repeat downloading is not the same as repeat listening, especially when automatic downloads are a factor. Secondly, IAB's download and "listener" measures are based on IP address and user agent strings. In the vast majority of cases, these are not stable identifiers over time. My phone's IP address today is not the same as my phone's IP address last week. And it's certainly not the same IP address as last month, or last year.

Any audience retention measure built on top of IP addresses is almost certainly guaranteed to show a steady, inevitable march towards 100% churn. Why? Because eventually, nearly everyone's IP address changes.

The technique Bumper uses to calculate new and returning listeners is not based on volatile identifiers like IP addresses. Rather, it's based on first-party data from Apple and Spotify, where consumption is tied back to unique user accounts and device IDs, which are significantly more stable over time.

New and returning listener analysis is coming to the Bumper Dashboard

I've spent a lot of time analyzing Bumper's clients' shows through the lens of new vs. returning listeners. I've spotted a number of patterns that suggest healthy growth over time, and patterns that shed light on symptoms related to declining audiences.

After years of wishing for this metric, I'm delighted that we've identified a technique to calculate it, and we've started to use it in our work with clients. It's been so useful that we plan to add it to the Bumper Dashboard, our proprietary measurement aggregation tool.

If you have access to the Bumper Dashboard, stay tuned. If you don't have access to the dashboard, we have a waiting list.

Remember

Sustainable podcast audience growth requires both net new listeners, and returning listeners
Daily, weekly, and monthly listener counts are directionally helpful, but often hide detail about audience composition
YouTube Studio offers a new vs. returning audience comparison. Apple Podcasts Connect and Spotify for Creators do not. Despite this, podcasters can manually compute new vs. returning audience figures using data provided by Apple and Spotify.
Effective podcast marketing convinces prospective net new listeners to sample a show. These listeners show up as net new first-time listeners.
Great shows keep listeners listening again and again. These listeners show up as returning listeners.

Keep 'em coming back: how to measure podcast audience churn and retention