Frequency Capping: A True Native Media Study

“When we’re thinking about creating any predictive capabilities or forecasting, it needs to be complex. It can’t just be as elementary as it really is right now. And while I do absolutely believe that frequency capping should exist… I believe the technology is not there yet.”

Frequency capping is podcasting’s newest hot topic. 


As advertisers, we know we want long-running campaigns where we can get in front of as many people as possible, but that’s not where our job ends. It’s also our job to say, “Hey, the audience needs a break from hearing about this ad,” when necessary. 

Frequency Capping: The ability to define the maximum number of times an ad can be delivered to a listener within a given time period.

Frequency capping is a great addition to the industry, but its current iteration leaves us with more questions than answers. 

The Problem

An easy way to think of frequency capping is to ask, in a two-week or four-week campaign, how often has this person heard this ad?


This might prompt you to think of the marketing rule of seven, a long-standing idea that says the consumer needs to hear about your product seven times before making a buying decision. Many advertisers still use this rule today, but the advertising world has changed significantly since this rule developed in the 1930s. 


In Spotify Ad Analytics’ benchmark report for Q2 of 2023, they found that advertisers have the highest conversion when they have a frequency of two to five for a given campaign. 

It’s become an advertiser’s job to make sure a consumer is hearing about your brand just enough to influence a buying decision but not too much that it leads to listener fatigue. 

Listener Fatigue: A phenomenon that happens when users are exposed to too many ads and when they see the same ad too often. This can result in users ignoring the ad altogether.

The current issue the podcast industry has been facing with frequency capping is that when an advertiser puts a frequency cap on a campaign, we have no idea how many impressions are actually going to be delivered. It becomes a game of estimation; we’re not sure if that means we can deliver 30,000 impressions or 40,000 impressions because of the way frequency capping changes the ability to predict how many impressions are going to be delivered. 


Which led us at True Native Media to the question: “If we put a frequency cap on a given campaign, how many impressions do we think we can deliver?”


To answer this question, we turned to our resident software expert, Anthony Firn

The Findings

There are numerous different types of frequency capping, with the simplest being a campaign over a 30-day period where the full flight is 30 days.  In this situation, there is no reset period. Instead, you can directly calculate reach per unique listener because those unique listeners will only get so many impressions before they max out. You can then use this information to figure out which listeners will max out their reach and which won’t in order to determine your expected impressions for that flight. 

“For a non-frequency capped campaign, the impressions are going to be closely related to downloads. In a frequency-capped campaign, because you’re artificially dropping the number of impressions, the goal is to reduce the reach.”

To determine the exact number of impressions a certain frequency-capped campaign can deliver, Anthony created a simulation to randomly choose if a listen is going to happen every day and then tried to fit those simulation numbers into real results we see in real campaigns. 


This led Anthony to one of his most interesting findings – not all listeners are created equal. Some listeners will listen to their favorite show as the episode is published, while others will binge an entire podcast over the span of a few days. 


In the simulation, this left Anthony with a large group of individuals who only listen to a podcast once or twice a month and a much smaller group that listens to a podcast many, many times. And while this information is podcast-specific, it’s safe to assume every podcast will have a mixture of heavy to not heavy listening individuals. Meaning identifying each group is one of the first challenges we need to address in order to make a stochastic prediction. 


Another factor that needs to be considered when trying to predict impressions from a frequency-capped campaign is the drop days of the episode. The results from a show that publishes episodes daily will be vastly different from shows that only release episodes twice a month.

The Future

Ultimately, the promised impressions after a frequency-capped campaign are podcast-specific. You can have one show where they were able to deliver their full number of impressions for the campaign but also have one that could only deliver 7%. 


This goes to show how, without a simulation like Anthony’s, we’re operating in the dark. If we’re promising impressions, we need to know we can deliver them. But there isn’t a sophisticated enough tool out there to determine this with certainty… yet.

“We don’t have the full picture yet. We’re going to continue to investigate.”

We know we want to make sure we’re getting the results that advertisers are looking for. We know we want to make sure our campaigns are converting well, but the technology isn’t there yet. 


Our hope for frequency capping is that we continue to talk about it and continue sharing research like Anthony’s. 


It’s easy to feel like you’re talking into the void when you’re in your office alone with a podcast mic, but this industry has a strong community. It’s our responsibility to come together and have that hard conversation about what isn’t working and how we can fix it.

If you are interested in buying podcast ads but have no idea where to start, read this article, Podcast Advertising Best Practices Every Marketer Should Know, and contact us at


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LinkedIn – Heather Osgood | True Native Media | Podcast Advertising Playbook

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