You’re Probably Undervaluing Your Podcast Ads — Here’s How to Measure What’s Actually Working
Reshma Patel
Head of Finance
,
Fairing
Most marketers are undervaluing their podcast advertising.
Not because their ads are underperforming—but because their attribution models weren’t built for how conversions from podcast advertising actually happens.
If you're running podcast ads and relying solely on promo codes, last-click attribution, or pixel-based attribution to prove performance, you're likely missing critical insights. And in some cases, you're even cutting campaigns that are quietly doing the best work.
This post breaks down:
Why podcast performance often looks weak on paper
What that data gap is costing you
How sophisticated teams are measuring podcast ROI today
A simple, scalable way to start capturing what’s actually working
The problem: podcast ads don’t behave like digital ads
Click-based attribution was never built for audio. Podcast listeners are highly engaged, but they’re not in a place to click. They’re driving, lifting, walking, or working. When they hear about your brand, they store it away. Later, they search for it or are reminded of it by a mention on another platform.
That non-linear path—between hearing the ad and taking action—breaks most attribution systems. The path to conversion looks invisible. So instead of showing up as a successful campaign, your podcast ad gets no credit.
And when high-performing campaigns don’t show up in reporting, they’re the first to get cut.
Simulcast fragments the path even more
In 2025, most podcasts aren’t just podcasts. They’re multi-channel content machines. The same episode gets:
Streamed on YouTube
Clipped on TikTok
Promoted through Reels, Shorts, and Stories
Referenced in creator newsletters
Shared in Facebook groups and Reddit threads
Which one of those touchpoints caused the customer to remember you? It’s hard to say—and even harder to track. Simulcast has expanded your reach, but it’s also scattered the attribution path across platforms with no shared analytics or pixels.
Most attribution tools can’t track that kind of influence. But customers can. And that’s the key shift in how smart teams are measuring today.
Promo codes and vanity URLs help—but only tell part of the story
You should absolutely use promo codes and vanity URLs. They give you a clean, bottom-funnel conversion path when they work.
But here’s the catch: most customers don’t use them. Even when they were influenced by the ad, they’ll forget the code and purchase anyway. So the code never gets used, and the campaign never gets credit.
Relying on redemptions alone is like trying to evaluate a brand campaign with only direct clicks. It tells you something—but not the whole story.
Pixel-Based Measurement
Pixel-based measurement in podcast advertising - used by companies like Podscribe and Claritasin - involves matching the IP address of the listener at the time of ad exposure to the IP address recorded during a conversion event, such as a purchase on the advertiser's website. This method allows advertisers to attribute conversions to podcast ads, even when listeners don't use promo codes or vanity URLs.
By matching the IP addresses, advertisers can infer that the same individual who listened to the podcast ad also made a purchase, thereby attributing the purchase action to the ad exposure.
However, this method has its challenges. IP addresses can be shared among multiple users, especially in environments like offices or public Wi-Fi networks, leading to potential inaccuracies. To mitigate this, sophisticated attribution platforms use statistical modeling to account for "noisy" IP data and improve attribution accuracy.
While pixel-based attribution is a valuable piece of the puzzle, it has key blind spots—especially with offline or delayed conversions—that limit its ability to tell the full story.
What sophisticated teams are doing: triangulating signal
The most effective marketers today don’t try to force podcast ads into click-based systems. They triangulate attribution using multiple signals—and they start by asking the customer directly through Attribution Surveys.
One question: "How did you hear about us?"
When you ask this question post-conversion, you get insight into the real moment of discovery—which is often long before the purchase, and well outside the reach of your pixel.
With the right system in place, this response gets structured, categorized, and fed into your reporting workflow. It reveals:
Which podcast shows, clips, and creators actually drove the brand impression
Whether discovery happened on an audio network, YouTube, or social network
What percentage of your customer base was influenced by hard-to-measure media
And when paired with code redemptions, traffic spikes, and occasional lift tests, triangulation gives you a complete picture of what’s driving demand—even if it happens offline.
Attribution surveys only work if they’re built for complexity
Attribution surveys are powerful—but not all survey tools are equal.
To really make surveys work, you need more than a simple form field. You need structure:
Open text with auto-suggest prompts, so customers type in “Armchair Expert” and see it standardized
A reclassification engine that maps open responses into structured data
Taxonomy management that keeps simulcast environments tidy (so “YouTube version of My First Million” and “My First Million podcast” don’t get split)
Clean integrations into dashboards and CRM tools where decisions actually happen
When all of this is handled within your attribution survey platform, the result is simple: the data comes out clean, and your team knows what’s working.
From noise to strategy
When you know which shows, creators, and formats are truly moving the needle, your planning gets sharper:
You keep the budget for shows that matter—even if they underperform in click-based reporting
You negotiate renewals with confidence
You align media buying with what your customers actually remember
And you give your executive team the clarity they need to keep funding long-term brand-building channels
TL;DR: how to actually measure podcast ads in 2025
If you're serious about measuring podcast performance today, here's the approach:
Accept that clicks and pixels won't tell the full story
Ask your customers “How did you hear about us?”
Use your attribution survey provider to reclassify and normalize that data
Triangulate with promo codes and click/pixel-based attribution sources
Build budget and creative strategy around what that data tells you
This is how high-performing teams are keeping their best channels funded—while others are still cutting them based on incomplete data.
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