Podscribe, whose recent research revealed that 99% of podcast advertisers reach only one-quarter of potential listeners, has launched a TransUnion integration that offers brands precise demographic intelligence on exactly who converts from podcast advertisements.

The new integration matches IP addresses from podcast downloads to TransUnion’s household profiles, revealing whether homeowners, college graduates,  high-income households, or hundreds of other audience segments are responding to specific podcast campaigns. 

TransUnion is one of the big three credit bureaus in the U.S. that allows consumer insights to be extracted. Within the TransUnion system, there is an identity graph that allows the translation of different signals.

“The integration allows advertisers to see what profiles are over-indexing,” explains Camden Weber, Senior Director of Partnerships at Podscribe. “We’re over-indexing for conversions of homeowners, or we’re over-indexing for audiences with a professional or technical occupation. This allows us to execute our next campaign more strategically, taking these learnings and building a better plan based on the data supporting the narrative.”

Podscribe chose to partner with TransUnion because of its extensive consumer database and identity resolution tools. Camden, who joined Podscribe eight months ago after spending nine years in measurement and attribution at Claritas, helps partners incorporate these insights into their marketing strategies.

Podscribe’s partnership with TransUnion also combines its Neustar device graph with Experian’s Tapad, creating a double device graph for scale and accuracy in podcast measurement.

With the combined coverage of the two leading U.S. device graphs, Podscribe can now match over 85% of U.S. households to an internal household and has three times more digital identifiers available for improved attribution precision.

The largest brands working with Podscribe specifically requested more detailed analytics about their audiences. “Advertisers wanted to get a more granular view of the types of consumer segments responding to their ad campaigns,” Camden says, one of the driving factors behind the TransUnion integration.

Internal growth at Podscribe also played a role. “We’ve been growing that team, we’ve been growing our commercial team, we’ve been growing our support team. And so as the team grows, we’re also investing in growing the product,” Camden says. 

Additionally, as the podcast advertising market expands, advertisers increasingly expect the same measurement capabilities they’ve become accustomed to in other digital media channels.

Two Key Features for Podcast Advertisers

The TransUnion integration adds two major new features to Podscribe’s platform, improving advertisers’ ability to understand podcast audience composition and campaign performance.

The first feature is Detailed Audience Reporting for Publishers and Planners. This adds to Podscribe’s research and planning tools with detailed audience breakdowns for podcasts in their database, giving publishers clear insight into their listener demographics while helping advertisers identify shows with audience profiles matching their target customers.

“From a publisher standpoint, it is a more deterministic tool to understand the audience breakdown of their network or their individual shows,” Camden says. “If I am a podcast network and let’s say the majority of my shows are true crime, I may have some assumptions that my listeners are maybe majority women between the ages of 18 and 55. This becomes a great tool for publishers to have a holistic view of who is listening.”

The tool provides insights across multiple categories, including net asset value, ethnicity, marital status, homeownership status, political alignment, automotive behaviors, and financial behaviors.

“Because I see that I’ve got a high propensity for Toyota truck drivers in my audience, I can take this insight and go to Toyota and say, ‘You should be running ads across my shows,’” Camden explains. “They can be found here, we can reach them.”

The second major feature is Conversion Attribution with Demographic Profiling. It applies this demographic information to campaign measurement, showing which audience segments are most responsive to a brand’s podcast advertising.

“When we’re measuring campaigns actively, the attribution portion of our dashboard showcases the index of the different profiles of people converting,” Camden notes. “We may see that if I’m Bombas socks, for example, people of a certain education or households of a certain income level are 20-40% more likely to buy your products.”

These insights help with media planning by helping brands find additional podcasts with similar audience compositions to their best-performing shows. As Podscribe’s CEO, Pete Birsinger, noted in the company’s press release, this essentially brings “lookalike audiences to broadcasting.”

The Path Forward: From Measurement to Activation

The TransUnion integration is a key step in Podscribe’s product plans, but it’s just one element of the company’s approach to podcast advertising. The next phase will add these audience insights to Podscribe’s planner tool.

“The next initial phase is to incorporate this into our planner, which is more of a sandbox environment for advertisers to play around with media plans or potential media plans,” Camden explains. “The planner will allow marketers to find shows and add them to a mock media plan to see my net new reach if I were to add these shows, and how much of my existing audience can be found listening to them.”

According to Camden, this will allow advertisers to test campaign performance before allocating budget, using TransUnion’s audience data to estimate reach and effectiveness without committing media dollars to validate what performance may look like.

Also in development is Podscribe’s “Reacher” tool, which is currently in beta testing. This feature would enable advertisers to execute targeting strategies directly through their preferred DSPs (demand-side platforms).

“We’re also exploring in early stages of beta testing something that we’re coining the reacher, which is the ability for an advertiser to plug this data into their DSP of choice and run anti-target campaigns or retargeting campaigns or lookalike targeting campaigns,” Camden says.

Camden provides a specific example of how this would work: “We work closely with BetterHelp, for example. They run ads everywhere on so many different shows, hundreds of millions of impressions. In that use case, they want to anti-target people that they’ve previously reached. We want to get their message out to as many net-new people as possible.”

Challenges in Podcast Measurement

Despite these improvements, podcast advertising measurement still has inherent limitations. Camden mentions several persistent issues:

Access limitations: “Spotify has its premium video content that is, from a third-party measurement perspective, not a trackable source of impressions,” Camden explains. Similar issues exist with podcast content on YouTube and Rumble, where third parties can’t get the data needed for attribution.

Noisy IP addresses: Commercial locations, public Wi-Fi, and cellular connections make household matching difficult. “When people are traveling and on a cell tower IP address, or in a Starbucks or the office, those are commercial IP addresses. Those are many-to-many matches,” Camden notes. Podscribe models these conversions rather than using direct matching, which would create noisy signals.

Impression verification: Unlike display advertising, podcast downloads don’t guarantee ad listening. “We don’t know, or nobody knows, if the consumer listened to the ad. We just know it was delivered,” Camden says, comparing it to traditional TV advertising where “we know the ad was delivered, but we don’t know if anybody was in the room when the TV was on.”

Despite these issues, Camden sees podcast measurement as much improved. “Six years ago, this was novel and challenging, with a lot of troubleshooting to ensure that things went smoothly. But the environment and technology have matured and grown a lot,” he says. “This is expected on all podcast campaigns from our perspective. Most advertisers require some sort of third-party measurement to validate reporting and what’s working or not.”

Advice for Brands New to Podcast Advertising

For brands just starting with podcast advertising, Camden offers practical advice that acknowledges the field’s complexity while emphasizing the value of partnerships.

“Don’t be afraid to ask the dumb questions. The environment’s always changing,” he advises. “What you understand about the ecosystem today may be different tomorrow.”

Camden suggests that brands use expertise from their podcast partners rather than trying to become measurement experts themselves. “If you’re a brand, you’re an expert about your product, your service. It’s good to have enough information about the inner workings of the ad servers and macros, how this data collection takes place, and how an exposure connects to a conversion. But you don’t need to be an expert in that,” he explains.

Instead, Camden recommends: “Find a podcast publisher with an ad operations or analytics team that you can lean on for support to unpack performance, unpack the technology, and ensure that you’re supported throughout the buying process.”

As podcast listening increases, Podscribe’s measurement tools help ensure that advertising dollars follow listener attention by closing the measurement gap between podcasting and other digital channels.

“We’re excited about the attention that the integration with TransUnion got,” Camden says. “I’ve spent the past nine years in this industry, and I’m perpetually blown away by our team’s ability to build.”