Can you tell us about your background and what led you to co-found Barometer?
I am a cognitive scientist and machine learning engineer by training and my first love has always been the brain. Since childhood, I have been fascinated by our human brain, its capabilities, and its limitations, and this curiosity led me to start my career in computational neurobiology. However, after spending many years in the lab, I wanted to work on projects that would have a more direct impact on society and this led me to the space of user-generated content analysis.
One of my favorite qualities of the brain is that it constantly updates its representation of the world based on new information such that every piece of new information you process forever changes how you will experience every future piece of information. Despite this powerful truth, we are far less vigilant about the content we consume compared to the food we eat, for example. When we founded Barometer, my co-founder, Grant Nelson, and I were on a mission to bring more transparency to the contents of user-generated content so that advertisers and ultimately consumers could consume responsibly.
The other key aspect of my background that contributed to the creation of Barometer is my own, and my cofounders’, international upbringings. I was born and raised in Kharkiv, Ukraine at a time when everybody spoke Russian, and half my family still lives in Ukraine while the other half live in Russia.
Growing up with this dichotomy and having to experience state-sponsored news has given me an unshakable perspective on the importance of free speech and critical thinking while also giving me a clear position on the dangers of censorship. Podcast content, both in its inherently decentralized nature and in its long-form content format that requires critical thinking, achieves a level of free speech that would not be possible in the countries I grew up in.
Podcast advertising is the key way these essential conversations can continue to stay free to the consumers who benefit from learning from these conversations. This is why at Barometer we are committed to using our data to drive the transparency needed to grow advertiser confidence and investment in podcast content.
Can you discuss the significance of being the only independent brand suitability and contextual targeting solution for podcast advertising?
Part of the reason that an independent third party for brand suitability and contextual targeting is necessary for the podcast advertising industry is that there is an inherent conflict of interest between the buy side and the sell side that we believe can be managed through radical transparency. Even though publishers are extremely knowledgeable about their inventory and often do an excellent job curating buys for clients, before Barometer there was no real way for advertisers to trust but verify that their standards are being upheld at scale.
We have all heard of the analogy that publisher-influenced content analysis is like grading one’s own homework. The trust but verify model will ultimately yield stronger trust outcomes between advertisers and publishers. Independence in decision-making is a critical factor in ensuring our data can be trusted. We take great pride in our processes and the knowledge that no relationships or conflicts of interest can drive our analysis and decision-making.
How does Barometer’s independence differentiate itself from other brand suitability and contextual targeting solutions in the podcast advertising industry?
Barometer is the only brand suitability measurement vendor in the space that does not have conflicts of interest with any major shareholders. This allows us to have a truly third-party perspective and keeps us free from unfair influence. Separately from our fiscal independence, we are also an independent player in the industry as an AI frontier technology company, as opposed to being a media company. Our AI expertise stems from our talented team of trained AI engineers hailing from institutions like NASA, the FDA, the Salk Institute, and more.
How does Barometer ensure impartiality and objectivity in providing brand suitability and contextual targeting solutions?
Barometer uses an automated process to consistently evaluate each piece of content according to the exact same criteria. Through this automation, we eliminate the possibility of human biases. By being transparent with the “rubric” we use and by always analyzing each piece of content in the same way, we can ensure both objectivity & impartiality. Another important aspect of ensuring impartiality is avoiding conflicts of interest, which we accomplish by staying independent.
Can you provide more details on how Barometer’s partnership with Katz Digital will help address the gap in podcast brand safety solutions? How does Barometer’s advanced offerings ensure brand suitability standards?
Barometer works with Katz by analyzing all of the inventory they represent (yes all 40,000 shows!). Once the inventory has been processed, we add all of the brand suitability, host intelligence, and contextual targeting data into an interactive, self-service dashboard that the Katz team can use to curate collections that meet clients’ requirements. Partnering with Katz allows us to make a big impact because they work with inventory from many publishers and make it possible for clients to buy that inventory at scale.
As we discussed earlier, brand suitability is in the eye of the beholder, unlike brand safety which is an inherent property of the content itself. We are able to report that 100% of the inventory Katz represents is brand safe, and we then make it possible for the Katz team to use our platform to filter and sort based on brands’ individual suitability standards. It’s so amazing that every brand, and often every campaign, has subtly different suitability standards. The self-service nature of our platform empowers the Katz team to understand and act on the data we are generating about their inventory.
With the podcast industry becoming increasingly fragmented, how will this partnership help maximize revenue and audience reach?
Fragmentation is a huge point of frustration for advertisers, particularly larger brands seeking to buy larger impression volume across premium inventory at more manageable CPMs. Fortunately, Katz is actually an important part of the solution when it comes to helping advertisers overcome the challenges of fragmentation. Our partnership with Katz paves the way for advertisers to be able to simultaneously buy across multiple publishers in a transparent and non-black-box way.
Naturally, when any targeting filters such as contextual targeting or brand suitability filtering are applied, it will narrow down the set of shows that matches all the targeting criteria. This is a catch-22 because, on the one hand, better targeting can result in better performance, but advertisers must also consider the impact of their targeting on reach.
The beauty of our partnership with Katz is that advertisers can broaden out their reach across dozens of publishers and maintain significant reach while also applying their targeting parameters. The focused & intentional targeting results in higher revenue because advertisers pay a small premium to target, but also in a better return on investment for advertisers who are able to maximize reach while ensuring contextual alignment.
Can you discuss the process of how Barometer’s brand-suitability and contextual targeting insights will be integrated into Katz Digital’s media plans?
While I don’t want to give away their secret sauce and the exact processes they are using to curate the perfect inventory for their clients’ media plans, I will share that they are now able to use our self-service platform for this curation. This means that they are able to access dashboards in Barometer that have all of their shows analyzed using our brand suitability and contextual data solutions. They are then able to interact with their inventory in the dashboard using filter sets including the IAB’s Content Taxonomy 3.0 for contextual alignment and the GARM filters for brand suitability. This way they can literally curate the plans in real time.
The coolest part of using the platform for this relates to one of your earlier questions about the tradeoffs between targeting & reach. They are able to instantly see the impact on reach with any targeting decision they make.
For example, if they were to create a subset of inventory that is focused on healthy living and the advertiser told them they’re concerned about too much adult content, they are able to show the advertiser the relative impact on reach if they restrict their tolerance to “medium level” vs “low level” for adult content, and instantly pull up examples to help the advertiser gain comfort and understanding about the differences between these two levels. This instantaneous visual feedback empowers the Katz team to have data-driven conversations with their clients that allow both parties to maximize ROI.
The Katz team is truly doing something very special, both from the point of view of investing in this level of insights for their vast premium inventory and also by empowering advertisers to trust but verify through transparent monitoring solutions.
How will this partnership benefit larger brands investing in podcast advertising who demand the same brand suitability and targeting capabilities as other digital advertising channels?
Historically, podcast advertising has been an incredibly effective channel for performance marketers, but has been a challenge for brand marketers. Fragmentation, perceived challenges of attribution, and lack of inventory transparency are all factors that impact our industry’s ability to grow. We believe that our partnership with Katz, as well as our other ecosystem partners including ArtsAI and Newsguard on the measurement & data sides are all important components of accelerating growth within the podcast marketplace.
We have heard from several large agencies and brands that they would never have considered something like a run-of-network without having access to the ability to monitor and target based on brand suitability preferences. Our partnership with Katz provides the transparency required to address advertiser requirements and makes it possible for advertisers to buy more widely across the ecosystem, rather than cutting entire genres or cherry-picking shows, the current best practices.
There are also numerous studies that have revealed larger advertisers’ fears and biases about brand suitability in podcasting, which can easily be dispelled with data. We believe that through this partnership, and others of its kind, we are investing as an industry in making podcast advertising a more mature channel, equipt with all the data, reporting, and analytics that savvy marketers demand. For better or worse (we think better), digital advertising has empowered advertisers to be more data-driven.
This has also led marketers to demand the data they need to optimize their media spend. We are seeing a lot of signals supporting a data-driven future in podcast advertising based on signals from both our own (cite: Trade Desk/ Tombras/ Orange Theory) and other channels (cite: P&G targeting). We believe that brand suitability and contextual targeting data & insights will soon be table stakes for publishers and advertisers in podcasting, and will open up podcast advertising to the largest brand marketers who have historically either underspent or completely avoided the space altogether.
Lastly, can you share any exciting new developments or upcoming projects for Barometer?
We have been growing & building at an amazing pace, which we believe is a testament to the importance and timeliness of Barometer’s offerings for our industry. We’ve expanded both our engineering and business development teams to ensure we continue to be on the cutting edge of bringing frontier AI methods into podcasting to drive growth for all parties. We closed a fundraise earlier this year and have recently moved into our new offices in Manhattan. We have also been working on some exciting integrations with DSPs to lay the foundation for contextual and brand suitability targeting at scale.
At the IAB Podcast Upfront, we announced an exciting partnership with ArtsAI and two new products we’ve released together. In particular, our AB Daily monitoring product represents an important move in consolidating data from previously disparate information streams: attribution & contextual data, into a “full-stack” implementation. This creates further simplicity for advertisers, reduces complexity, and provides the data required to interpret the ROI of podcast advertising apples to apples with other channels.
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