Sullivan-Get With The Program-Get With The Program Selected Papers of #AoIR2023: The 24th Annual Conference of the Association of Internet Researchers Philadelphia, PA, USA / 18-21 Oct 2023 GET WITH THE PROGRAM: PROGRAMMATIC ADVERTISING AND THE DATAFICATION OF PODCAST AUDIENCES John L. Sullivan Muhlenberg College The podcasting landscape has been reshaped in the past several years by acquisitions and mergers among players in the industry. Major platform services like Spotify, SiriusXM, iHeartMedia, Google, and Apple have all attempted to more closely bind consumers to their proprietary services, threatening the open architecture of distribution via RSS (Morris, 2021; Sullivan, 2019). While control and monetization of intellectual property is one key driver of platformization in podcasting, another key institutional shift is being accelerated by these changes: the datafication of the audience. In short, datafication involves the quantification of human activity to enable surveillance, prediction, and mass customization of advertising. The process of audience datafication is being driven largely by platform services, which leverage their “privileged access” to all user interactions on the platform to both extract and monetize these raw data (Srnicek, 2016, p. 44). This drive to extract, sort, analyze and commodify user-generated data fuels an ever-increasing drive by platforms to expand their access to even more specific data about audiences’ media consumption habits, also known as “surveillance advertising” (Crain, 2021). In this paper, I explore one significant impact of widescale platformization within podcasting: the emergence of programmatic advertising markets. By essentially “listening in” to industry discourses (Corrigan, 2018) about podcast advertising (in podcasts and in the Podcast Upfront presentations from Spring 2022), this essay outlines the importance of platform-to-platform data transactions and highlights the resulting shifts in podcasting: away from the intimate, relationship-driven ethos of the medium and toward a quantitative, surveillance-driven ecosystem. Programmatic Advertising in Podcasting Podcast advertising has developed significantly since 2015, with companies developing platforms and services to automate the process of buying and selling advertising across a huge array of shows, often directed by AI-driven algorithms with little direct human intervention. The key innovation in podcast advertising has been the Suggested Citation (APA): Sullivan, J. L. (2023, October). Get With The Program: Programmatic Advertising And The Datafication Of Podcast Audiences. Paper presented at AoIR2023: The 24th Annual Conference of the Association of Internet Researchers. Philadelphia, PA, USA: AoIR. Retrieved from http://spir.aoir.org. emergence of programmatic advertising. Programmatic advertising involves “the automated serving of digital ads in real time based on individual ad impression opportunities” (Busch, 2016, p. 8). In essence, programmatic approaches automate the process of buying and selling digital advertising by creating ad “exchanges”, or digital marketplaces that allow publishers and advertisers “buy and sell advertising space, often through real-time bidding, most often display, video and mobile ad inventory. Agencies use Demand-Side Platforms (or DSPs), software programs used to purchase advertising in an automated fashion, to track money spent, ad prices and placement, audience data and metrics, and targeted audiences” (Watkins, 2019, p. 13). Programmatic advertising offers a number of advantages over traditional advertising in the sense that it is targeted to specific consumers at a granular level, it can be deployed in real time (e.g., dynamically delivered to a consumer when they access a particular type of digital content), and automated via algorithms (Busch, 2016). Both Facebook and Google were early adopters of programmatic advertising by creating their own “Supply-Side Platforms” (SSPs) of user-generated content, which were then matched with DSPs that enabled advertisers to upload their ad messages intended for specific consumer targets. Algorithms then place ads in front of specific consumers in real time, either as the result of specific text or keyword markers (called “prospecting”) or when a specific consumer demographic is identified by the SSP (called “retargeting”) (Mills et al., 2019). For podcasting, the introduction of programmatic advertising has meant that creators and publishers can provide their content or RSS feed to an SSP and make that content available to any DSP that would like to run an audio advertisement within their podcast. The key element to the success of this “just in time” advertising strategy is the deployment of dynamic advertising insertion (DAI). A dynamically inserted ad is “piece of audio (referred to as the ‘creative’ from here) that is recorded and produced separately from a podcast episode. The creative is ‘stitched’ into the podcast episode file at the time of download when the ad targeting conditions are met” (Resler, 2020). DAI enables a whole new range of capabilities for podcast advertising, such as the ability to place advertisements instantly across hundreds or thousands of podcast episodes, to place limits or caps on either the time range for a particular campaign (30 days long, for example) or the number of times the ad is played (to reduce advertising load on listeners), or even to offer slightly different versions of the same campaign to the same listener across multiple podcasts (Barletta, 2022). Programmatic Consequences in Podcasting: Centralization, Surveillance, and Brand Safety Programmatic advertising and DAI are placing the platforms at the strategic center of the industry because these players have access to vast quantities of audio content (“inventory”) that they have made available for programmatic advertisers. Despite the convenience and the scalability of programmatic advertising, however, some in the industry are worried that the relentless monetization of podcasts will lead to more ad “clutter”, higher ad loads for consumers, and lower quality ads similar to those found on commercial broadcast radio (Guaglione, 2022). Along with the industry concerns, there are consumer concerns as well, especially since the dynamic ad insertion process requires extensive surveillance of listener behavior, such as tracking IP addresses, app usage, and listening of specific podcasts and moments within those podcasts. These all hold the potential to disrupt the experience of intimacy and trust between the podcaster and the audience. Programmatic approaches have the potential to indirectly alter or censor forms of creative production as well. Since programmatic advertisers no longer have a personal connection with the individual podcaster (and indeed may be wholly unfamiliar with the content of their show), buying ad impressions in bulk via a DSP may result in some advertisements placed opposite “controversial” content. This creates a concern for what advertisers call brand safety. As Bishop explores in her analysis of social media influencer tools on sites like Facebook and Instagram, brand safety refers to “a positive reproduction of a brand’s ideals, an avoidance of controversy, and a circumvention of sex, violence, and profanity” (Bishop, 2021, p. 4). Much like the social media influencers discussed by Bishop, podcast advertisers have also recently expressed concern about their ability to avoid controversial content as an environment for their programmatic ad buys. This has fueled heavy industry investment in AI-driven language processing technology for actively scanning podcast content for objectionable words, topics, and issues, essentially expanding the scope of industry surveillance to include podcast content. Thus, the emergence of platforms, advertising supply side platforms, and dynamic advertising insertion have not only rationalized the buying and selling of advertising across the industry, but these shifts have opened new vistas of podcast content surveillance and potential censorship as well. This analysis of programmatic advertising also highlights the importance of understanding platform-to-platform dynamics when considering the impacts of platforms on online cultural production and distribution. References Barletta, B. (2022, September 13). Programmatic Advertising for Buyers. Sounds Profitable. https://soundsprofitable.com/update/programmatic-ads-for-buyers Bishop, S. (2021). Influencer Management Tools: Algorithmic Cultures, Brand Safety, and Bias. Social Media + Society, 7(1), 205630512110030. https://doi.org/10.1177/20563051211003066 Busch, O. (2016). The Programmatic Advertising Principle. In O. Busch (Ed.), Programmatic Advertising: The Successful Transformation to Automated, Data- Driven Marketing in Real-Time (1st edition, pp. 3–16). Springer. Corrigan, T. F. (2018). Making Implicit Methods Explicit: Trade Press Analysis in the Political Economy of Communication. International Journal of Communication, 12(0), 22. Crain, M. (2021). Profit over privacy: How surveillance advertising conquered the Internet. University of Minnesota Press. Guaglione, S. (2022, March 4). Why podcast agencies are warning about the move to dynamically-inserted ads. Digiday. https://digiday.com/media/why-podcast- agencies-are-warning-about-the-move-to-dynamically-inserted-ads/ Mills, A. J., Pitt, C., & Ferguson, S. L. (2019). 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