Advertisers have been procrastinating ever since Google first announced back in 2020 that third-party cookies would be phased out: It is 2024, and according to WSJ the 6-billion online ad industry still isn’t ready. Given that Chrome accounts for a staggering 65% of all internet traffic worldwide, this will have a big impact on marketers, advertisers, and everyday users. A recent survey by Adobe reports that across all countries, 75 percent of marketing and CX leaders still rely heavily on third-party cookies and at least 16% deem the consequences of the cookie-pocalypse as “devastating”.
Google has announced that cookies will be phased out entirely of the Chrome browser during the second half of 2024, which will impact the greatest revenue-generating period of the year. Back in 2021, Forbes predicted that the podcast advertising market could be a big winner with the demise of cookies – partly due to the contextual and behavior-based targeting technologies available for audio ads – and the timing of Google’s decision might cause the perfect storm for podcasts.
Cookies are small pieces of data stored on users' devices by websites they visit and represent the epitome of digital advertising for marketers. They help track users’ activity across different apps and websites, storing information like account information and purchasing behavior. First-party cookies create a better experience while browsing, logging you in automatically, remembering the items in your online shopping cart, and recommending products that you might be interested in. Third-party cookies, in return, are used by advertisers to track user’s browsing history and activities to present them with personalized advertising.
So what is the problem with cookies, then? Third-party cookies, or cookies that are collected by ad servers as opposed to by the website, have been subject to privacy concerns, particularly regarding the practice of user profiling and user tracking without consent. Have you ever noticed, for example, that your phone is listening to your conversations and serving you targeted ads immediately after you talk about something? You can thank cookies for that.
Cookie files aren’t harmful by nature, but if they end up in the wrong hands, that data can be stolen and used to commit cybercrimes, known as cookie hijacking. The biggest threat that cookies pose to users is related to the use of private information and how your personal data is shared online. Concerns are so big that governments have made consent and full disclosure mandatory, Apple and Mozilla disabled third-party tracking in 2020, and the only left standing is Google Chrome, with more than 60% of browser users, and it will completely phase out third-party cookies in 2024.
Podcasts have emerged as a powerhouse medium for brands to connect with their target audiences, and with millions of listeners tuning in regularly, podcast advertising offers a unique opportunity for brands to reach engaged audiences in a highly targeted manner. However, one of the challenges that marketers face in podcast advertising is measuring the effectiveness of their campaigns when compared to other media that rely on third-party cookies to track users.
At present, podcast advertising is seen as an inferior form of digital advertising, since cookies track individual devices and podcast ads track all devices in the same network through IP addresses. However, after third-party cookies are phased out on all forms of advertising, it will level the playing field for podcast advertising, as advertisers will no longer be able to track unique devices for targeted advertising.
Podcast advertising is one of the few media out there that naturally don’t rely on cookies. Its underlying technology, the RSS feed, is a form of cookieless technology as It is intended for public consumption and distribution with no need for personalized content delivery or tracking user behavior. The fact that RSS feeds are cookieless also ensures they are compatible with a wide range of applications and prioritizes efficient delivery. But this has always been regarded as a major drawback for podcast advertising, limiting the use of podcast advertising as part of a multichannel campaign, since there is no way to track an individual device.
The demise of cookies will force advertisers to look at new solutions for online advertising, which are currently facing a Sliding Doors moment, where transitioning early as opposed to being late will be key for the future success of agencies. Disruption will be coming in the form of technologies based on contextual targeting, artificial intelligence, machine learning, and others. This change will level the playing field for podcast advertising when it comes to measurement capability and adoption, as marketers will need to keep track of their customers without compromising their personal data.
AdsWizz, a leading technology in contextual podcast advertising specializing in audio applications is at the forefront of the innovation in audio advertising. AdsWizz uses predictive audience algorithms and AI transcription technology to reach audiences in a privacy-friendly way based on content preferences, rather than purchasing behavior and browsing history. Contextual targeting also allows advertisers to perform keyword targeting, which allows advertisers to target based on the conversation topic, rather than the podcast or genre.
Acast is also looking at the death of cookies as an area of opportunity for the industry. The company which pioneered dynamic ad insertion for podcasts, is also preparing to serve cookieless advertisers through an identity graph tailored for podcasting. Identity graph allows first-party data from advertisers to be integrated into the Acast marketplace, allowing for audience matching and improved targeting. An Identity Graph relates first-party data from users across devices and helps businesses personalize their advertisements.
So how do you measure and define success in a podcast campaign without cookies?
One of the pitfalls for advertisers in the podcast industry is that only 49% trust their capacity to measure ROI in podcast advertising, which is the lowest level of trust among all digital advertising channels. Furthermore, the study by Nielsen points out that only 17% of the global market believes podcast advertising is extremely effective. Despite this, 54% of marketers globally plan to raise their spending on podcast advertising during 2024. In order to make the transition easier for advertisers into the cookie-pocalypse, we need to find clear guidelines on how to do the best possible advertising in what is going to be a much more fragmented experience for marketers. Enter podcast attribution methods – the cookieless tools and techniques that help marketers track and measure the impact of their podcast advertising efforts.
💡A podcast tracking pixel, for instance, allows you to track ad conversions across different devices and does not store a file in the user’s browser, as its sole intention is to track activity. Pixels have been used in podcast advertising for a few years and work best with dynamic insertion (ads that are automatically and programmatically inserted into podcast episodes), allowing them to track impressions – if somebody actually listened to the audio ad – and engagements in real-time.
A pixel, also known as a tracking pixel or web beacon, is a small, transparent image embedded in a webpage or digital advertisement and its primary function is to track user interactions and provide data to advertisers or website owners. Pixels work by loading when a user visits a webpage or interacts with an ad, sending information back to the server and enabling the tracking of actions such as clicks, conversions, and engagements.
In podcast advertising, attribution pixels, exposure pixels, and conversion pixels can be included in the RSS feed and accompanying web pages or show notes. When listeners visit these pages after hearing a podcast ad, the pixel records their activity, providing valuable insights into the effectiveness of the campaign. This flexibility allows advertisers to track user behavior effectively while mitigating some of the privacy concerns associated with cookies.
Vanity URLs are customized website addresses that are easily remembered and closely associated with a specific campaign or brand. In podcast advertising, advertisers often include vanity URLs in their ad scripts, encouraging listeners to visit a specific webpage for more information or to redeem an offer.
Through vanity URLs, advertisers partner with podcast hosts or networks on an affiliate basis, tracking referrals and conversions through unique affiliate links. They offer several advantages as an attribution method, as they are easy to track and provide direct insight into listener behavior. Additionally, they offer a seamless user experience, as listeners can easily recall and type the URL into their browser.
Similar to Vanity URLs, promo codes are another popular attribution method in podcast advertising. Advertisers provide unique codes that listeners can use to redeem special offers or discounts when making a purchase during checkout. By tracking the usage of these codes, advertisers can directly attribute conversions and sales to their podcast advertising efforts.
Promo codes offer a tangible incentive for listeners to engage with the advertised product or service, making them an effective attribution method. Additionally, they provide valuable data on conversion rates and ROI, allowing advertisers to optimize their campaigns for better results. However, promo codes require listeners to take an extra step to redeem the offer, which may result in lower conversion rates compared to other attribution methods.
Advertisers collect feedback from listeners through surveys or feedback forms to gauge the impact of their podcast ads. Surveys are often conducted by ad results companies in order to measure the effectiveness of a campaign in the form of brand lift studies that compare an exposed group to a control group of listeners to identify key performance indicators such as awareness, brand recall, and consideration.
Surveys can also often be included during the checkout or sign-up process of a website in the form of a “How did you hear about us?” question, and tools like Spotify for Podcasters also allow you to add polls that can be answered directly by listeners on its platform.
Spotify, through its streaming-powered tools, allows you to create clickable ads on podcasts that are streamed through Spotify. This allows you to track clicks directly on the Megaphone hosting platform. This tool is currently being tested with a list of selected publishers and it’s present in Spotify’s internal campaigns, but this functionality and all of Megaphone’s streaming-powered tools are planned to be released to the wider public in the future.
Measurement services like Magellan AI and Veritonic provide the golden standard for measuring ROAS for campaigns, and provide these services at a fractional cost of the CPM of the campaign you are measuring, which makes it very cost-effective. Veritonic is commonly associated with larger programmatic campaigns and provides services directly to advertisers, but companies like Podscribe and Spotify Ad Analytics (formerly Podsights) provide similar services for independent publishers who are working alongside advertisers on individual campaigns. For podcasters looking to grow their audiences, Chartable provides solutions for measuring podcast-to-podcast audio ads and Voxalyze’s solution integrates other forms of media as well to know what’s driving downloads.
In conclusion: Targeting and attribution are better when you add more signals
Contextual targeting, powered by machine learning and AI is driving podcasts’ growth as one of the top up-and-coming media for digital advertisers, allowing advertisers to reach highly-targeted audiences in a privacy-friendly way. Furthermore, the demise of cookies and the continued evolution of audio ad technology will only help to accelerate the medium’s adoption by mainstream ad agencies.
The adoption of best practices and the improvement of attribution methods play a crucial role in helping marketers measure the effectiveness of their podcast advertising campaigns. While each method has its strengths and limitations, a combination of multiple attribution methods can provide a more comprehensive understanding of campaign performance. By leveraging tracking pixels, vanity URLs, promo codes, and other attribution methods, marketers can optimize their podcast advertising efforts and drive meaningful results in this rapidly growing medium.
Podcasters' & publishers' willingness to insert pixels is a key factor in the medium's evolution as a reliable source of performance data for marketers. For best results, it is important to work with a dedicated podcast agency that knows how to execute the campaigns and interpret the results. If you’d like to learn more about podcast advertising and explore ways to integrate it into your multichannel marketing efforts, reach out to Genuina Media. We are a podcast ad agency specializing in Hispanic audiences working alongside publishers and attribution experts to execute data-driven performance campaigns and provide valuable insights to advertisers and brands.
Resources:
Google Is Finally Killing Cookies. Advertisers Still Aren’t Ready. - WSJ
Google shares update on next step toward phasing out third-party cookies in Chrome
Podcasts Could Be A Big Winner With The Demise Of Cookies
Privacy Issues for Computer Cookies
Why is Data Privacy Important for Your Future? | All About Cookies
How to stop your phone listening to you [+Video] | NordVPN
Podcast Contextual Targeting and Predictive Audiences | IAB UK
Acast launches keyword targeting tool for podcast advertisers
The Death of Third-Party Cookies and Opportunity in Podcast Advertising
What Is an Identity Graph? [The Plain-English Guide]
Tracking pixel vs cookie explained (and why it should matter to you)
The ultimate guide to podcast attribution
Clickable Promos | Megaphone Help Center
Pixel-based attribution | Magellan AI - Podcast advertising analytics
SmartPromos - Podcast-to-Podcast ad attribution - Chartable