Quantifying the true (positive) impact of iOS 17
Introduction
The iOS 17 update has introduced significant shifts in podcast consumption and advertisement delivery. Over the past 12 months and coming out of Q4 there have been notable improvements in not only general podcast advertising performance but the performance of specifically impression-based campaigns!
These enhancements are largely due to iOS17 and the reduction of "phantom impressions," a term coined by Glenn Rubenstein (CEO, ADOPTER Media) to describe impressions from automated downloads that did not equate to actual listener engagement.
Podscribe's latest quantitative findings (Q4 PPB Report) shed light on the substantial improvements in the space and for the first time concrete evidence of these positive changes.
“The iOS 17 adjustment has been challenging for publishers. But one positive impact of iOS 17 is that by actualizing numbers we get closer to a true north of listenership that other channels still do not have.”
“For the first time, we’re witnessing the positive change iOS 17 had on the podcast space, particularly seeing improved confidence in impression-based buys and DAI”
The Impact of iOS 17 on Podcast Advertising
Before the iOS 17 update, Apple Podcasts automatically downloaded all missed episodes of a subscribed podcast whenever a user resumed listening after a break. These automated downloads were factored into the show’s impression and download counts despite 10-30% of them never being listened to by a user.
The recent Apple podcast updates via iOS 17 changed this (read more), leading to a significant drop in these auto-downloads. For “impression-based” buys on back-catalogs this has led to significant performance improvements.
Impression vs Episodic Buys
The distinction between “impression” and “episodic” campaigns (more commonly referred to as DAI and "baked-in") has been a topic of considerable interest and analysis within the industry. The latest data from Podscribe’s Q4 report demonstrates the evolving dynamics between these two advertisement strategies, especially in light of the iOS 17 update.
Episodic Performance, Q4
Over the last 12 months, episodic/baked-in campaigns sustained their lead in terms of achieving a higher visitor rate when compared to their DAI/impression-based ad counterparts. This traditional form of advertisement, where ads are embedded into the podcast content, has historically shown a strong performance, primarily due to its seamless integration with the podcast content and the perceived endorsement by the podcast host. However, we are starting to see that change…
Impression-Based Ad Buying: An Ascending Trajectory
Despite the historically stronger performance of episodic and baked-in ads, impression-based campaigns have demonstrated a significant improvement since Q3. In Q4, Podscribe not only identified that the performance gap between baked-in ads and DAI has notably narrowed: In Q3 baked-in/episodic ads outperformed impression-based ads by 35% while in Q4, baked-in/episodic only performed 21% better than impression-based ads!
But quarter over quarter impression-based buys saw a +30% increase in performance!
Specifically in their effectiveness at driving listeners to site!
This is noteworthy, considering the inherent challenges faced by DAI and impression-based ads when trying to match the levels of listener engagement baked-in ads offer.
The adaptability of DAI, enabling ads to be inserted dynamically based on listener demographics or content relevancy, cannot be overlooked and is continuing to show its potential benefits in engagement, cost-efficiency, and performance!
The improvements in impression-based performance are largely attributed to the iOS 17 updates. The elimination of these "phantom impressions" has leveled the playing field for impression-based buying, allowing for a more accurate measurement of listener engagement and ad performance.
We are now, for the first time, tangibly seeing that the decrease in automated downloads not only benefited the space but has specifically improved the performance of “impression-based” and back-of-catalog buys. With a cleaner, more accurate dataset, DAI and impression-based campaigns are now set up to demonstrate their real value and efficiency in reaching, engaging, and converting podcast audiences.
Opportunity for Podcast Advertisers
The shift in Impression-based ad performance post-iOS 17 offers a silver lining for podcast advertisers. With fewer but more targeted impressions across shows, advertisers can expect not only a higher engagement rate from their campaigns but higher performance in bottom-of-funnel metrics as well. This change underscores the importance of trusted, third-party verification in ensuring the effectiveness of ad placements and verified “downloads”.
Conclusion
For advertisers, the evolving landscape of podcast advertising signaled by these Q4 findings presents new opportunities. While episodic and baked-in ads continue to offer the advantage of a more integrated and host-endorsed advertisement, the improving efficacy of impression-based ads cannot be overlooked. The flexibility of dynamic insertion, combined with the removal of misleading download data, suggests that dynamically inserted ads are becoming increasingly competitive in achieving meaningful listener engagement and driving conversions.
This trend should encourage advertisers to reassess their strategies, potentially integrating a mix of episodic and impression-based ads to leverage the strengths of both approaches.
As the podcast industry continues to evolve, particularly with technological advancements and changes in consumption behavior, the ongoing analysis of ad performance metrics will be crucial in informing future advertising decisions.
FAQ
Q: How has iOS 17 affected podcast ad delivery? A: The update has led to a decrease in about 10-30% of downloads.
Q: How has iOS 17 affected DAI performance? A: By reducing automated downloads, iOS 17 has eliminated non-engaged impressions and the industry has seen an increase in DAI performance over Q4 compared to Q3.
Q: What are "phantom impressions"? A: Impressions counted from automated downloads that were not actually listened to, thus not contributing to real engagement or conversion.
Q: How does removing these impressions affect conversion rates? A: With the removal of phantom impressions, conversion rates for DAI campaigns are calculated over a more accurate base, showcasing higher efficiency.