Podscribe's dashboard can track the full delivery and impact of episodic sponsorships (i.e baked-in ads), including additional exposure from simulcasting podcasts on YouTube, which is an increasingly common practice. This information is valuable for advertisers who want to understand the full effectiveness of their sponsorships.
Full Delivery of your sponsorships
The Podscribe dashboard offers a comprehensive overview of your sponsorship's delivery by automatically matching the YouTube episodes with their corresponding podcast episodes. Leveraging the YouTube API and the Podscribe prefix or pixel, Podscribe gathers real-time YouTube views and podcast downloads for each matched episode. This integrated data provides a unified perspective on the total reach of an advertiser's embedded ads.
Total performance measurement
Podscribe models conversions for simulcast campaigns based on the podcast version's performance. Standard attribution is run on the podcast episode, and the resulting conversion rate is applied to the YouTube video's view count.
As YouTube’s algorithm promotes videos based on video characteristics and viewership trends, it is much more likely to have a YouTube video go viral than to have a podcast episode go viral. Podscribe attempts to smooth those types of spikes by taking a 9-day rolling average of the modeling coefficient each day.
Flexible YouTube Modeling
To give advertisers more control, Podscribe allows you to adjust the weighting of YouTube views relative to audio downloads directly in your dashboard.
- Navigate to
Overview > Attribution Settings
- Update the assumption for how a YouTube view compares to an RSS download
- Apply the setting to your simulcast campaigns
By default, Podscribe treats one YouTube view as equal to one RSS download. But because downloads and views have different qualities, you may decide to weight YouTube views differently based on your own performance data. For example, some marketers apply a slightly higher multiplier to reflect the broader visibility of video impressions.
A note on YouTube modeling
Many consider applying the audio conversation rate to video as conservative, since downloads & views have different qualities. Given more data, we may consider adjusting to perhaps use a 1.25x the audio conversion rate on YouTube. For now though, this solution lets marketers view on one, real-time automated dashboard their simulcast performance just as they’d view any ordinary audio campaign.
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