Podcast data and discovery platform Podchaser has developed a new audience category to help advertisers tailor the reach of their campaigns. It is political skew.
The idea, in Podchaser’s words, is to “offer unprecedented clarity, classifying podcasts by political alignment to help brands focus resources on listeners aligned with their messaging.”
Lest anyone imagine that the intelligence behind this is simplistic — hooking into party registrations, for example — Podchaser sketches out the methodology:
“Podchaser Pro’s political skew data leverages a combination of AI-driven analysis and human verification to determine the political lean of each podcast audience. This multi-layered approach includes the analysis of podcast content, pre-existing media datasets, and learning models, with each data point undergoing rigorous checks to ensure accurate categorization.”
Keywords, topics, and recurring themes play parts in the classifications. Additionally — and getting away from reliance on machine intelligence — the human team at Podchaser cross-checks AI-driven results with manual reviews. The company promises that this step aligns data-sourced results align with industry standards.
The political skew is more nuanced than merely left-right buckets. Tighter categories include neutral/mixed, low left-right, medium left-right, and high left-right.
All this applies to English-speaking podcasts.
Podchaser’s official announcement includes a screenshot of a Power Score results screen. It is too low-rez to reproduce here, and all of its examples are in the Neutral category, making it less interesting. But the lengthy announcement has other interests, and can be seen HERE.
