By ; Rasha Hagag
In its first product launch since being acquired by wealth AI leader BridgeWise in February, Context Analytics now enables institutional investors to quantify market sentiment in podcasts using ticker-mapped, finance-tuned scores.
CHICAGO, IL — Context Analytics, a BridgeWise company, today launched its Podcast Sentiment Analysis Feed, the first quantitative-grade sentiment analysis product built from financial and business podcast content.
The new feed delivers finance-tuned, ticker-level sentiment scores derived from high-accuracy audio transcriptions, giving quantitative traders and systematic investors access to a measurable signal channel that has until now remained entirely unquantified.
Bridging the Final Gap in Unstructured Data Coverage
Context Analytics already quantifies what investors are reading (Quantitative News Feed), disclosing (Corporate Filings Intelligence), and saying (Social Media Sentiment Feeds - from X, StockTwits, and Reddit) via the SentimentWise solution. The Podcast Sentiment Feed adds the missing fourth channel to this powerful solution set: what investors are listening to.
With more than 4.5 million podcasts worldwide and nearly 600 million global listeners, podcasts have become one of the most influential, yet least-measured media formats in finance.
“Investors and industry experts have been creating and consuming podcasts for years. There is valuable market insight locked in that audio, but until now, the industry lacked the infrastructure to turn it into measurable data," said Joe Gits, Context Analytics Managing Director, North America. “We’re excited to provide reliable sentiment signals from this increasingly critical media channel.”
According to Edison Research, 55% of Americans are now monthly podcast consumers, with the medium quickly becoming a highly influential educational channel. A Pew Research poll found that 88% of these listeners tune in specifically to learn. With the rapid growth of financial and business shows, quantifying this channel's sentiment is critical for a complete view of capital markets.
How It Works
The Podcast Sentiment Analysis Feed ingests financial, business, and news podcasts from a broad, continuously expanding universe of over 3 million podcasts. Audio is transcribed using automatic speech recognition infrastructure, then processed through Context Analytics’ proven NLP sentiment pipeline. Each transcript is entity-tagged at the company and ticker level, producing two structured outputs: quantitative sentiment scores and metrics for systematic trading workflows, alongside AI-generated summaries capturing detailed company mentions and podcast context for qualitative research.
Early Signal Performance
Preliminary quintile analysis of the Podcast Sentiment Analysis Feed shows a ~10% cumulative return spread between the most positively and most negatively discussed companies over a ~10 year backtest period.
The Podcast Sentiment Analysis Feed is available now for trial access, covering U.S. equities. Data is delivered via JSON, API, or FTP to integrate directly into existing workflows. Qualified institutions can request a dataset demo and walkthrough by visiting https://www.contextanalytics-
