Executive Summary

Many PR agencies, publishers, media-monitoring firms and large enterprises currently rely on show notes, manual tracking, or keyword searches to capture podcast guest appearances, leaving them with poor attribution and missed exposures across thousands of new episodes each month; this is a clear pain for roughly 100,000 potential buyers that make up an addressable market estimated at $4.0B (100,000 organizations x $40K ACV). The consequence is that teams cannot measure per-guest ROI or automate alerts without costly audits and manual verification. A viable product would be an enterprise SaaS pipeline that ingests raw audio, runs modern ASR plus speaker embeddings, extracts and disambiguates named entities, and resolves voice and name mentions to canonical profiles (CRM/LinkedIn) with time‑stamped, confidence-scored records and APIs for integration and reporting. Offerings should include batch retroactive indexing, near-real-time alerts, a human-in-the-loop verification tier for SLAs, and export connectors to existing PR and analytics stacks. This market looks attractive now because three converging trends lower both the technical and commercial barriers: podcast proliferation increases the discovery burden, speech AI (ASR and speaker-id embeddings) has materially improved detection accuracy, and buyers expect per-guest attribution rather than show-level vanity metrics; those factors are reflected in a market score of 88/100 and revenue potential of 82/100, with competition assessed as medium. The $40K ACV profile supports enterprise sales motion and pilot budgets if accuracy and workflow fit are demonstrated. To differentiate you must optimize for precision and verifiable confidence (not just recall), combine audio-based detection with entity resolution to canonical IDs, and offer an enterprise-grade human-verified tier plus privacy/compliance assurances and publisher partnerships for transcripts. Be honest about challenges: noisy recordings, multilingual and overlapping speech, limited labeled training data, and the trust hurdle with enterprise buyers will all require upfront investment in models, evaluation datasets, and pilot customers before scaling.

Market Opportunity

Detecting podcast guest appearances reliably using audio + entity resolution targets a $4.0B = 100,000 organizations (PR agencies, publishers, media-monitoring firms, large enterprises) x $40K ACV total addressable market with medium saturation and a year-over-year growth rate of 15-25% (driven by podcast ad market growth, enterprise demand for audio monitoring, and AI tooling adoption).

Key trends driving demand: Podcast proliferation -- More shows/episodes increase the discovery burden and create demand for reliable guest-tracking.; Improved speech AI -- Better ASR and speaker embeddings enable higher-precision guest identification across noisy audio.; PR measurement sophistication -- Firms want per-guest ROI and attribution, not just show-level metrics.; Third-party indexing opportunities -- Platforms limit access, so neutral indexers can capture enterprise demand..

Key competitors include Listen Notes, Podchaser, Descript, Chartable, Enterprise media monitors (Cision / Meltwater) — adjacent.

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Detecting podcast guest appearances reliably using audio + entity resolution

Executive Summary

Market Validation

Market Opportunity

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