Local radio ad intelligence for agency prospecting

Executive Summary

Local marketers lack an easy feed of which businesses are running radio ads. Build an audio monitoring + matching service that reveals advertisers by station, frequency, and cadence so agencies can target lookalike local advertisers. Advances in low-cost cloud audio processing and robust audio fingerprinting models make continuous monitoring of many radio streams feasible at scale. The reddit source and stage 1 validation flagged monthly recurrence and budget-owner evidence, showing agencies will value recent, recurring ad signals for outreach. Meanwhile, incumbent ad-intel providers focus on national TV and digital, leaving local radio undercovered; this gap plus the steady cadence of local radio buys creates a timely niche. Combine automated audio fingerprinting and schedule scraping to create a continuous, local-first dataset of radio ad occurrences and advertiser identities. The product leverages a proprietary dataset of matched audio-to-advertiser events per station and market, sold as a searchable feed and API to agencies. The source idea explicitly cites recurring local buys - e.g., "Lawyer X and Y are advertising for four months consistently" - which supports a product that surfaces repeat advertisers and campaign cadence for prospecting. Because radio is hyperlocal, a focused dataset across many small markets can become a unique data moat that mainstream ad intelligence vendors under-index.