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Hours spent searching
Running a campaign for an artist means mentions come from every direction - TikTok comments, Reddit threads, podcast asides, blog reviews, tweets. Trying to make sense of all the noise could take hours each week, and even then, things slip through. Once the data is gathered, it still has to be pulled together - consolidated in one place, analysed for recurring themes across platforms, and connected to actual campaign performance.
A system that listens, filters, and connects
We built a media monitoring pipeline that tracks mentions across social platforms, podcasts, news outlets, blogs, forums, and YouTube. AI filters out false positives - posts that mention the artist's name but aren't actually about them. Coverage is automatically clustered by topic, so reactions to a new single sit separately from tour announcements or festival appearances. Alongside the volume and sentiment analysis, AI surfaces the things a human would spot if they had time to read everything: an interesting tastemaker posting about the band, a podcast host worth reaching out to, coverage that hints at a collaboration opportunity. All of this media data is then mapped against campaign metrics - streams, merch sales, mailing list signups - with the campaign calendar providing context about what happened when. The result is a weekly insights report, generated as a PDF and emailed to the team, with data also pulled into a dashboard that visualises everything in one place.
From scattered signals to clear picture
ATC's team now gets a weekly summary that tells them not just what's being said, but what it means for the campaign. They can see which moments drove results, spot opportunities they'd have missed, and make decisions based on the full picture rather than fragments.
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