When a federal agency published an interim rule affecting a major industry, the public comments flooded in. Thousands of them. Drivers, carriers, fleet managers, advocacy groups, all reacting in real time to a regulation that would directly affect their businesses and livelihoods.
The interest was already there. Coverage was already happening. The question was: is there something useful inside all that reaction, and can we get to it fast enough to matter?
That’s where AI came in, but not to write the pitch….to read the pile.
In this solo episode, I walk through a real campaign where we used AI sentiment analysis to sort through a massive pool of public comments, surface the patterns, and build a data-driven story that trade journalists actually wanted. I also share the journalist response that made the whole thing worth talking about and why timing mattered more than the technology every step of the way.
I also get into something that doesn’t get enough attention: how PR and SEO need to be working together before the pitch ever goes out.
What This Episode Covers
The setup. A live federal regulation, an already-active news cycle, and thousands of public comments sitting in the Federal Register waiting to be useful to someone.
The approach. How AI sentiment analysis helped group reactions, surface patterns, and give shape to something messy — fast enough for the story to still be timely.
The pitch. What we led with, why we led with it, and why the methodology was the footnote, not the headline.
The response. What a skeptical executive editor said when he received it — and what that tells you about what journalists actually care about.
The PR and SEO connection. Why the campaign worked partly because the content foundation was already in place, and how to make sure your SEO team and your PR strategy are actually talking to each other.
Listen on Apple Podcasts or Spotify