Hey, it’s Arvid.

We’ve shipped a few things over the past few weeks that I’m genuinely excited about. Each one solves a problem that’s been bugging me (and probably you) for a while.

Let’s get into it.

1. IAB categories that reflect reality, not wishful thinking

Here’s a dirty secret about podcast categorization: most shows pick their own categories when they submit to Apple or Spotify. A crypto bro calling his show “Business” doesn’t make it a business podcast.

We now analyze the actual content of every episode and assign IAB (Interactive Advertising Bureau) categories based on what’s really being discussed.

Why this matters:

- For sponsorship buyers: You can finally filter by true content category, not self-reported labels. That “Business” podcast that’s actually 90% sports betting commentary? You’ll know.

- For audience research: IAB categories are the industry standard for ad targeting. Now you can find podcasts that genuinely reach your target demographic.

- For competitive analysis: See what categories your competitors actually show up in—not where they think they belong.

2. Sentiment analysis on every topic mention

When someone mentions your brand, your competitor, or your industry on a podcast, the words matter. But so does the tone.

We now track sentiment for every topic and entity we extract. You’ll see whether a mention is positive, negative, or neutral—and you can filter your results accordingly.

A few ways to use this:

- Brand monitoring: Catch negative sentiment early, before it becomes a PR problem. Or find your biggest advocates and amplify them.

- Competitive intelligence: Are people frustrated with your competitor’s product? That’s market research you can act on.

- Trend analysis: Track how sentiment shifts over time. Is the conversation around AI in your industry getting more skeptical? More optimistic?

This shows up in your dashboard and in the API, so you can build sentiment tracking into your existing workflows.

3. Podscan now works with AI agents

This is the big one.

We’ve built an MCP (Model Context Protocol) integration that lets you connect Podscan directly to Claude, ChatGPT, and other AI assistants.

What does that mean in practice? You can now ask your AI agent things like: - “Find podcasts where our CEO would be a good guest fit” - “What are people saying about [competitor] in tech podcasts this month?” - “Create a list of business podcasts that discussed supply chain issues last quarter.”

And it will actually search our database of 4+ million podcasts, pull real data, and give you answers grounded in actual podcast content.

If you’re building agentic workflows, automating research, or just want to query podcast data conversationally—this is for you.

Learn more about MCP integration → https://podscan.fm/docs/mcp-server​

All of this is live now

These features are available in your dashboard and via the API. If you’re on a plan with API access, the new IAB categories and sentiment data are already flowing through your existing endpoints.

Questions about any of this? Just reply—I read every email, and I’m happy to walk you through how these features might fit your specific use case.

Cheers, Arvid

P.S. The MCP integration is particularly powerful if you’re already using AI assistants for research. Instead of copying data between Podscan and your chat window, your agent can just… ask us directly. It’s the kind of workflow improvement that sounds small until you try it.