Speaker 1: Hey, what's up everybody, Finn here. I want to do a tutorial on one of my favorite podcast databases out there. It's called Podchaser. And what differentiates Podchaser from all the other podcast search engines out there like Spotify, Google, Apple, et cetera, is the ability to filter results beyond just searching for specific terms. So let's do an example here. Let's just for the sake of this tutorial, assume that I am a marketer at a B2B software company and I am interested in finding podcasts in the B2B marketing space. I can just type that head term here into the search bar, click on view all podcast results. And initially here, it's going to return shows in a way that's no different from the other search engines. But what's cool and what makes Podchaser different is this add filters option, which I'll click on. And there's a number of different filters that you can apply to these results. One of the first filters that I like to apply is date of last episode, which I'll click into. The reason being, if you do these searches in a search engine like Apple, for example, it's very hard to distinguish between shows that are still producing new content and shows that have stopped producing new content. This filter solves for that. And what we have here is a date range of roughly three or four months. And what I'm going to be doing here is applying a filter for shows that have published new episodes within this date range. I can apply that. And here are the results that it returns, which is great. Let's say that I want to dive deeper. Another filter that I like applying is this rating filter. It's a great proxy for two things, the first being quality. So in this case, I only want to return shows that have an average rating of at least three. It's also a great proxy for audience engagement. There isn't really a great one out there currently, but if there's evidence of people leaving ratings and reviews on shows, you can assume that the host has at least a decent following and it's worth trying to get on that show for a conversation. So we'll apply that as well. And these are the filtered results, which is awesome. Now we can keep applying filters. So you know, episode frequency, category, average episode length, there's a lot of different variations you can do, but the bottom line and what I wanted to show you today is just what makes Podchaser really a great tool to use in the podcast tour research process. Like I said, it's very hard to quickly and efficiently filter for things like the status of a show and its ratings and reviews. You can do that here on Podchaser. So this is always the last database that I like to go to when I'm adding shows to a tracking sheet. So thank you for your time. I hope this was helpful. If you weren't already familiar with Podchaser, now you are.