Daniel Parris combined his love for pop culture with data science to create the Substack ‘Stat Significant’

Today's episode is sponsored by Rev, the productivity powerhouse for content creators, journalists, market researchers, and more. Capture audio from anywhere, get AI-powered summaries and quotes, and leave security worries behind with Rev. Whether you're on the go or in the office, Rev's got you covered. Discover more at rev.com. I'm Kendall Kelton, and I'm your host today on The Rough Draft, featuring honest conversations with folks from across the creative industry. The Rough Draft explores the creative process, tools, and resources used by some of the best in the business. From journalists to content creators and business leaders, we shed light on what it looks like to break into the industry, make mistakes, collaborate with others, and also the essential tools that help us along the way. This week, I'm super excited to be talking with Daniel Paris, the brain behind the popular newsletter Stat Significant. Daniel's got a unique gig. He's a data scientist who blends numbers with pop culture. So if you've ever wondered about the statistical side of why you can't stop watching true crime documentaries or what makes Star Wars fans so dedicated, Daniel's your guy. And today we're gonna get a peek behind the curtain of Daniel's creative process. So I wanna kick things off by having you tell us, you know, a little bit about how you stumbled into this, you know, what it means to be a, a data scientist, uh, in that, in that sense to you, even though that might not have been what you intended to do with your career at first.

Start at the beginning. So when I was 8 years old, I watched a, an American Film Institute special on the 100 greatest movies. And I printed out a list of the movies and I put it on my wall and I vowed to watch every single one. And I wasn't able to really get like super far on the list until I was a little bit older because that list has things like A Clockwork Orange and Midnight Cowboy and some really upsetting movies. Maybe some things that aren't as appropriate that my parents weren't psyched about, but I just went through the list. I think like to this day I've probably watched like 90 or so of them. And that just kicked off a love of film. I made a lot of movies when I was a kid. I would go to film camp. I would go after school to all these film programs. That was sort of my identity. I went to school and I majored in film and I actually worked in the entertainment industry for a little while. So I worked for the Conan O'Brien Show and I worked for Steve Carell. It sounds fun. And I worked— it sounds a lot cooler than it is. And then I also worked for Steve Carell's production company, which also sounds a lot cooler than it is. And I just really did not like the entertainment industry. I sort of saw what the next 5 to 10 years of my life were gonna look like. And I realized that even as an intern at the lowest rung of entertainment, I was basically fighting with the other interns to get coffee for people. And so I just saw where my life was trending towards. And I had an aggressively bad intern manager when I worked at the Conan Show. And I remember calling my dad walking off the Warner Brothers lot and being like, I'm sorry, I can't do this. I know that this was the dream that I settled on when I was 8 years old, but I think I have to choose another path. So at the time, my now wife was moving to San Francisco. And so I said, cool, me too, why not? And I was told that if you move to San Francisco, there are a lot of tech jobs there. So I got a job working at like a travel startup doing sales, and I was actually quite bad at sales. And so the company decided to repurpose me as a data analyst. So I actually started going to night school to learn SQL, Python, data science, machine learning, and I found I really liked it. So I just kept funding my own education and going to night school, and I would buy textbooks and just like learn about statistics and do all these online courses. I ended up joining a, a company called DoorDash in 2016.

Never heard of them. Don't know it well.

Yeah.

I'm kidding.

At the time they were this crummy little startup, but I was one of the first data science hires and I stayed at the company full-time for 6 years doing a bunch of different data science projects. And by the time I left, the company was around 10,000 employees. So just a crazy ride. It was a great environment to learn just because I basically lived through 30 different types of company. I saw it when it was a little startup. I saw it when it was growing really fast. I saw it when the pandemic happened and it was growing even faster. And I got to work on a bunch of cool different things. I left in 2022 because it was definitely different than the company I'd first joined. And since then I've been doing data science consulting. And then I realized that I kind of just like missed movies and entertainment and I had felt like I'd been away from that stuff for too long. So I just sat down one day and I was like, well, what if I combined the stuff I loved when I was 10 years old with this, you know, vocational skill set that I've cultivated over the last few years? And effectively what was born was Stat Significant, and it's been, been a blast. A lot of people write about movies on the internet, and I wanted to figure out, is there a way that I can come at this that's unique, both unique to my skill set and then also allows me to talk about these things and pay reverence to them, but in a way that's maybe different than how others are talking about these things on the internet.

Your topics are so unique. They are really, they're really fascinating.

And I feel like my favorite part of the articles is I usually lay out a question, then I provide like a few different graphics and visualizations, like things that I've found by digging into data. And then there's usually like a section that I call final thoughts. Where I feel like I effectively like shoehorn a more like editorialized opinion.

One of my personal favorite ones that you wrote, it was from a few months ago, the When Do We Stop Finding New Music? I'd love to like hear a little bit more of how do you stumble upon some of these topics and then how do you get going in terms of gathering the data that you need?

This is usually like heavily driven by something that has happened to me in my day-to-day life. So as an example, the When Do We Stop Finding New Music article was because Spotify launched this new DJ feature. You know, it's an AI DJ, and I realized that it was just like spoon-feeding me music from when I was 13. And to be fair, when I, when I listened to Spotify, I only listened to music I liked when I was 13. But the idea that this person the DJ would reference, here is the year of the songs that I'm playing for you. And I kept realizing like, oh, this is within a very tight band of years. And after like, you know, the third like My Chemical Romance song or the fourth Fall Out Boy song, I started realizing that like it crystallized as something that felt like more than a trend. And I had thought about this topic a few times before. And so I guess I put it in this, this, this long running list I have of ideas. And at this point it's got about 100 ideas. Some of them are absolute garbage. I'd say 90% are, are never gonna be made into an article. And then some of them I'm slowly collecting different data points and data sets on and trying to figure out like, is there maybe something topical that's about to happen that could be a good tie-in or. Is there like an end to this article, like a good question to sort of lead with? And I guess going back to the, when do we stop finding new music, I found a lot of really good data. So, you know, this has been studied by different researchers. This has been studied by like Spotify employees. This has been studied by the New York Times. And so I was able to gather all of that data.

Let's chat through a bit more about your, um, writing process because it, I, it takes a lot of discipline, um, from what I've, I've read and would like to, you know, help our audience get a little bit of a peek behind the curtain of what you do on the daily because it is quite, um, it's a labor of love.

Yeah, it is. It is a labor of love. Sometimes I, I joke to myself that I've created the world's worst business cuz it's, it's like 10 to 20 hours. For each article right now, it's a free Substack. So, you know, it's 10 to 20 hours that just goes out into the abyss and there's no compensation, which is fine 'cause I really love doing it.

Writing these in-depth essays takes a lot of discipline. So I've heard you have like a pretty specific writing routine. Can you kind of share how that works for you and kind of what, you know, what started that path?

Yeah, so I actually write at least the first draft of my articles either while on walks around my neighborhood or while on the treadmill at the gym. And so I'll use one of two tools. If I'm walking around my neighborhood, I'll bring a voice recorder and I won't bring my phone. And so I'll just dictate like what I think the article should be. If I do it at the gym, I basically am only like, I'm writing directly into a note-taking tool called Notion. And basically I say, as soon as I get on the treadmill, I'm only, I'm obviously gonna be doing my workout, but for 30 minutes I'm only in Notion. I'm not going anywhere else on the internet and I'm just writing as quickly as possible. And when I do that, I can usually write in 30 minutes on the treadmill. I usually can write about like half of an article. And so between like 2 days, 30 minutes on the treadmill, I can usually like knock out the first draft and then I'll ultimately go through, take the whatever garbage I wrote for a first draft and edit it into like a second draft. But it is a really good way to just kick off the creative process and just go through that writer's block.

Getting, getting more of a look behind your creative process has been like really, really fascinating. In the next episode, we'll dig in more into, into the tools that you, you love and use on the daily. So thank you. Well, that's it for today's episode of The Rough Draft. Be sure to rate and subscribe in order to stay up to date with the latest episodes and visit rev.com/podcast for even more content. Thank you for listening, and we look forward to seeing you again on the next episode of The Rev Draft.