#282: Using (and Creating!) Data to Understand Pop Culture with Chris Dalla Riva

0:05[Announcer]: Welcome to the Analytics Power Hour. [Announcer]: Analytics topics covered conversationally and sometimes with explicit language. [Tim Wilson]: Hi, everyone. [Tim Wilson]: Welcome to the Analytics Power Hour. [Tim Wilson]: This is episode number 282. [Tim Wilson]: And technically what we're going to talk about on the show is pop culture, which can feel like a pretty kind of vibey and nebulous and subjective topic. [Tim Wilson]: And I'm Tim Wilson, and as Michael Helbling inadvertently reminds me on a regular basis, pop culture is something where I seem to be pretty locked into like a pretty narrow window of the 1980s.

0:41[Tim Wilson]: I did, after all, weave in the mid-80s sitcom 227 into the introduction I did for episode 227 of this show. [Tim Wilson]: In my defense, that was one of Regina King's earliest appearances, and she is still going strong. [Tim Wilson]: But I digress. [Tim Wilson]: I'm going to give a shot at facilitating a discussion centered around pop culture ago, even though maybe not my forte, because I think this show is going to uncover some useful perspectives about a range of kind of things that we want to measure and analyze that are inherently kind of vibey and nebulous.

1:17[Tim Wilson]: consumer sentiment, employee engagement, social influence. [Tim Wilson]: Anyone? [Tim Wilson]: Luckily, I'm joined by a couple of much more hip cats, as we said back in the day, than I am for this discussion. [Tim Wilson]: Julie Hoyer, would you agree that the data shows that I am the least likely co-host to get a Chapel Roan reference? [Julie Hoyer]: Yeah, that's probably a good conclusion, honestly. [Val Kroll]: At least he said her name right.

1:44True. [Tim Wilson]: I do have a 20-year-old daughter. [Julie Hoyer]: See, that helps. [Tim Wilson]: Yeah. [Tim Wilson]: I get a lot of dads on those sorts of things. [Tim Wilson]: And Val Crowell, we heard you. [Tim Wilson]: What about you? [Tim Wilson]: Have you ever considered checking in with me to learn about what's trending in the zeitgeist? [Val Kroll]: You are quite plugged in, Tim. [Val Kroll]: Moere than you think. [Tim Wilson]: Perfect.

2:10[Tim Wilson]: Not. [Tim Wilson]: The funny thing is that I've been a regular reader of our guest's sub-stack, which is called Can't Get Much Higher. [Tim Wilson]: I've read that for several years now. [Tim Wilson]: That newsletter is a weekly data-driven analysis about the musical trends of yesterday and today. [Tim Wilson]: So I like to think it provides me with some analyses that help me kind of fake my pop culture knowledge. [Tim Wilson]: The author, Chris Dalareva, has a day job as a senior product manager of data and personalization at Audio Mac, which is a creator-friendly music streaming service.

2:42[Tim Wilson]: Chris is also a musician and the author of an upcoming book called Uncharted Territory, what numbers tell us about the biggest hit songs and ourselves. [Tim Wilson]: For the book, Chris went back and created a pretty fascinating and extensive data set by listening to every Billboard number one song from 1958 until earlier this year, which wound up being just over 1100 songs. [Tim Wilson]: He then conducted a bunch of analyses with that data and the results are what kind of fed into the book.

3:12[Tim Wilson]: And today he is our guest. [Tim Wilson]: Welcome to the show, Chris. [Chris Dalla Riva]: Thank you for having me. [Chris Dalla Riva]: I'm looking forward to chatting with the other hip cats here. [Tim Wilson]: The fact that I am the oldest one on this mic by a lot. [Tim Wilson]: So I think hip cats might even be a little dated for me. [Tim Wilson]: So maybe a good place to start would be just by getting a little bit deeper on kind of the what, the why, the like, what were you thinking kind of in the how of the book.

3:47[Tim Wilson]: Like what prompted you to even tackle that project in the first place? [Tim Wilson]: And then how did you kind of land on Billboard number one songs as a place to do that? [Chris Dalla Riva]: Yeah, good question. [Chris Dalla Riva]: I don't think if I had some grand scheme, this listening journey would have ever started or a book would have ever been written. [Chris Dalla Riva]: In fact, I think to write a book, you have to be a little bit insane because it starts to feel like a fool's errand at multiple parts during the process.

4:15[Chris Dalla Riva]: But the reason this started was I was working in consulting when I got out of college, economic consulting. [Chris Dalla Riva]: I was in the data world already, but [Chris Dalla Riva]: I wasn't particularly enamored with my job. [Chris Dalla Riva]: I still played in bands. [Chris Dalla Riva]: I had released music, but I was just looking for another musical outlet. [Chris Dalla Riva]: And I just came up with this idea that I was going to listen to every number one hit.

4:37[Chris Dalla Riva]: And again, I probably thought this would peter out after 50 songs or something. [Chris Dalla Riva]: But I was like, oh, you know, the Billboard Hot 100 started in 1958. [Chris Dalla Riva]: I'll do one song a day. [Chris Dalla Riva]: I'd play along with it on my guitar and it would just be like a nice wind down activity for my day. [Chris Dalla Riva]: Eventually, I was telling a friend about this probably when I was 20 songs in and he was like, oh, I want to do that too.

5:00[Chris Dalla Riva]: So every day I would send him the song, we would chat about it. [Chris Dalla Riva]: And that was really it. [Chris Dalla Riva]: At a certain point, we started ranking the songs, rating the songs out of 10. [Chris Dalla Riva]: And it would just be like a fun, again, end of the day activity, but because I was already enmeshed in the data world through economic consulting, I started tracking our ratings in a spreadsheet. [Chris Dalla Riva]: This spreadsheet grew to, yeah, naturally to include an absurd amount of information.

5:31[Chris Dalla Riva]: I noticed some trends and I just started writing about it and [Chris Dalla Riva]: I started sending it around to people and they were like, oh, this is pretty good. [Chris Dalla Riva]: You should keep at this. [Chris Dalla Riva]: I did. [Chris Dalla Riva]: Eventually I realized I sort of have the makings of a book. [Chris Dalla Riva]: I'd never published anything before. [Chris Dalla Riva]: So ultimately I started trying to get articles published.

5:50[Chris Dalla Riva]: That's why I started this newsletter. [Chris Dalla Riva]: And I eventually parlayed that into eventually getting this book published. [Chris Dalla Riva]: It was a weird circuitous journey. [Chris Dalla Riva]: It's all sort of wrapped together, but it just started as a daily way to wind down, I guess. [Tim Wilson]: And then you couldn't wait because you didn't have time to do that because you had to work on content, content production.

6:11[Chris Dalla Riva]: Yeah, yeah. [Tim Wilson]: Definitely a personal issue. [Tim Wilson]: Like it sounds like it started as kind of a two column spreadsheet or say a three, it was year, song, however long it was. [Tim Wilson]: And it grew. [Tim Wilson]: I'm just conceptually thinking that's a bunch of other columns. [Tim Wilson]: Every time you added another field, you didn't have to go back and re-listen to the songs. [Tim Wilson]: That's this fundamental question I've been chomping at the bit to ask you is how the data model, I guess, if you think in classic business speak, it's going to be let's design our schema.

6:50[Tim Wilson]: And this kind of grew more organically, presumably had good intuition. [Tim Wilson]: But how did the width of the data set grow and how did you manage backpopulating, I guess? [Chris Dalla Riva]: Yeah, that's a good question because this process was super organic. [Chris Dalla Riva]: And as I was going along and I would think to write about something else, I would have to go back and repopulate it. [Chris Dalla Riva]: Some of those things did require re-listening to these songs.

7:21[Chris Dalla Riva]: For example, in chapter five of the book, I write about the evolution of song structure. [Chris Dalla Riva]: So I had to tag every single song. [Chris Dalla Riva]: the structure of every single song. [Chris Dalla Riva]: So the most common song structure these days in the pop world is just a verse chorus structure. [Chris Dalla Riva]: So when I realized I wanted to write about that, of course, as I kept going forward, I would fill out the information, but then I was like, all right, I got to go back and fill the other stuff.

7:50[Chris Dalla Riva]: And for that exercise, I had to re-listen to everything. [Chris Dalla Riva]: But I would do it at the time I was living with my parents and I would take the bus every morning into New York City for my job and I would just sit on the bus and listen to these songs and tag them. [Chris Dalla Riva]: But other stuff didn't require, most stuff required backfilling. [Chris Dalla Riva]: Some of it was easier than others or didn't require listening to all the songs.

8:15[Chris Dalla Riva]: Another good example is I track a lot of demographic information about who the artist is, where they're from, gender, race, and I do the same for songwriters and producers. [Chris Dalla Riva]: Looking up that information doesn't require actually listening to the songs. [Chris Dalla Riva]: There was a ton of manual work, which I think [Chris Dalla Riva]: was actually very, what's the word? [Chris Dalla Riva]: Manually filling all this out actually got me so deeply in touch with this data and going back through it a bunch of times.

8:47[Chris Dalla Riva]: But if I were to set out from the beginning with a hundred different columns, again, this book probably would have never happened. [Chris Dalla Riva]: It was just the organic nature and the insanity of being like, all right, I'll backfill 800 songs. [Chris Dalla Riva]: What else do I have going on? [Val Kroll]: What was one of the first themes that emerged that you were like, oh, this is a little bit of a pattern that's like novel or I hadn't heard talked about before during this time period or from this music.

9:19[Val Kroll]: I'm curious. [Chris Dalla Riva]: Yeah, the reason I initially was compelled to write something was I noticed there were lots of songs with very grisly, lyrical topics. [Chris Dalla Riva]: You know, lots of songs about teenagers getting in car wrecks and dying. [Chris Dalla Riva]: This is like the late 50s, early 60s. [Chris Dalla Riva]: And I'm thinking to myself, like, that's weird. [Chris Dalla Riva]: You know, when I turn on the radio, I feel like [Chris Dalla Riva]: If you were starting a focus group for how to write a pop song, you would be like, avoid all songs about teen car wrecks.

9:49[Chris Dalla Riva]: And there's, you know, 10 or 15 songs in a very short period that were all very popular. [Chris Dalla Riva]: So I started looking into this and this was a legitimate, a legitimate trend so much so that it has a name. [Chris Dalla Riva]: They're called teenage tragedy songs. [Chris Dalla Riva]: And again, usually it involves two high schoolers in love and one tragically dies. [Chris Dalla Riva]: Often it involves a car. [Chris Dalla Riva]: And I wanted to sort of pick that apart a little because it was so strange.

10:14[Chris Dalla Riva]: Yeah, and that was the first weird. [Chris Dalla Riva]: That sort of set me off on this journey. [Chris Dalla Riva]: The rest of the book isn't so grim, but that was the beginning of, I was like, oh, there's, you know, maybe these songs actually are speaking to something a bit deeper about what's going on in the world around [Chris Dalla Riva]: when they come out. [Julie Hoyer]: So the way the top hit of the Billboard Hot 100 list is, is it like a weekly thing?

10:39[Julie Hoyer]: And did you get runs of a song being number one multiple weeks in a row? [Julie Hoyer]: So were you like re-listening to a Beyonce song like five times in a row for certain years? [Julie Hoyer]: You know what I mean? [Julie Hoyer]: Like I'm just curious, like how did that feed your data set exactly? [Chris Dalla Riva]: Yeah, I should have specified that the Billboard Hot 100 is Billboard's pop chart. [Chris Dalla Riva]: So the goal of the Hot 100 is the number one song.

11:03[Chris Dalla Riva]: Billboard is trying to say this is the most popular song in the United States. [Chris Dalla Riva]: in a given week. [Chris Dalla Riva]: So it is weekly data. [Chris Dalla Riva]: Moest, it ebbs and flows throughout the years, but most number one songs I would say are number one for like at least three weeks. [Chris Dalla Riva]: So usually you get, I say on average like 20 number one hits per year. [Chris Dalla Riva]: I wouldn't, if a song was number one, like Hey Jude is number one for like nine weeks.

11:24[Chris Dalla Riva]: I just listened to it one day, you know? [Chris Dalla Riva]: And then the next day I go on to the next song. [Chris Dalla Riva]: You weren't a purist that way. [Chris Dalla Riva]: No, no, I didn't have to live the past in real time. [Chris Dalla Riva]: One day was enough. [Tim Wilson]: That could be one row. [Tim Wilson]: I presume what you had when it was number one. [Tim Wilson]: What was the unit of analysis, the core of the data was a song, I guess, recently?

11:48[Chris Dalla Riva]: Yes. [Chris Dalla Riva]: The core was the song. [Chris Dalla Riva]: I tracked the amount of weeks each song was at number one. [Chris Dalla Riva]: At various times when I was conducting analyses, I'd be like, oh, should I wait it by the number of weeks that the song is at number one? [Chris Dalla Riva]: Or should I just be like, all right, if it got to the number one, that's it. [Chris Dalla Riva]: We're just going to wait everything equally.

12:05[Chris Dalla Riva]: So you could approach it differently, but the unit of the data set is at the song level. [Tim Wilson]: So you started to dip into this and you had one of your newsletters kind of talked about some of this. [Tim Wilson]: You were picking [Tim Wilson]: You were picking the number one song, but the nature of how that is calculated and what goes into it. [Tim Wilson]: We think of it as being this is the number one song because it's labeled the number one song.

12:34[Tim Wilson]: Everyone understands it. [Tim Wilson]: It feels like this very objective, concrete, hard measure [Tim Wilson]: But in and of itself, the number one song is kind of a proxy you said it. [Tim Wilson]: It's like it is an attempt to say, what is the most popular pop song this week? [Tim Wilson]: But as soon as it gets converted to gathering that label number one, it's not the number two. [Tim Wilson]: And it could have been a coin flip one week.

13:00[Tim Wilson]: And here we are 40 years, 30, 20 years later, and you're listening to the one song and not the other one. [Tim Wilson]: But you had some cases where you even sort of sussed out that maybe that underlying, right? [Tim Wilson]: Was it the 70s or the 80s where it sort of felt like maybe somebody was putting a finger on the scale? [Chris Dalla Riva]: Yeah. [Chris Dalla Riva]: I mean, you have to realize like ultimately Billboard is a, it's a trade publication.

13:26[Chris Dalla Riva]: It's like, if you go into, I work at the music industry, if you go into a label, I mean, you still see copies of Billboard magazine laying around in the same way that [Chris Dalla Riva]: I don't know, if you were running a trucking company, I'm sure there's some trucking trade publication that people read. [Chris Dalla Riva]: It's just that billboards also write, yeah, billboards also writing about celebrities, right? [Chris Dalla Riva]: So it does have that pop culture crossover.

13:48[Chris Dalla Riva]: But I mean, I don't know, say you're living in 1970 and you have been tasked with defining what is the most popular song in the United States. [Chris Dalla Riva]: I don't know, I mean, how are you gonna define it? [Chris Dalla Riva]: Okay, we should look at radio. [Chris Dalla Riva]: We should look at what people are buying in record stores. [Chris Dalla Riva]: how are you gonna get that information? [Chris Dalla Riva]: At the time, Billboard would just call record stores and be like, hey, what's selling?

14:11[Chris Dalla Riva]: You know, that's a sample of record stores does seem like a great way to do it, but of course it's imprecise. [Chris Dalla Riva]: I mean, maybe the person at the record store gives you bad information accidentally. [Chris Dalla Riva]: Maybe they give you bad information on purpose for whatever reason. [Chris Dalla Riva]: You know, there are many ways that it could become skewed and in the 70s, [Chris Dalla Riva]: There are various stories about certain songs being put up at number one just for...

14:39[Chris Dalla Riva]: You know, back there, there's just deals that people were cutting like, okay, you give me the number one song this week. [Chris Dalla Riva]: And what I write about in chapter five of the book is that you can actually see this in the data. [Chris Dalla Riva]: There's some anomalous behavior in how long songs are staying at number one, when they lose the top spot, how far are they falling down the charts? [Chris Dalla Riva]: So we did a little bit of a fraud investigation there.

15:01[Chris Dalla Riva]: But it's interesting as time has gone on, of course, we listen differently these days. [Chris Dalla Riva]: And again, it becomes even harder to define what is the most popular song. [Chris Dalla Riva]: It's like, okay, we're going to look at streaming. [Chris Dalla Riva]: We're going to look at what people are buying on vinyl, what people are downloading digitally. [Chris Dalla Riva]: It's a tough task. [Chris Dalla Riva]: It's more accurate now because since in 1991, Billboard switched over to a system called SoundScan.

15:29[Chris Dalla Riva]: which basically would track when a barcode was scanned at the record store. [Chris Dalla Riva]: Like, okay, we're going to log the actual purchase and we're going to get actual playlist from the radio. [Chris Dalla Riva]: And today it's even more automated. [Chris Dalla Riva]: It's like every streaming service is sending streaming data directly to billboard. [Chris Dalla Riva]: It doesn't mean there's no shenanigans going on, but it's a very hard task.

15:51[Chris Dalla Riva]: And, you know, I think just the exercise of thinking about it makes you realize [Chris Dalla Riva]: how tricky it is to define things. [Chris Dalla Riva]: What does it mean for something to be popular and how do you weight all these things differently? [Chris Dalla Riva]: It's hard. [Tim Wilson]: But it is, you pass over. [Tim Wilson]: I mean, even like, Nielsen ratings kind of went through the, was better when it was like, we have a sample representative sample of set top boxes and people are watching TV this way.

16:19[Tim Wilson]: And then they have like really struggled to say, [Tim Wilson]: you know, what is the most popular show? [Tim Wilson]: Or I even think with like social media with trying to figure out who is like, who is an influencer? [Tim Wilson]: And there's the, you know, the Kelsey brothers or Taylor Swift. [Tim Wilson]: That's an easy, they're like way up there. [Tim Wilson]: But when you try to get down to some sort of quantifiable measure, you're stuck with trying to pick some sort of proxy.

16:47[Tim Wilson]: And if that proxy becomes [Tim Wilson]: widely adopted than it's subject to be, you know, manipulated. [Tim Wilson]: Oh, it's going to be the number of followers they have on these accounts. [Tim Wilson]: Well, then they can, people can go and buy followers. [Tim Wilson]: So, cool. [Tim Wilson]: That was just existential. [Tim Wilson]: Well, yeah. [Tim Wilson]: The Kelsey Brothers and Taylor Swift. [Tim Wilson]: I am like tapped in.

17:09[Tim Wilson]: Look at that. [Chris Dalla Riva]: But they are ultimately proxies. [Chris Dalla Riva]: You're right. [Chris Dalla Riva]: All this stuff is we're proxying, we're trying to get at something. [Chris Dalla Riva]: Is the number one record in a given week dramatically more popular than the number two record? [Chris Dalla Riva]: I don't know, probably not. [Chris Dalla Riva]: Is it unpopular? [Chris Dalla Riva]: No, I also wouldn't say that.

17:32[Chris Dalla Riva]: Like it's getting at popularity. [Chris Dalla Riva]: I don't know if you've reached the platonic form of measuring this, but it's a hard problem. [Tim Wilson]: Does it matter if one and two and three and four and five in general have some kind of similar characteristics over time, week to week, based on what you're trying to look at? [Tim Wilson]: Presumably, it would come out in the wash. [Tim Wilson]: You're working with some level of uncertainty, but if you're looking at the size of the backing band or the number of writers on the song, presumably, as you've been trying to look at, what are these trends happening over time?

18:17[Tim Wilson]: You could have gone and listened to every number three song and probably come up with the exact same or very, very similar results, right? [Chris Dalla Riva]: Yeah. [Chris Dalla Riva]: I went through this at the beginning of the book where someone was like, when I was first starting to write this, someone was like, well, our number one song is really a representative sample of what's going on in popular music. [Chris Dalla Riva]: Shouldn't you be looking at the entire top 10 or the entire top 100?

18:42[Chris Dalla Riva]: That would be impossible given that I was listening to the songs and, you know, I have to... The bus ride wasn't that long. [Chris Dalla Riva]: No, well, some days... [Chris Dalla Riva]: Damn tunnel. [Chris Dalla Riva]: Yeah, literally. [Chris Dalla Riva]: What I came upon is exactly what you were saying, Tim, is that for something to become the most popular song in the United States for even one week, it is typically representative of a larger trend that is going on.

19:13[Chris Dalla Riva]: And I would see that again and again. [Chris Dalla Riva]: Occasionally, there is just one random song that shoots to the top of the charts. [Chris Dalla Riva]: It's completely unconnected from everything else. [Chris Dalla Riva]: But most of the time, [Chris Dalla Riva]: There are musical movements and that's how these songs become popular. [Chris Dalla Riva]: So they are, if I were to have chosen the number three song, I mean, it doesn't have as nice of a ring to it, but I think the outcome for all of the analyses in the book and my newsletter would largely look the same.

19:41[Julie Hoyer]: I wonder if your fraud one would have looked the same or not though, because I doubt people are like, [Julie Hoyer]: you know, if they're trying to put their finger on the scale, are they really going to be happy with number three? [Julie Hoyer]: They're like, no, give me number one. [Julie Hoyer]: You know what I mean? [Julie Hoyer]: Like I would do wonder if some of those like drastic anomalies would exist if you had done, you know, top three instead of one.

20:01[Chris Dalla Riva]: I should have done that as a comparison point, but I didn't. [Val Kroll]: a list of things to do. [Tim Wilson]: I bet they would care more about whether they're 10 or 11 than they would care about whether they're 4 or they're 5, right? [Tim Wilson]: I mean, I could see just what people say billboard top 10, right? [Chris Dalla Riva]: Yeah, their top 40 has been the thing for decades where it's like a radio format. [Chris Dalla Riva]: Um, so if you were at number 40, there were lots of shows over the years that have counted down the top 40 songs every week.

20:32[Chris Dalla Riva]: So if you were 41, that's really bad for you. [Chris Dalla Riva]: So that's, there's probably weird, really weird behavior around there too. [Chris Dalla Riva]: Um, especially back when radio was very important to how music work. [Val Kroll]: top nine at nine. [Val Kroll]: I'm just like revisiting all these like memories of like the radio, like counting things down. [Val Kroll]: But I remember being like on Friday nights, like I'm from Chicago.

20:52[Val Kroll]: So B96, I would always record it. [Val Kroll]: So I'm like, this is it. [Val Kroll]: This is the top nine. [Val Kroll]: Like they know they figured it out. [Val Kroll]: Like we got to record it. [Val Kroll]: This is, this is the playlist that everyone's going to be listening to while they're playing hopscotch on you. [Val Kroll]: I don't even know how old it was, but I was pretty obsessed with that. [Val Kroll]: I do recall. [Tim Wilson]: Something else that you said was that you started listening and the generating of the data was just you and your friend with a rating and a ranking.

21:22[Tim Wilson]: But then you already alluded to, well, there's other stuff that you realized was other metadata about the song, but you went to other sources that wasn't from listening to it and creating the data, which [Tim Wilson]: Did you remember when the first time you're like, oh, I could add 12 columns to this data set by pulling data from somewhere? [Tim Wilson]: The whole supplementing, that's intriguing as well, that your data set grew from other data sets.

21:57[Chris Dalla Riva]: Yeah. [Chris Dalla Riva]: There are a couple sources that I started tapping pretty early in the process. [Chris Dalla Riva]: Of course, the big thing is like, who's involved in making this song? [Chris Dalla Riva]: Beyond the performer, the top things are songwriters and producers. [Chris Dalla Riva]: Songwriters have always fascinated me. [Chris Dalla Riva]: So there are some songwriter databases run by BMI and ASCAP, which are two of the biggest music publishers in the United States.

22:23[Chris Dalla Riva]: And they track [Chris Dalla Riva]: you know, they get songwriters paid. [Chris Dalla Riva]: So I would go there to get songwriter information. [Chris Dalla Riva]: Spotify also generates... [Chris Dalla Riva]: a ton of information about the audio files on their platform, things like BPM, but they also gauge loudness and energy and what they call danceability and acousticness. [Chris Dalla Riva]: They've sadly shut down a lot of these APIs because I think people were probably using them to train LLMs.

22:52[Chris Dalla Riva]: Luckily, I had gotten all the information before that. [Val Kroll]: You got some time. [Tim Wilson]: Were there any APIs that you were like, this is like, they like really, or this data was very, very so easily accessible that was like really pleasant. [Tim Wilson]: And on the flip side, was there somewhere like that, you know, they have the data, but they've done, it's an absolute nightmare to pull it in any sort of scale. [Chris Dalla Riva]: Spotify, I mean, still the Spotify API is really easy to use.

23:21[Chris Dalla Riva]: They've just changed what you can actually get access to. [Chris Dalla Riva]: So that was always, [Chris Dalla Riva]: Always a pleasure, Spotify. [Chris Dalla Riva]: Thank you. [Chris Dalla Riva]: I would have playlists of these songs on Spotify, and it's very easy to just take a playlist of songs and ask the API to spit back certain metadata with a Python script. [Chris Dalla Riva]: So that was great. [Chris Dalla Riva]: I mean, lyrics are really easy to get around the web.

23:48[Chris Dalla Riva]: Those were always a pleasure to grab. [Chris Dalla Riva]: And I've done a lot of stuff over the years on my newsletter and in the book using data from Wikipedia. [Chris Dalla Riva]: And Wikipedia, there's an API and then people have built nice little wrappers for it and it works pretty well. [Chris Dalla Riva]: So I never [Chris Dalla Riva]: There are music data sources that you have to pay for. [Chris Dalla Riva]: I never really had to rely on them for the stuff that I was doing because I feel like a lot of it was sort of wacky and based on historical data where no one's monetizing label or songwriter credits from hits in the 1960s.

24:28[Chris Dalla Riva]: If I want information on like [Chris Dalla Riva]: streaming trends, like streaming trends right now, that's stuff you really have to pay for. [Chris Dalla Riva]: There's a couple sources out there, but for the book, I didn't really rely on stuff like that. [Julie Hoyer]: How did you decide when you were done making this data set or is it like your baby and you're like, I can't stop. [Julie Hoyer]: I'm just going to keep adding it.

24:49[Chris Dalla Riva]: Well, I sort of joke about that at the end of the book. [Chris Dalla Riva]: I'm like, well, I had to end the book, but it's not like music doesn't end. [Chris Dalla Riva]: The day this comes out, it's already gonna be dated. [Chris Dalla Riva]: If there's gonna be other number one songs. [Chris Dalla Riva]: The dataset grew until I finished the last chapter and I was like, all right, the book is done. [Chris Dalla Riva]: I'm saying it grew lengthwise in terms of songs, but also widthwise.

25:11[Chris Dalla Riva]: If I was writing the last section, the last chapter and I was like, [Chris Dalla Riva]: There would be this really cool analysis that I could run and I didn't have the data. [Chris Dalla Riva]: You have to be a little nuts to, I think, do something like this and not feel angry that you're going to have to go back and fill in a ton of information. [Chris Dalla Riva]: Yeah, it grew as I needed it to grow and not really much beyond that.

25:38[Julie Hoyer]: Did you have a lot of it automated by the end? [Julie Hoyer]: Like you would listen, you'd have maybe 20 columns you fill out. [Julie Hoyer]: I don't know, maybe that's like really small and you're like, I wish or you're like, no, that's crazy. [Julie Hoyer]: 20 is too many. [Julie Hoyer]: But did you have a lot of it automated and it wasn't pretty easy to just keep adding to? [Chris Dalla Riva]: Actually, very little of it was automated, but the reason it never really became automated was because I was only listening to one song a day.

26:03[Chris Dalla Riva]: So I was like, you're just listening and I'm typing information as I'm listening. [Chris Dalla Riva]: I really usually only think about automating things if I'm grabbing tons and tons of data at once, but it was very tractable for me to be like, all right, today I'm going to sit down and listen to hot stuff by Donna Summer. [Chris Dalla Riva]: By the time you listen through twice, you've probably filled out all the information you're looking for.

26:29[Tim Wilson]: That was actually, so was that kind of the typical? [Tim Wilson]: Was it sort of two listens or was it like how many times did you have to listen to feel good about? [Chris Dalla Riva]: I would tell myself I would always listen twice, whether some of the songs [Chris Dalla Riva]: Even if I wasn't alive at the time, I mean, you're intimately familiar with, but still I would try to listen twice with fresh ears to see if anything struck me.

26:51[Chris Dalla Riva]: I mean, at this point, I've heard many of these songs too many times, but some of them twice is all you need and hopefully never hear again. [Val Kroll]: Okay, that's some of the stuff I'm super interested in. [Val Kroll]: I do have a data-related question, but is there any song that you heard that you wasn't one of your favorites or not even on your radar, but now it's a go-to playlist item? [Val Kroll]: Or in verse, you're like, if I have to listen to the song one more time.

27:20[Chris Dalla Riva]: There's another nice thing I think about using number one hits as a sample is that if you were to look at some list of music of the 1960s, it would probably be packed with things that are now considered classics, but in every decade, in every era, [Chris Dalla Riva]: There is good stuff released and there is horrible stuff released. [Chris Dalla Riva]: The horrible stuff just gets, you know, swept away and we never listen to it again.

27:45[Chris Dalla Riva]: But when you listen to just number one hits, again, it's just what was popular in one single week. [Chris Dalla Riva]: you get the good, the bad, and the ugly. [Chris Dalla Riva]: And I certainly saw all that through my journey. [Chris Dalla Riva]: I mean, there's one, there's a song in their early 70s called Want Ads by a group called Honey Cone that's completely forgotten by however you measure it. [Chris Dalla Riva]: I mean, this song has no cultural footprint and it's absolutely awesome.

28:09[Chris Dalla Riva]: I always am telling people about it. [Chris Dalla Riva]: And there's also stuff that has no cultural footprint anymore that is horrible. [Chris Dalla Riva]: I mean, there are tons of novelty songs from over the years. [Chris Dalla Riva]: There's a song called Disco Duck from the 70s, which was like a joke about disco. [Val Kroll]: It's really been like... I'm familiar. [Tim Wilson]: Nope, that hit me when I was at a certain age.

28:32[Val Kroll]: Yeah, it was... It would be like my Macarena. [Chris Dalla Riva]: The Macarena is another great example of, I mean, dance crazes have also, people have been dancing for thousands of years. [Chris Dalla Riva]: So you can imagine that every generation has their handful of dance songs. [Chris Dalla Riva]: Some of them seem silly now. [Chris Dalla Riva]: I mean, I'm not gonna throw on the Macarena, you know, on Saturday afternoon, but it's representative of something that was going on, something larger in the cultural atmosphere at that time.

29:05[Val Kroll]: That's funny. [Val Kroll]: So I'm curious about, and you wrote about this in one of your posts about the one hit albums or one hit wonder albums. [Val Kroll]: I'm not going to say that correctly, but in the context of this exercise, I'm curious if there was something that was a little bit more qualitative that you were rating that as you went through it, it made you think [Val Kroll]: Oh, I need to reassess my definition or even when we were talking earlier about like teenage tragedies that I was just thinking, even though like on the face, like that feels, you know, like yes or no.

29:37[Val Kroll]: But, you know, when the girl meets the boy from the wrong side of the tracks, like, you know, maybe as a fit in it, does it not? [Val Kroll]: Like, I'm curious about how some of that stuff was scored or how you even documented for yourself what some of those definitions were to be consistent across all your listens. [Chris Dalla Riva]: Tim mentioned this earlier is when we think about popular culture, there's a fuzziness to it. [Chris Dalla Riva]: I mean, we're not talking about chemistry class or physical compounds.

30:07[Chris Dalla Riva]: As much as I would want to be able to categorize certain things perfectly, you have to understand the fact that some of this stuff is always going to be fuzzy no matter what. [Chris Dalla Riva]: Some of it won't. [Chris Dalla Riva]: I track how long the song is. [Chris Dalla Riva]: I don't think there's gonna be ton of a debate about [Chris Dalla Riva]: You know how many seconds Benny and the Jets by Elton John goes on for but I That's something I would grapple with constantly before I was this is I think a perfect example and I write about this in the book is This topic is a little bit like inside baseball ish, but the structure of popular songs is [Chris Dalla Riva]: When we, most people think of a popular song these days, I think of your typical verse chorus song.

30:51[Chris Dalla Riva]: I mean, most stuff you hear on the radio now to talk about Chapel Roan is gonna be, you have your verses and you have your big repeated chorus that goes on and on throughout the song. [Chris Dalla Riva]: And I wanted to see if that was the most common way popular songs were structured over the decades. [Chris Dalla Riva]: The short answer was it was not. [Chris Dalla Riva]: There were different song structures that were popular before that.

31:15[Chris Dalla Riva]: the most common structure at the time is sometimes called like the great American song structure or A A B A in something, use something like Over the Rainbow by Judy Garland is of this structure. [Chris Dalla Riva]: There's not really a chorus in that song. [Chris Dalla Riva]: Every verse opens with a refrain and then there's a B section, which is like the someday I'll wish upon a star. [Chris Dalla Riva]: I don't want to get too much into the weeds there, but the point is that even [Chris Dalla Riva]: I wish there were just like five song structures that people perfectly adhered to, and I could just be like, all right, this is song structure three on this song.

31:48[Chris Dalla Riva]: But that's not how artists work. [Chris Dalla Riva]: There would be songs like, this is very, very close to this one structure. [Chris Dalla Riva]: It's a little bit different, but I'm still just going to call it that because that's what it's close to. [Chris Dalla Riva]: You do have to wrestle with stuff like that throughout the process. [Chris Dalla Riva]: And when I write my newsletter, I often try to show the process that I'm going through because often I think the thought process is just as interesting as the final result because you have to wrestle with this fuzziness.

32:17[Tim Wilson]: When there's a big part of that, I think it was the one hit wonders one where there were kind of a series of pieces that all seemed like you were like, this seemed straightforward. [Tim Wilson]: It was straightforward and it was absolutely did not pass the sniff test. [Tim Wilson]: Nobody is going to believe that [Tim Wilson]: You know, the grateful debt is, I can't remember what the examples were, but you were like, so I have to then change the way I do the analysis.

32:45[Tim Wilson]: So that was kind of a step removed from the data collection, right? [Chris Dalla Riva]: Yeah. [Chris Dalla Riva]: I believe you're talking about, I did want about two hit wonders. [Chris Dalla Riva]: A coworker of mine asked me, we were joking. [Chris Dalla Riva]: at work about the band 38 special that they have two, they have these two songs that we would both always hear in the supermarket. [Chris Dalla Riva]: And he was like, oh, I wonder who the greatest two hit wonder of all time is.

33:08[Chris Dalla Riva]: And I was like, I think I'm the guy to find out for you. [Chris Dalla Riva]: But this seems like a really simple question. [Chris Dalla Riva]: All right, let's just find every band that had two top 40 hits and nothing else. [Chris Dalla Riva]: You can easily download the entire history of the Billboard Hot 100 going back 65 years. [Chris Dalla Riva]: And then I'll sort those artists by their current popularity on Spotify. [Chris Dalla Riva]: also data that's easy to get.

33:39[Chris Dalla Riva]: And then the number one, two hit wonder, the most popular two hit wonder was Pink Floyd. [Chris Dalla Riva]: And I was like, that cannot be right. [Chris Dalla Riva]: How is that possible? [Chris Dalla Riva]: This is one of the greatest selling bands of all time. [Chris Dalla Riva]: But [Chris Dalla Riva]: Pink Floyd didn't really release a lot of singles in the US. [Chris Dalla Riva]: They were mostly known for their albums. [Chris Dalla Riva]: And Pink Floyd truly only had in the US two top 40 singles, Moeney and Another Brick in the Wall.

34:01[Chris Dalla Riva]: And there's a lot of other weird bands that end up on this list, like The Killers or The Cure, you know, bands that are tremendously successful. [Chris Dalla Riva]: And I was like, that can't be right. [Chris Dalla Riva]: So then what I had to do, I was like, all right, you have to have two top 40 singles and you can never have had a top 10 album. [Chris Dalla Riva]: And then suddenly you end up with a list that more passes the smell test.

34:27[Chris Dalla Riva]: You get a group like AHA, who is most famous for their huge hit take on me, but they had another top 40 hit in the US. [Chris Dalla Riva]: They're more popular in Europe. [Chris Dalla Riva]: Crowded House for our 2000s kids, Cascada. [Chris Dalla Riva]: had two hits evacuate the dance floor and every time we touch. [Chris Dalla Riva]: And when I was looking at this list, I was like, I was like, this, these feel like legitimate to hit wonders, but you have to grapple with like, [Chris Dalla Riva]: You have an idea in your head about a lot of this stuff and then you follow it through and it doesn't make any sense.

34:58[Chris Dalla Riva]: And you realize that your intuitive definition is not accurate enough or does not reflect reality in the way that you think it does. [Chris Dalla Riva]: And that applies in the work I do in the book and my newsletter. [Chris Dalla Riva]: But I think in data analytics, generally that applies. [Chris Dalla Riva]: Like you have to figure out how you want to define things. [Tim Wilson]: But then you wind up down the path of telling your business partner that [Tim Wilson]: Yeah, you just add the business equivalent of what are the top two hit wonders.

35:26[Tim Wilson]: When you come back and say, well, that actually didn't make sense. [Tim Wilson]: I have to give you enough other little context of where I had to correct for that does seem like that's a regular challenge of the analyst. [Julie Hoyer]: I was going to say this is such a good example of, I remember being a newer analyst and like, I think music is so personal to people and everyone can connect to it easily. [Julie Hoyer]: So like the type of things you're talking about Chris and running into, I think it's more obvious to people like, oh, well, you have to consider XYZ or did you think to ask yourself this type of question?

36:02[Julie Hoyer]: But when you're a newer analyst and you get into data that you're not as familiar with or don't have as much context around it, I think you fall into the trap of taking it at face value and not asking some of those probing questions of like, how is it collected? [Julie Hoyer]: How are they determining certain aspects of or characteristics of the data? [Julie Hoyer]: And so it's just interesting that music [Julie Hoyer]: really shows the squishiness of the data around it.

36:30[Julie Hoyer]: And when you're trying to answer a question, how you really have to think through and refine the definitions and your assumptions. [Julie Hoyer]: Because actually, I was going to ask too, in your, it's funny that we all read your one hit wonder articles. [Julie Hoyer]: I was reading the one album wonder article. [Julie Hoyer]: And you had a quote in there saying, one of the most important things you need to learn when working with data is when the data is insufficient to solve your issue.

36:56[Julie Hoyer]: And I was just curious, like, you highlight it for the one album wonder topic, but were there other topics you've run into where you're like, yeah, the data just can't really answer this question that I had about music or pop culture? [Chris Dalla Riva]: I run into this. [Chris Dalla Riva]: frequently where I want to write about something or someone suggests something and I just can't get the information. [Chris Dalla Riva]: The longest running topic I have related to this much to the anger of one friend that suggested it to me is he's convinced that if you are a punk, popular punk musicians are much more likely to have had their parents get divorced than the average person in society.

37:43[Val Kroll]: You need that trauma? [Chris Dalla Riva]: I was, yeah, I was like, well, I mean, this again, this is theoretically shouldn't be hard to figure out, but it's just like, first you need a list of punk musicians, which you could get somewhere. [Chris Dalla Riva]: I mean, I use Wikipedia a lot and there's always like, there's tons of lists on Wikipedia, like list of punk musicians from Australia or something, but then, you know, pairing that with who people's parents are and if they, if their marriage survived, it's, [Chris Dalla Riva]: That's almost impossible.

38:14[Chris Dalla Riva]: It's almost impossible. [Chris Dalla Riva]: So yeah, every time I see it. [Val Kroll]: Like the ancestry. [Julie Hoyer]: Yeah, it was like genealogy. [Julie Hoyer]: Maybe if he makes you your data set, then you could do their analysis, you know, like his labor of love, following up on how the marriages went. [Chris Dalla Riva]: I do get upset about that topic because I thought it was, I mean, it's a grim, but it's sort of a, sort of a funny topic.

38:37[Chris Dalla Riva]: And I sort of believe, I believe his theory too, but [Chris Dalla Riva]: you would just need, not only would you need that, but I would also, I would want to have comparisons for other genres than comparisons to like the general population. [Chris Dalla Riva]: It's never gonna happen, but you have to know when to say, I can't write about this because I don't have the information. [Chris Dalla Riva]: Like data can't address, that's something that is measurable, but you can't get the information.

39:05[Chris Dalla Riva]: Then there's other stuff. [Chris Dalla Riva]: It's like, it's probably not measurable in the right way. [Tim Wilson]: a Python code. [Tim Wilson]: That is another one that kind of parallels to the more qualified leads instead of hit singles would be [Tim Wilson]: that your interest, the topic of interest is around punk musicians and their parents, but you can't really draw conclusions without seeing if that is great. [Tim Wilson]: Somebody thinks, well, if you had all of that data and then you just, you're like, yeah, but even all that data, that wouldn't tell you if that is how that compares.

39:47[Tim Wilson]: So all of a sudden, the data set that's needed has to, [Tim Wilson]: expand to some degree. [Chris Dalla Riva]: This is a problem I have frequently because I do some stuff where there's a preexisting data set and I crunch the numbers. [Chris Dalla Riva]: But I tend to, a lot of the stuff I do, I have to build a data set, which leads to, I think some interesting writing, but it's a pain to do. [Chris Dalla Riva]: So that case would, it's never going to happen, but we can do it.

40:19[Julie Hoyer]: Do you ever time box yourself on analyses or like, [Tim Wilson]: The publisher probably did for the... [Julie Hoyer]: You definitely did but like in general when you get like a I guess two two thoughts here one How do you source some of your? [Julie Hoyer]: Like hypotheses going into an analysis and then once you get into it Are you like okay? [Julie Hoyer]: I'm gonna give myself X amount of time or X amount of effort Or you just kind of go until you hit an obstacle that's a lot you can't overcome.

40:49[Chris Dalla Riva]: Yeah, like I'm so I publish every Thursday and [Chris Dalla Riva]: really pretty religiously and though maybe the only thing I've learned on the internet over the last decade across social media platforms is that [Chris Dalla Riva]: you should just put stuff out, even if it's not perfect or finished in the way that you want, because you'd never know what people are gonna connect with. [Chris Dalla Riva]: And I've had stuff where I'm like, ah, this is okay.

41:15[Chris Dalla Riva]: It's not perfect. [Chris Dalla Riva]: And then it ends up doing really well. [Chris Dalla Riva]: And then you have the thing you've worked on for two and a half months and you put out, no one cares. [Chris Dalla Riva]: So I usually, I just usually spend a couple of days on this stuff, unless it's something like, I know this is gonna take more time. [Chris Dalla Riva]: I'm gonna publish it. [Chris Dalla Riva]: in a couple of weeks, but it's usually in the matter of a week I'm going to sit down.

41:37[Chris Dalla Riva]: I have a list of topics that whenever I think of something, I'll be like, all right, let's try to do this. [Chris Dalla Riva]: If it's not going anywhere, move on to something else. [Chris Dalla Riva]: But I know that I have to put something out on a Thursday, so I'm very schedule-oriented. [Chris Dalla Riva]: So, I'm always working under the clock. [Chris Dalla Riva]: Funny if the book was less like that because I couldn't get a publisher for this book for so many years that by the time I found a publisher, nearly all of it was written.

42:01[Chris Dalla Riva]: I had to edit it, but I wasn't on a time clock as much as then with the weekly newsletter, which I'm in complete control of. [Val Kroll]: That's nice. [Val Kroll]: So then your list of topics, are those like the hypotheses like Julie was saying? [Val Kroll]: And how do you come up with that list? [Val Kroll]: Is it like comments or questions from prior weeks in publishing or how do you come up with that? [Chris Dalla Riva]: Yeah.

42:21[Chris Dalla Riva]: I mean, at this point, people do ask me a lot of questions that [Chris Dalla Riva]: if I think I can get information on, I'm willing to take a hack at. [Chris Dalla Riva]: But other stuff is just, I don't, I spend a lot of time thinking about music. [Chris Dalla Riva]: I work, my day job is in music. [Chris Dalla Riva]: I play in bands over the years. [Chris Dalla Riva]: You know, I've worked on this book. [Chris Dalla Riva]: I read about music.

42:43[Chris Dalla Riva]: So stuff just comes up over time and I just write it down. [Chris Dalla Riva]: And then when I sit down one week, I just see which one seems interesting. [Val Kroll]: What inspires you? [Val Kroll]: So do you tell your bandmates, like, I have all this data, I know all the ingredients, the secret sauce for the perfect song. [Val Kroll]: We just have to follow the AB classic pattern. [Val Kroll]: Got to have some heartbreak in there.

43:08[Chris Dalla Riva]: Sadly, no, I actually joke about this at the end of the book because this is a frequent question. [Chris Dalla Riva]: It's like, have you discovered the secret? [Chris Dalla Riva]: And I'm like, well, if I discovered the secret, I would have wrote the song instead of the book because probably more lucrative and would take much less time. [Chris Dalla Riva]: So yeah, I mean, there are, [Chris Dalla Riva]: The people I play music with joke that if they make an observation about music to me, they may see it in a newsletter.

43:36[Chris Dalla Riva]: But no, there's no real secret sauce. [Chris Dalla Riva]: I mean, the only thing I could tell you is that things that are pop, when something's very popular, usually there are many other things that are popular that are similar-ish to it. [Chris Dalla Riva]: So if you want to write a really popular song, you should be working within the constraints or the structures that are popular at a given moment. [Tim Wilson]: Given on that front, though, did you pick up on any sort of dimensions, very clear inflection points that something shifted?

44:11[Tim Wilson]: We intuitively think 60s pop sounds different from 70s pop sounds different from [Tim Wilson]: early 80s to late 80s, but is it always kind of a gradual continuum or were there ones where you said, no, like the invention of this technique or something shifted everything? [Chris Dalla Riva]: One of the key themes throughout the book is that musical innovation. [Chris Dalla Riva]: This is my theory, not my personal theory, but what I write about a lot.

44:39[Chris Dalla Riva]: Musical innovation is often downstream of technological change. [Chris Dalla Riva]: So things are gradual, but there are certainly moments where something is invented or something changes and it fundamentally shifts the way things sound. [Chris Dalla Riva]: You're talking about the 80s. [Chris Dalla Riva]: And it's actually, it is interesting because even people who only listen to music very passively can usually listen to something and have a general idea when it's from.

45:09[Chris Dalla Riva]: The creation of drum machines in the late 1970s, which became ubiquitous throughout the 1980s, is many, many popular songs are created with drum machines. [Chris Dalla Riva]: That's sort of an inflection point where the sound of popular music changes. [Chris Dalla Riva]: In the early 90s, hip hop becomes very popular. [Chris Dalla Riva]: And that's a fundamental shift you can see in the data on multiple fronts. [Chris Dalla Riva]: Because for the first half of the 20th century, your most popular songs were usually focused on melody and harmony, you know, something you could sing along to in the shower.

45:46[Chris Dalla Riva]: And then by the late 90s, early 2000s, [Chris Dalla Riva]: Popular music becomes much more focused on lyricism and rhythm, not to say that there's no melodic qualities of hip-hop, but you're not gonna hum, lose yourself by Eminem in the shower. [Chris Dalla Riva]: I mean, just, it's not. [Chris Dalla Riva]: Speak for yourself, Chris. [Chris Dalla Riva]: That's not a show. [Chris Dalla Riva]: But you can see stuff like this, and I write about it, it's like, [Chris Dalla Riva]: It's words per minute in songs.

46:15[Chris Dalla Riva]: I mean, it dramatically increases in the 90s because hip-hop is a much wordier genre than the things that come before it. [Chris Dalla Riva]: And one of my other favorite examples I always talk about where in the first half of the 20th century, and I measure this, there's a larger portion of songs without vocals, so instrumental portions of songs. [Chris Dalla Riva]: After 1960, if there's a front person in a group, it's almost always the singer.

46:42[Chris Dalla Riva]: We basically take this for granted that the singer is the star, but that wasn't the case for decades upon decades. [Chris Dalla Riva]: If you look at all these old big bands, the band leaders usually like the tuba player or the clarinet player. [Chris Dalla Riva]: Part of the reason you see this shift is just because microphone technology improves. [Chris Dalla Riva]: Previously, [Chris Dalla Riva]: If you were, again, imagine a world without microphones.

47:06[Chris Dalla Riva]: If there's an orchestra playing, how are you gonna hear a voice over it? [Chris Dalla Riva]: You're gonna have to sing at the top of your lungs, and even then, you probably need a choir of people to be heard. [Chris Dalla Riva]: But in like the 30s and the 40s, microphones get a lot better, and suddenly you can be Frank Sinatra, and you can sing with this very soft croon, and it can be heard over everything. [Chris Dalla Riva]: with clarity, that technology fundamentally changes, you know, who's the star in groups and which vocal styles can even be performed.

47:36[Chris Dalla Riva]: Again, if you can't pick up a quiet voice, then you don't get Bing Crosby or Frank Sinatra. [Chris Dalla Riva]: It's just a different singing style. [Chris Dalla Riva]: So, longest short is, yes, there are these inflection points, and I don't think it's deterministic, but technology really does shape [Chris Dalla Riva]: how we hear songs and what songs are made, and you see that in musical data. [Julie Hoyer]: I have to admit, when you said musical technology, because I'm obviously not a musician, my brain went to the whammy bar.

48:07[Julie Hoyer]: That's like all I could think about. [Julie Hoyer]: I was like, what's musical technology? [Julie Hoyer]: That is a musical technology. [Julie Hoyer]: So yeah, that's really it. [Chris Dalla Riva]: No, that is totally. [Chris Dalla Riva]: That's even like the electric, the creation of the electric guitar, like you don't get rock and roll if someone, someone, Leo Fender or whoever doesn't, [Chris Dalla Riva]: figure out how to plug in a guitar and distort it and whatever.

48:30[Julie Hoyer]: Yeah. [Julie Hoyer]: Tim, before you cut us off. [Tim Wilson]: No, no, I got to shout out the Roland TR-808 drum machine, which the 99% Invisible did an entire podcast episode about, and also not really a musician, so I didn't. [Tim Wilson]: But when you said the drum machine technology, like they walk through an exhaustive [Tim Wilson]: explanation similar to what Chris, I just, there's some listener who's listening to other podcasts and saying, but what about the 99 PI episode?

48:58[Chris Dalla Riva]: I have heard that episode. [Chris Dalla Riva]: That's a great, I mean, that whole podcast is great. [Chris Dalla Riva]: Yeah. [Julie Hoyer]: That's awesome. [Julie Hoyer]: Cause as I was going to say, I want to ask one more question. [Julie Hoyer]: I'm curious. [Julie Hoyer]: I'll allow it. [Julie Hoyer]: Do you? [Julie Hoyer]: Why? [Julie Hoyer]: Thank you. [Julie Hoyer]: I want to know, because again, when I was reading through some of your newsletters, you mentioned that you go through this process.

49:19[Julie Hoyer]: Sometimes you have to iterate, iterate on definitions. [Julie Hoyer]: And I love that you show your readers that process as you go through. [Julie Hoyer]: But it made me think, are there any analyses, as time has gone on, that you've gone back and wanted to redo? [Julie Hoyer]: Or are there any that you did in the past that you're like, oh, that was such a bear, I hated it, or that was my favorite? [Julie Hoyer]: I kind of wanted to get a hit list of your [Julie Hoyer]: Top 10 analyses are top five.

49:45[Val Kroll]: You know, your top charts, your top five charts, whatever category you want to pick. [Chris Dalla Riva]: Yeah, there are a couple that come to mind. [Chris Dalla Riva]: Every Christmas season, I try to do an addition on predicting new Christmas classics, usually from some data approach. [Chris Dalla Riva]: And I try to... [Chris Dalla Riva]: I've tried to use Spotify playlist data. [Chris Dalla Riva]: I've tried to use looking up songs.

50:09[Chris Dalla Riva]: What are people looking up on Wikipedia? [Chris Dalla Riva]: Like I said, I love Wikipedia. [Julie Hoyer]: I never would have thought to use Wikipedia as a data source, by the way. [Julie Hoyer]: But you talking about it, I'm like, oh, wow, it sounds like a plethora of information. [Chris Dalla Riva]: It is. [Chris Dalla Riva]: I use it in the book and I use it in the newsletter from time to time. [Chris Dalla Riva]: But yeah, I go back to that Christmas one a lot, not because [Chris Dalla Riva]: I think that the earlier ones were bad, but I don't think it's constantly changing and the ways I've tried are not exhausted.

50:42[Chris Dalla Riva]: I'm sure there are other ways to pick up on which Christmas songs are becoming more popular. [Chris Dalla Riva]: There's others sometimes. [Julie Hoyer]: Have you predicted some correctly? [Chris Dalla Riva]: I think the two... I don't think this is a surprise. [Chris Dalla Riva]: Moedern classics or on their way to classic dumb are Santa Tell Me by Ariana Grande and Underneath the Tree by Kelly Clarkson Seem to from the last decade seem to be getting more play There are some things I write where I start taking an analytical approach.

51:14[Chris Dalla Riva]: I'm like [Chris Dalla Riva]: this isn't working and I just end up, I don't always write, sometimes I just write about like the music industry or some trend, not really from a quantitative perspective. [Chris Dalla Riva]: One that comes to mind was I wanted to write about the evolution of music and supermarkets. [Chris Dalla Riva]: Just how has that changed over the years? [Chris Dalla Riva]: What you hear when you're in the produce section?

51:41[Chris Dalla Riva]: And I couldn't get historical data on it. [Chris Dalla Riva]: I was talking to some people who like companies that they pipe in the music to stores and I ended up not getting it. [Chris Dalla Riva]: And then wrote a sort of a history of music and supermarkets, which was sort of interesting. [Chris Dalla Riva]: If I could get that data. [Chris Dalla Riva]: I could get that data. [Chris Dalla Riva]: Yeah. [Chris Dalla Riva]: So there's a lot of stuff like that where...

52:07[Chris Dalla Riva]: I can't get the data, and I'm at least like, well, there's something interesting here that I can write about and not quantify in the way that I was hoping to. [Chris Dalla Riva]: But yeah, there's sort of a laundry list of topics like that. [Tim Wilson]: Well, man, I feel like we could ask a million more questions. [Tim Wilson]: Plus, it's just fun to have somebody who's got a near encyclopedic reference point for examples of X, Y, and Z on the music front.

52:37[Tim Wilson]: But now we're gonna actually take a quick break with our friend Michael Kaminski from ReCast, the MMM and GeoLift platform, helping teams forecast accurately and make better decisions. [Tim Wilson]: Michael's sharing bite-sized marketing science lessons over the coming months to help you measure smarter. [Tim Wilson]: So Michael, over to you. [Michael Kaminsky (Recast)]: In our last measurement byte, we talked about the fundamental problem of causal inference and how our inability to control for unobserved differences across individuals makes observational causal inference either extremely difficult or just impossible.

53:10[Michael Kaminsky (Recast)]: The beauty of randomization is that, in an experimental setting, if we're able to truly randomize across individuals, we don't have to do any statistical adjustments at all. [Michael Kaminsky (Recast)]: That randomization takes care of adjusting for observed confounders is of enormous utility, but that it takes care of adjusting for unobserved confounders is truly miraculous. [Michael Kaminsky (Recast)]: And the reason why is beautifully simple.

53:30[Michael Kaminsky (Recast)]: With large enough sample sizes, if we can truly randomize treatment, all of those individual differences will simply average out between our treatment and control group. [Michael Kaminsky (Recast)]: and we can empirically show this either with a mathematical proof or via simulation and code. [Michael Kaminsky (Recast)]: The magic is that since this works for everything we can observe, we know it will also work for everything we can't observe.

53:49[Michael Kaminsky (Recast)]: This is the magic of randomization, and that's why a randomized experimental design is always the first stop of every researcher. [Michael Kaminsky (Recast)]: It just works. [Michael Kaminsky (Recast)]: It not only handles the hard work of statistically adjusting for observed confounders, but without any extra effort, it works the miracle of adjusting for your unobserved confounders as well. [Tim Wilson]: All right, so if you enjoyed that mini lesson, Michael and the team at Recast have put together a library of marketing science content specifically for analytics power hour listeners.

54:17[Tim Wilson]: For everything from building MMMs in-house to communicating uncertainty to your board, head over to www.getrecast.com slash aph. [Tim Wilson]: That's www.getrecast.com slash aph. [Tim Wilson]: So now the last thing we do on the show is go around the horn and share a last call, something that you've read or seen or heard or thought about that might be of interest to our users. [Tim Wilson]: And Chris, you're kind of just a fountain of last calls on this whole episode.

54:49[Tim Wilson]: So, but do you have a last call, something you haven't shared that you'd like to share? [Chris Dalla Riva]: Yeah, there's this very, very popular music YouTuber named Rick Beato. [Chris Dalla Riva]: Also, this has nothing to do with analytics, but for some reason I think people may enjoy this. [Chris Dalla Riva]: Rick Beato is very, I think he's probably the most subscribed to person on YouTube that just talks about music. [Chris Dalla Riva]: It is a lot of great stuff, but he's been in a war with universal music recently because they've been filing copyright claims on his videos because he usually has like 10 seconds snippets of songs and he's been posting about.

55:26[Chris Dalla Riva]: them trying to take down these videos. [Chris Dalla Riva]: And there hasn't been a resolution yet, but there's been a couple videos and then other people in the music YouTube space have been posting, backing them up saying this should be fair use. [Chris Dalla Riva]: So I've wrote about this a little, but I've been watching with bated breath to try to figure out what's going on here. [Chris Dalla Riva]: Like he's definitely providing traffic to music in the universal catalog.

55:53[Chris Dalla Riva]: So it doesn't seem like something they should really care about. [Chris Dalla Riva]: given that the ad revenue they would generate from his videos would be a rounding error on their balance sheet. [Chris Dalla Riva]: So I'm just curious to see where this goes. [Chris Dalla Riva]: But I just checked, right before this, I just checked. [Chris Dalla Riva]: I don't know when this is going to come out, but there was no update up to this moment.

56:13[Chris Dalla Riva]: But when this comes out, maybe you could see if Rick Beato has resolved his issues. [Tim Wilson]: Well, and you did, we'll link to the newsletter that you did about that so people can refer. [Tim Wilson]: That was kind of a fascinating one about what the options are when you push. [Tim Wilson]: music. [Tim Wilson]: The reason you can find that stuff on YouTube is because the person who uploads it can say, I want to leave it up, but any ad revenue goes to the rights holder for the music.

56:44[Tim Wilson]: Is that right? [Chris Dalla Riva]: Yeah, yeah. [Chris Dalla Riva]: That's generally right. [Chris Dalla Riva]: If I use 30 seconds of a [Chris Dalla Riva]: Chapel Roan song, you know, her people can claim the revenue from the video and they can say, all right, you can leave it up, but we're going to collect the money. [Chris Dalla Riva]: But usually 10 seconds and it's criticism, you know, that should be in my rudimentary understanding of fair use.

57:06[Chris Dalla Riva]: It should be fair use. [Chris Dalla Riva]: But here we are. [Tim Wilson]: Here we are. [Tim Wilson]: Nice. [Tim Wilson]: Val, what about you? [Tim Wilson]: What's your last call? [Val Kroll]: All right, so this one is actually related to the topic. [Val Kroll]: One thing that I always find so interesting when it comes to music and thinking about quantification is genre. [Val Kroll]: And however many genres you think there are of music, there's like a hundred more than whatever that number is.

57:32[Val Kroll]: And there's this website called Every Noise at Once. [Val Kroll]: Have you heard of this one, Chris? [Chris Dalla Riva]: Oh, I am intimately familiar with every noise. [Val Kroll]: So this site has, it's a visual kind of display of every genre that exists. [Val Kroll]: And you can click it and it will play like examples of those songs or you can like search for an artist to figure out exactly where they fall. [Val Kroll]: in the spirit of like quantification of genres is kind of a fun thing to play around to figure out like what is the difference between techno rave hard industrial techno and belgium techno well turns out a lot a lot is different so anyways it's kind of just a fun thing if you're looking to burn 10 minutes or however deep in your hole you get maybe an hour in my case so [Tim Wilson]: Just thinking if you homeschooled Abby, how that would somehow be part of the core curriculum for when she turns eight.

58:29[Tim Wilson]: You bet. [Tim Wilson]: I love that. [Tim Wilson]: Nice. [Tim Wilson]: What about you, Julie? [Tim Wilson]: What's your last call? [Julie Hoyer]: Well, I wish I was. [Julie Hoyer]: on trend and had something about music. [Julie Hoyer]: It'd be much more fun. [Julie Hoyer]: But actually, this one does loop back to you, Chris. [Julie Hoyer]: I was reading your newsletter, and you had made a shout out for BI bytes, and you had linked to an article by them about time series data.

58:54[Julie Hoyer]: And so I was reading through that, and I actually thought it was a really good article. [Julie Hoyer]: It's called Same Data, Different Questions, Transforming, Time Series Data for Better Insights. [Julie Hoyer]: And I love that it was because we talk about time series data a lot, especially in the industry that we work in. [Julie Hoyer]: It's just something you run up against. [Julie Hoyer]: And so I love anything that helps break down better ways to think about looking at time series data or how to analyze it.

59:18[Julie Hoyer]: And so I love that it was a list of [Julie Hoyer]: four to five different visuals that are really helpful when you're trying to break down and understand like, is there any significant change in this time series data? [Julie Hoyer]: So I thought that was awesome. [Julie Hoyer]: So thanks for leading me to that. [Chris Dalla Riva]: Oh, no problem. [Tim Wilson]: Yeah, Tim, what about you? [Tim Wilson]: Yeah, I missed that. [Tim Wilson]: So now I've got something to go through.

59:42[Julie Hoyer]: I love that I found something Tim didn't find. [Julie Hoyer]: So I will. [Julie Hoyer]: That's rare. [Tim Wilson]: I didn't know if one of us was going to do the Kassi Kassarkov article that we were having an exchange about, but we'll save that. [Tim Wilson]: Okay. [Tim Wilson]: Well, I will march even farther away from music with a past guest current. [Tim Wilson]: superfan of Ben Stansel, but in one of his recent newsletters he linked to something he wrote back when he was still at mode back in 2020 called a dispassionate examination of the empirical evidence regarding positional punctuation in SQL.

1:00:21[Tim Wilson]: So this was basically for [Tim Wilson]: many listeners or sequel writers. [Tim Wilson]: So the old debate around the leading or the trailing comma as to what makes more sense. [Tim Wilson]: And he basically concluded that, yes, objectively, putting a leading comma at the start of the line is like the better way to go. [Tim Wilson]: But the trailing comma is just kind of, that's kind of still what people do and it doesn't look weird.

1:00:47[Tim Wilson]: So it's funny because he's a hilarious writer, but I did want to go ahead and quote the way that he wrapped it up, said, so the next time you find yourself questioning where commas go in SQL, SQL query select statements, the answer is simple. [Tim Wilson]: While leaders lead with leading commas and trailing commas are leading signs of failing lines and the tail lines, no matter the database breed, we're not agreed that it's best to concede to lead because the more we scale our query needing, the more we follow the trail to trailing from leading.

1:01:16[Tim Wilson]: because it's people who do the reading. [Tim Wilson]: And that was written pre-LLMs hitting the mainstream, but it's... Nicely done. [Tim Wilson]: Yeah. [Tim Wilson]: So, all right. [Tim Wilson]: And with that, thank you, Chris, again, for coming on. [Tim Wilson]: I had high expectations for how much fun this would be, and it exceeded those dramatically. [Tim Wilson]: So, thanks for coming on. [Chris Dalla Riva]: Oh, it was a pleasure even though I do use trailing commas in my SQL queries.

1:01:57[Tim Wilson]: As do I. I think, yeah, it's a fun, I mean, it's actually kind of an empirical analysis. [Tim Wilson]: So he does, he pulls from different places. [Tim Wilson]: So it actually, maybe there's a little bit of a link to a similarly trying to answer a question that maybe doesn't have deep consequence, but he dug into it anyway. [Tim Wilson]: So thanks for coming on. [Tim Wilson]: That was a great discussion. [Tim Wilson]: We'll have links to your newsletter and the book.

1:02:23[Tim Wilson]: And yeah, while I was just thinking about that, I was like, am I going to link to every single song or album that was referenced? [Tim Wilson]: And I will tell you, no, probably not. [Val Kroll]: It's not as thorough as Chris's data set. [Tim Wilson]: Oh, that. [Tim Wilson]: Have you considered or have you or are you going to ever like publish or share the data set itself? [Chris Dalla Riva]: Oh, it's out there. [Chris Dalla Riva]: I would love if you shared.

1:02:51[Chris Dalla Riva]: It's just in a Google sheet. [Chris Dalla Riva]: Anyone can use it. [Tim Wilson]: Okay. [Tim Wilson]: We will definitely add that for now. [Tim Wilson]: I wish I'd taken a look at that before. [Val Kroll]: Yeah. [Tim Wilson]: So many more questions. [Tim Wilson]: Okay. [Tim Wilson]: So for that next book, we'll have you back. [Tim Wilson]: So everyone out there, thanks for listening. [Tim Wilson]: As always, we would appreciate, love to have a review or a rating or both on the platform that you listen on.

1:03:21[Tim Wilson]: Should that be a possibility? [Tim Wilson]: We do kind of ebbs and flows on our end, the volume of requests for podcast stickers that we get. [Tim Wilson]: But if you go to our website, there's a simple link in the global nav and we'd be happy to send you [Tim Wilson]: a sticker or three or four for free, just fill in a little form. [Tim Wilson]: I am hosting this, so I'll go ahead and say, if you haven't bought a copy of Analytics the Right Way, a business leaders guide to putting data to productive use by yours truly and Joe Sutherland, the holidays are coming and nothing is the perfect stocking stuff or like a book on analytics.

1:03:59[Tim Wilson]: We'd love to hear from you. [Tim Wilson]: Feel free to reach out to us on LinkedIn. [Tim Wilson]: You can reach out through the podcast page. [Tim Wilson]: You can reach out to any of us as individuals. [Tim Wilson]: You can reach out on the measure Slack. [Tim Wilson]: You can just send us an email at contact at analyticshour.io. [Tim Wilson]: So regardless of what [Tim Wilson]: what era, what decade you are stuck in listening to and thinking about, and now you're gonna go back and re-listen to and analyze and whatever songs you're not, you're listening to and getting distracted by when you should be looking at the data.

1:04:33[Tim Wilson]: For Julie, for Val, I'm Tim. [Tim Wilson]: Keep analyzing. [Announcer]: Thanks for listening. [Announcer]: Let's keep the conversation going with your comments, suggestions, and questions on Twitter at @analyticshour on the web at analyticshour.io, our LinkedIn group, and the Measure Chat Slack group. [Announcer]: Music for the podcast by Josh Crowhurst. [Charles Barkley]: Those smart guys wanted to fit in, so they made up a term called analytics.

1:05:00[Charles Barkley]: Analytics don't work. [Charles Barkley]: Do the analytics say go for it, no matter who's going for it? [Charles Barkley]: So if you and I were on the field, the analytics say go for it. [Charles Barkley]: It's the stupidest, laziest, lamest thing I've ever heard for reasoning in competition. [Tim Wilson]: You should tell that story to, although he probably has everybody tells him their like quirky billboard stories now that. [Val Kroll]: I was telling, do people tell you all the time?

1:05:28[Chris Dalla Riva]: No, no, I'm curious what this is gonna be. [Val Kroll]: You're like, it's one of two directions. [Val Kroll]: No, I'll try to be brief. [Val Kroll]: When I was in sixth grade, I went to CD Warehouse with my allowance and bought the Billboard top 10 CDs from 1960 to 1969. [Val Kroll]: It just became obsessed. [Val Kroll]: And so on Fridays, for music class, everyone could bring a CD. [Val Kroll]: We wrote the names of the board, teacher would draw a number, you got to play your song.

1:05:53[Val Kroll]: and the week that the new Spice Girls album came out, I brought Billboard 1965 and played Eve of Destruction, which is like a very heavy topic protest song that's about four and a half minutes long. [Val Kroll]: And it wasn't the favorite of the people in the class. [Val Kroll]: Surprisingly, to my surprise, this is not what everyone was dying to hear. [Val Kroll]: But I was obsessed with it. [Tim Wilson]: That's awesome. [Tim Wilson]: And he said the bullying was already happening.

1:06:23[Tim Wilson]: Oh, yeah. [Tim Wilson]: Or that's what. [Tim Wilson]: Yeah. [Tim Wilson]: That's good. [Tim Wilson]: And that really helped. [Val Kroll]: I couldn't figure out what what I was what I was doing wrong, you know. [Tim Wilson]: I mean, if you made that choice, it feels like maybe maybe there are other choices being made. [Val Kroll]: should have been like, okay, all right, maybe right. [Val Kroll]: Oh boy. [Tim Wilson]: All right. [Tim Wilson]: Okay.

1:06:53[Tim Wilson]: With that, I really wanted to have that recorded. [Tim Wilson]: I've heard that now three times. [Val Kroll]: Never on it's still funny. [Val Kroll]: Yeah, it's good. [Val Kroll]: Maybe I'll give you a couple bars at the end in my best Barry voice, or what's his name, Barry? [Tim Wilson]: That's gonna be your last call. [Tim Wilson]: There's this hot song. [Val Kroll]: Yeah, it's a tick tock sound, but yeah. [Tim Wilson]: Rocked flag and disco duck.