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- [00:01]
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- [01:07]
Ari Poparo
Welcome to the Market Extra podcast. This is Ari Poparo. I hope everyone's having a good July 4th. Last week we just did the news, so we didn't have a guest. And now this week we're just having a guest and not doing the news. So we're trying to mix it all up. It's been a slow news week because of July 4th, obviously, and Eric Franti is off with his family, so it's just me. So this week I'm pretty excited because we have Justin Evans, who probably most listeners of this podcast have run into or worked with or know. Justin is an expert in everything about data. I crossed paths with him at Nielsen. He was also a collective, the ad network Comcast, Spotlight. Him and I have a habit of like, working at the same company at slightly different times. He's currently the head of innovation and insights at Samsung Ads. But the reason we're having here has nothing to do with any of that. It is because he has a new book out. It's called the Little Book of Data and it's about, as he says, it's not about number crunching, it's about ideas. So we want to hear about this new book, the Little Book of Data, how it's relevant to our lives, what it has to do with ad tag, if anything, and just generally catch up with Justin. So I'm pretty excited to have him here on the data theme. Next week we're going to bring back our normal sort of programming format and we have Chris Feo of Experian, so we'll hear his take on data. And. And the whole thing is pretty ironic because I just said last week to someone, I'm not sure who, that I hated having data people on this podcast because they tend to not say anything. So I'll also ask Justin about that. Without further ado, let's bring on Justin Evans, the author of The Little Book of Data. Justin, thanks for being here.
- [02:44]
Justin Evans
Hey, thanks for having me. It's great to be here. Appreciate it.
- [02:47]
Ari Poparo
Yeah, of course. You doing anything fun for the 4th?
- [02:49]
Justin Evans
I am doing everything I can to keep my dog from losing his mind in all the fireworks.
- [02:57]
Ari Poparo
Dog's least favorite holiday, you know, while I have you. What do you think dog's favorite holiday is? Halloween.
- [03:02]
Justin Evans
I think it's Thanksgiving. It's a day of roasted meats. In fact, that's what I think they call it among themselves, the Day of roasted Meats.
- [03:10]
Ari Poparo
It's coming up. We don't know why, but grandma will be here and we might get some turkey. I appreciate that. That's my favorite holiday, too. So what made you want to do this? Well, I mean, I'm the worst person to ask this, but it's crazy to write a book. I just wrote a book. So why'd you write a book?
- [03:24]
Justin Evans
I started to have this moment when I was at Comcast when I saw this very traditional business pivot and become a data centric, digital centric business. And I really saw a lot of change in the personnel in the company based on how well people understood data, felt comfortable with data, felt that they could integrate data into the way they worked. And some of that was perfectly appropriate, like people were not changing with the times. But some of it was actually kind of a bummer. There were people who were fantastic professionals, great leaders, who just didn't seem to be able to stomach the change. And then I saw that echoed a little bit in my personal life around New York City, where, you know, not all my friends are ed tech people, they're therapists, they're screenwriters, they are nonprofit leaders and so on. And I saw the same sort of split where some people were comfortable with data and AI and some people were not. And it seemed to have this kind of dividing effect on people's career. Tenure.
- [04:29]
Ari Poparo
Sure.
- [04:30]
Justin Evans
So I, I, that was kind of the impetus for me starting to take notes and say, well, how, how could I talk to myself 20 years ago when I was just starting the business and express what the kind of core ideas of data are? And, and by the way, are their core ideas of data? And I started to make notes and started to try and really, really distill what those ideas were? And then I wanted to do an extra thing with it, which is early drafts that were kind of dry and explanatory I thought would be elegantly simple. It turns out they weren't. And then I took the pivot to try and make the book of kind of like the Freakonomics for data. And so I found stories that would, that would illustrate the core concepts that I was sketching down. And that had another benefit to me. And you mentioned ad tech a couple of times, which is to get my head out of ad tech. I love ad tech. It's been a wonderful career and I, it's continues to be dynamic and change, but at the same time I wanted to kind of try to see how well these data concepts that we've learned in ad tech play outside of ad tech in the world of medicine and health and, and other areas. And that was part of the fun that I got to interview these experts from other areas of endeavor to illustrate ideas that I've crystallized From my, my 20 year career in adtech and data.
- [06:01]
Ari Poparo
That's awesome that you were able to apply learnings from ad tech outside of it, because I'm still trying to convince my therapist to track his clicks better, but unsuccessfully. Tell me. So you mentioned there's these core learnings or core principles. Walk us through a couple of those.
- [06:16]
Justin Evans
Yeah. So the four that are arguably the funnest in the book are the four data superpowers. And I really tried to distill what data does for us that we care about. And I came away thinking that they were like Prometheus and fire or electricity in the 20th century. It really was this foundational gift to our species. One of the superpowers is data gives us the power of omniscience. It allows us to in effect, see and know things from far flung parts of our existence. The ad tech example would be you have a client who is a retailer and they're getting sales data potentially attached to an ID and a loyalty card number from every single chain in their store. And that's something that we're accustomed to. But when you think about it, and maybe you think about it in terms of say, climate science, where you have 185,000 weather stations around the globe that are contributing data that allows us to solve a big problem or at least address a big problem like climate change. You really put it in perspective that this data capability becomes a superpower for the species.
- [07:31]
Ari Poparo
I was actually just thinking about this. I was on a ferry across island ferry just yesterday and we went right by a lighthouse. And obviously lighthouses are antiquated, but they're antiquated because there's more information. You don't just have to use your eyes to know what the information is. And that seems very analogous to what you're saying.
- [07:50]
Justin Evans
Yeah, and the other, other sections of the book deal with just the core use cases like counting and matching and scoring. And so it was fun to go back into my own professional history, like at Nielsen, of course, was obvious for me to go into the counting concept and to set up some juxtapositions for some of the other ones, like for matching. I talked to a biotech executive who had found or to help to find the linkages between genomics and cancer. And what was happening around the time she was doing her work was. And by the way, some of these stories had emotional components. Like this, this biotech executive, her, her younger sister had died of cancer in an untimely fashion. She wasn't even a smoker, she was like a singer. And she went to nightclubs. Secondhand smoke gave her cancer and she died. And it was a tragedy for my friend. And I talked to her about her work in, in, in cancer and genomics. And they really made a big breakthrough because, because in those days, everybody treated all lung cancers like they were lung cancers. And what the breakthrough was during this period in the teens was cancers are not organ cancers, they are genomic cancers. So when there is a genetic modification, there's a genetic mutation, it will drive a certain level of cancers. And it kind of goes horizontally if you were to think about it like so you have the organs vertically and the, and the, and the genomic mutations going horizontally. And it was much more predictive of what would be a powerful treatment for these cancers. And so what my friend had done was basically set up this. A equals B equals C transitive property of matching a database between the genetic mutation, the cancer, and then the treatment that treated that particular genetic mutation. And I'm like, my gosh, this is just like appending data to a customer database. And so the, the kind of riff in that chapter is basically how has direct marketing like curing cancer.
- [10:03]
Ari Poparo
So I want to, I want to delve into the psychology aspects, but also the skills aspects because I think what you said about your experience at Comcast was interesting. You were in the spotlight division, which is historically the area that sells the local advertisers. And the old version of that, the pre Internet version of that, was amazingly simple. You're basically just selling TV spots. And then that division had to transform to being data driven because people are watching less tv. Was it that some people are quantitative and some people are not and that just is some immutable part of who they are or can they learn? Are there other skills? Is it just a willingness to adapt? What did you find in your experience at Comcast, but also your research elsewhere?
- [10:51]
Justin Evans
The purpose of the book is to tell enough of these stories about how people think about data that when you read 20 of them back to back, hopefully it should sink in. Just like reading 20 Sherlock Holmes stories, you begin to think like a detective. And I really do think these handful of ideas that drive using data are common. So I don't think it's a quantitative mindset that's required. In fact, that's the opposite of what I'm trying to say. You don't need a computer science degree or a math degree or a stats degree to be able to understand data. You just need to understand these core ideas about how to manipulate it. So the focus should come on confidence in thinking that you can address data. An imperative that everybody who uses data as a expert or a non expert speaks English about it, or at least speaks business about it, because it should not be a jargon driven, acronym driven, vendor driven, product driven approach. It should be about business. And then the last thing is a respect for business knowledge and domain knowledge, sort of. I was an English major undergrad, and I actually think that's been a kind of a weird driver of my own career success. And except that I have it because I've been the person who's explained to the client in the market what data does. And the client should always demand that they be spoken to in English and also recognize that they know their business, even if they don't know data. And the business drives the use case.
- [12:36]
Ari Poparo
Yeah. So how does that kind of common sense business knowledge help with the data analysis? Is that part of the whole package?
- [12:45]
Justin Evans
Yeah. One of the stories I tell in the book is the experience they had at Nielsen when we were taken over by private equity. Were you before that time, Ari?
- [12:57]
Ari Poparo
Oh, God, I blocked it all out.
- [12:59]
Justin Evans
It was like 05 06.
- [13:01]
Ari Poparo
Yeah, no, I was after that time.
- [13:02]
Justin Evans
You're after that. So I had these experiences where, you know, the private equity guys would come into the boardroom and they were, they ran real deep. It was like Carlisle and Tommy Lee and KKR and Blackstone, all of them. And they had like a hundred bankers in the room, and on the other side of the table they would have a Nielsen data expert. And everybody in Nielsen knew what happens when private equity takes over your company. You know, you have a 40% chance of getting fired. And so these guys were sitting there across the table and trying to dance and trying to dazzle the bankers who knew nothing about data until the bankers kind of gave up and said, okay, no one can understand this business but this executive, and therefore he gets to keep his job. But the bankers were having none of it. And so the bankers sat there and said, okay, you know, tell me about your product. And they're like, oh, you couldn't possibly understand. It has a hundred data sources and a hundred different algorithms in it. And they're like, great, well, let's start with the first one. And they just sat there and bashed through all 100 data sources, all hundred algorithms, until it was all out there on the table, all the equipment. And it just was the lesson to me with everything can be picked apart and everything can be understood by. By even the non expert.
- [14:10]
Ari Poparo
Yeah, that's an interesting example. I definitely think that the most important trait in a private equity person is stubbornness and patience from my experience as well, but that's a different story. So how do you compare the data challenges in ad tech to those in other sectors, like biology? I've often thought that ad tech might be the hardest domain out there because of the amount of data, the flexibility, the messiness, and the need to respond in speed. What do you think of that assertion?
- [14:42]
Justin Evans
My inspiration for having confidence that what we learned in marketing and advertising applies to other domains was actually watching the career of Travis May, who, you know, he was the CEO of Liveramp as a very young man and pivoted and founded a company called Datavant, which is effect, in effect, Liveramp for medicine. They would tokenize and anonymize medical data even at the patient level, coming in in massive quantities, and allow players in the healthcare space to really kind of like run really massive experiments on anonymized data. And it helped those companies skip over steps where they had to do elaborate clinical trials in order to find a cure for a disease. They would actually be able to test it on historical data because they would find people with the condition and see what if, if a certain kind of natural experiment was taking place, whether their outcomes statistically were more positive. And I found that a really inspirational example. And I guess I didn't quite do like a wonderful end analysis between biotech and edtech or public health and ed tech. But what I did find is that the language between the woman who is the head epidemiologist at the Bureau of Communicable Diseases and someone from ad tech made sense and we could speak to each other. The entrepreneur who created a loneliness score based on his own father's untimely demise and help trying to help other seniors and senior centers by Scoring how lonely they are. Like there was, there was a language there. So I, I came away with a lot of confidence that these data concepts are completely universal and that I agree with you. I think we might be kind of in the, in the over training sector. I think, I think what we're learning is very fast, very big, and very applicable to these other areas.
- [16:43]
Ari Poparo
If there's one thing that the ad tech listeners of this podcast could take away, what would it be?
- [16:48]
Justin Evans
I think that we all have an opportunity to step back from the real nitty gritty minutia of what we do and have an opportunity to think more innovatively about how we can be helping the marketer. I think that as we get away, step away from data and think about use cases, I think there are ways for us to answer virtually any question a marketer has, especially now with AI tools. And so ironically, as a data person, I think that we should think less like data people and think more like business people and focus on business problems.
- [17:29]
Ari Poparo
Fascinating. So when I was researching this episode, I was on Amazon and I clicked on your author link and surprisingly, this is not your first book and it is your first data book, but there were two other books from your past. So how long have you been an author and what was the. Well, tell us about your previous works.
- [17:49]
Justin Evans
I really have always desperately wanted to be a novelist. And when I got out of school, I thought the path to fame and fortune was going to be to be a spy novelist. And it didn't occur to me that not knowing a single thing about the world of intelligence would be a problem. So I, after a few rejections, I looked for a way to write suspense fiction that would play to something I knew, or at least I. I knew relatively as much as anybody else. So I look to my Southern heritage and the crazy gothic stories of my father. As a. As a Georgia native told me in. In my Virginia native home, small hometown. And I, I wrote a couple of kind of gothic suspense novels. One is about demon possession and another is about a ghost.
- [18:40]
Ari Poparo
It would be quite a coup if you can write a thriller, a data thriller, because we know there are legal thrillers and intelligence throwers and military thrillers, but if you could get a guy sitting in front of big table to solve some world problems, I would take my hat off for you.
- [18:57]
Justin Evans
All right, well, challenge accepted.
- [18:59]
Ari Poparo
Challenge accepted. I mean, obviously Big Data would be just being a pretty easy name for the book. There's probably a million puns you could use for the name of the book. But I look forward to it. So thank you so much for being here. So Justin Evans, the author of the Little Book of Data. And this is available now, right? You could go on Amazon right now and buy it.
- [19:19]
Justin Evans
You sure can. It's available in hardcover and in audiobook where you can hear me sweat through two days of reading my own book, which is actually.
- [19:29]
Ari Poparo
Well, okay, I'm not gonna let you go yet. I have one follow up question because now I have a book coming out if those have been living under a rock. My book Yield is coming out on August 5th. I found the audiobook recording to be one of the most difficult things I've done in years. How did you do?
- [19:44]
Justin Evans
I had a great time. I mean, it was incredibly hard. By the end of the two days, you just want to have a Martini iv. But it was fun for me because I was a big Harry Potter fan. I read the Harry Potter books to both my kids and so I've been twice through them, once for myself, and that was the studio where Jim Dale read the Harry Potter books. So I had this thrill of being in the same studio that my favorite audiobook recording of all time had been recorded in.
- [20:14]
Ari Poparo
Oh wow. Mine was spread out over like two or three weeks, so it was really grueling two hours at a time. I couldn't possibly have done it in two full days. I would have lost my mind.
- [20:23]
Justin Evans
I did lose my mind. Yes, you would have.
- [20:25]
Ari Poparo
But nevertheless, it's an audiobook. You could download it anywhere you download audiobooks. So again, Justin, thank you so much for being here.
- [20:34]
Justin Evans
Thank you so much. Thank you for subscribing to marketecture.
- [20:37]
Ari Poparo
New interviews are added every week at.
- [20:39]
Justin Evans
Markitecture TV in your favorite podcasting app.
- [20:51]
Ari Poparo
Thank you for listening to the Market Podcast. New episodes come out every Friday and an insightful vendor interview is published each Monday. You can subscribe to our library of hundreds of executive interviews at marketecture tv. You can also sign up for free for our weekly newsletter with my original strategic insights on the week's news at News Market tv. And if you're feeling social, we operate a vibrant Slack community that you can apply to join@adtechgod.com.