Measuring Trust and Audience Behavior with Andy Asaro

Speaker A: Hello everyone, and welcome to the Marketing Roundtable, a digital marketing podcast. My name is Brandon Jones and I'm the producer and I'm also a paid media strategist. And I'm going to hand it over to Brian Cosgrove, the host for today.

Speaker B: Hi, I'm Brian Cosgrove. I'm principal, um, and founder of Braindew and a web analytics strategist. And I'm here to talk today with Andy Asaro.

Speaker C: Hi. Uh, thanks very much, Brandon and Brian. I'm Andy, uh, I am currently, uh, the global executive director at Conde Nast, uh, which is a portfolio of brands that include, uh, Vogue, gq, New, uh, Yorker and others. Uh, and I'm very excited to speak with you today.

Speaker B: So Andy, I would love if you could share with the audience a little bit more about, in your career to get to this director position at one of the largest publishers, I guess, um, in print ever, um, how you got into this analytics role in this career and you know, kind of starting earlier on so that people that are in various stages of their career that are listening now can kind of see what the path looks like.

Speaker C: I was always interested in media and specifically the effect that it had on me, uh, as someone growing up. Uh, and it was just something that interested me. Um, and it occurred to me that we take for granted the effect that uh, a piece of art, for example, or any kind of media has on us. Uh, and so I asked the question why I wanted to unpack that. And so, uh, throughout school I was a, uh, comp. Lit, uh, major, for example, where I, uh, was using literary theory to try to unpack novels and poems. Um, and media is just another, uh, system of, uh, text that you can also apply, uh, similar approaches to. And so that's what I tried to do. I was always very interested in that. It was always a bit, bit, uh, about qualitative analysis and research. And so, uh, as I was leaving school, uh, the opportunities in front of me were in those terms. That's what I was good at. So, for example, I was a business researcher at Ernst and Young, an accounting firm. Uh, and then afterward I was, uh, working as a researcher at Gartner, an IT research firm. Um, so it didn't necessarily have the technical aspects that, um, you might expect, uh, in someone who would eventually get into analytics. I was very fortunate that, uh, also as a young person I got really into developing websites, uh, others. Uh, yeah. And uh, you know, and over the course of doing that, of course they wanted to understand how their websites were performing Forming, uh, and sort. Uh, so I, I essentially, you know, was self taught, uh, and became familiar with some of the metrics that matter and things like that.

Speaker B: Um, uh, and sorry, I just, I want to pause there because there's a lot to unpack. So it's interesting. You came from very much the humanities, you know, sort of not from a quant, not from a straight math background, not from a stats background. People listening today, you know, it's interesting to hear that you can get into this industry and you can kind of excel and get to the level that you're at, even if you didn't come specifically from that side. What's in, what is the crossover point seems to be that qualitative analysis and just analysis in general. And so academic rigor sort of brought some of that out and kind of gave you a step in the right direction. So I'm kind of curious about this transition here.

Speaker C: Yeah, absolutely. Um, yeah, I would say, like there is, uh, a lot of rigor that can be applied, uh, qualitatively. And so for example, uh, I think one theme that will emerge, uh, throughout the conversation is the importance of having a good framework, uh, for analyzing something. Because, uh, you can measure all sorts of things by understanding which things, things are important to measure, uh, and how they fit with other things that you're measuring. To tell a story about, uh, the audience or about what kinds of content, um, uh, are relevant to those audiences and how that content works. You need to have a, almost qualitative framework that I feel like I established through my uh, studies, uh, in the humanities.

Speaker B: Now, to go from there to this position at Ernst and Young. Tell me a little bit about. Did you just apply to some, to a listing you saw online somewhere? What was kind of the original job title that you saw? And then how did. Obviously you did well in the interview that you were able to join the team, um, how were you able to sell kind of your background doing this qualitative research academically into that position at a, as you said, kind of more of an accounting, you know, focus at that time.

Speaker C: Yeah. Uh, so essentially I, uh, was looking for a job in research, um, and there was this concept of business research. And so you can imagine Ernst and Young, you have different practitioners, accountants, uh, risk, uh, advisory services, things along those lines. Um, but in order to understand again, where to apply those, uh, more quantitative, um, practices, uh, they need to have some understanding of, um, who the addressable audience is for those services. Uh, and so that entailed a, uh, lot of research of individuals at Companies, the companies themselves, overall market trends. I can give you an example, um, where one of my jobs was every day to look through uh, all the different articles that had been published about particular topics like insurance. Uh, sure. And to make that digestible for the practitioners. So to take that and to summarize what the themes were, uh, to uh, figure out a way to do that such that um, the audience for that report would actually consume it and take something away from it. Uh, that really got me into this habit of understanding it's not just throwing information at folks. You really need to understand uh, what your stakeholders are going to do with that information. Um, and so there's an example of something that you might consider a company that you might consider to be a more quantitatively oriented one that has ah, a qualitative function like research, ah, which I was cut out to do just uh, given my academic background.

Speaker B: Yeah, no, that makes a lot of sense. But it's also important for people to realize that, to look for those opportunities, um, you know, to make the leap that doesn't, you know, it's not like you're, you were an accounting major, you know, and yet here you are working at Ernst and Young. And now Ernst and Young has a pretty good reputation even in our, you know, analytics space, doing a lot of digital analytics consulting. They've kind of grown from there. Uh, but when you started earlier on, it sounds like they were still very much in this business research and more in this accounting financial world.

Speaker C: Yes, uh, that's right. They had, uh, I believe it was called Capgemini. Uh, but to your point, uh, if I were to give someone advice on how to get into analytics, I actually, I'm not sure I would recommend focusing so much on technical skills. Those are, are important. But I will tell you that again, it really is uh, uh, the more qualitative skills that are required to figure out how to, how to frame measurement, how to make sure that the information is digestible, that it, that it means something. Uh, I think we'll, we'll talk about uh, how for example, uh, vanity metrics, uh, uh, are something that uh, happen a lot. Um, and that's because they're not tethered to a ah, framework, a way of thinking about the why behind the what. Uh, and so a focus on those softer skills, those more qualitative skills I think is really important. Especially as AI comes, continues to evolve and potentially um, start starts uh, replacing some of these harder skills, more technical skills. Uh, I know, maybe we shouldn't go there.

Speaker B: No, I think that's great. Honestly, what I, uh, getting out of that is some of this research that you were doing before, you're reading a lot of different articles and you were summarizing them. And to me that's like immediately the first thing that comes to mind is, but you can throw them into Blender and have it extract themes and things like that. The interesting part though is to be able to craft the perfect prompt means you need to be doing a lot of deep thinking if you're going to achieve what you were describing, which is understanding the stakeholder, understanding the context, understanding what value they're going to take from it. And so even then it's like, I feel like all the prompt engineering or having the best LLMs in the world, they can't tell you, uh, how to pace the reality of all of these different individual stakeholders. And there's no straightforward way to take everything that you've perceived that you subconsciously and consciously about the people you're talking to and get that in there easily.

Speaker C: Yeah, I think that's, that's right. I think uh, a couple of things. One, that prompt, uh, engineering is all about precision and a precision with, with language. And so uh, the more practice you have with language and the more practice you have with asking the right kinds of questions, the more effective you'll be using an AI tool. Uh, and uh, you're absolutely right. Uh, and then the, the questions that you ask need to be tethered to the outcome that you're trying to drive on behalf of your stakeholders based on your conversations with them and what they need and understanding of how they digest information. Some folks will uh, prefer a deck and others an email and um, figuring out how best they consume information such that they can drive the outcomes that they're coming to you for help with. Uh, and it really requires ah, and emotional intelligence, frankly, that you can also um, get by reading novels and poems and engaging the humanities. Um, a lot of these skills are extremely important, increasingly important in uh, this environment where automation is becoming more and more pronounced.

Speaker B: So I think that's a great. So to go from there, you're Ernst and Young. You've brought your humanities to bear. You're doing great research. You're able to do things that again LLMs can help with today. But you brought all of that emotional intelligence and intuition and understanding around language to the table. Other people I think, should be able to relate to that part. How do you get from m there, you know, to your next stage? How do you get from there to media? Because that you're still not quite in media yet. But the one media tie in is the fact that you're reading all these articles.

Speaker C: Yes, that's right. I'm consuming media in order to enable, uh, accountants and risk, uh, advisors and all of that. For sure. Yeah. I think like, uh, the missing link, um. Um, that is required ultimately is some technical ability. So after Ernst and Young, ah, I went back to school and, um, I essentially did media studies at a graduate level. And, uh, one of the courses I took was about something called procedural rhetoric. Uh, and this idea that you could convince someone of your position if you could just figure out a way to have them go through the. Through a certain procedure that would, uh, give them the insight into, um, what you are, um, trying to convince them of. So part of this involved, uh, things like video games, uh, things of that nature. Right. Because in playing a certain video game, uh, you can take someone through an experience and convince them of a point of view, uh, to the point where they could even, uh, start producing tv, uh, series about these, uh. About these video games.

Speaker B: I actually want to kind of lean into that for a minute. So, uh, what procedural rhetoric sounds like it was kind of like a pivotal course in your grad studies. It seems like it's one of the ones that really helped you moving forward. And my understanding of what that sounds like is that you have a process or a more structured way to make a case for a particular viewpoint or insight that you're trying to get across. And then you mentioned that video games are kind of an interesting vehicle to be able to communicate, um, you know, particular perspective or view. And so I'm curious a little bit, just how does that work? Like, tell me a story of a video game communicating a, uh, perspective that maybe would help our audience follow.

Speaker C: Yeah, for sure. Um, so I can give you the example of the video game that, uh, I got to play in graduate school as part of a class, which was, uh, an independent game called Braid B R A I D. Uh, where, uh, the sort of the, uh, gimmick, let's say, was that you can control the flow of time. Um, and it was essentially a puzzle game, uh, where you had to solve the puzzles by changing the flows of time in different ways. Um, and, um, spoiler alert. At the end of the game, the objective of which is to, uh, save the, uh, damsel in distress. Time gets reversed and, uh, uh, the protagonist is revealed to be the villain.

Speaker B: Now you're saying that at the end of the game we've got a big twist where when they reverse time. There's a very different perspective that emerges. And to your point you're describing it as if when you look at it kind of going backwards, when you look at the flow going backwards, you see that the actual protagonist is sort of affecting. They're effectively the villain. To me it's about this. You know, the story itself viewed from different perspectives, can very much change kind of what you're supposed to take away from it.

Speaker C: Yeah, that's right.

Speaker A: Right.

Speaker C: In that case, it's subverting um, this concept of the hero saving the damsel in distress, uh, and you know, flipping it on its head and giving uh, you some insight into that, let's say form of masculinity. Uh, yeah. And uh, and so that there's an insight. And so uh, you, you work your way through this beautiful game working with time and memory and everything else. Um, and you're having your. As you go through the game you are getting insight into things like time and memory and tropes and uh, certain behaviors. Uh, and uh. And that's all through this procedure of getting from the beginning to the end of the, of the game and trying to achieve um, an objective. So as part of this class, uh, I had the opportunity to uh, produce a game of my own. Uh, and uh, this is where things start getting a bit more technical. And so what I came up with was an interactive resume. Uh, uh, I wanted to send up the concept of COVID letters in particular, which can be uh, boilerplate. And so there was this, this thing where it was a sort of a superficial story about myself. But there were opportunities to double, uh, click on, on various aspects of it to dig deeper into who I really was as a person. So for example, growing up, uh, I, I uh, was an engraver, uh, at a. Yeah, at a uh, um, at a religious goods store. Uh, for example. Um, and so what I was able to code using Javas was a uh, game where the user would have to flip the letters into in order to get them aligned correctly. And then they needed to trace the letter from beginning to end, uh, in order to uh, get to the next round, um, if that makes sense. If you can visualize engraving plates and having to flip, flip, flip everything and trace it exactly without ruining the jewelry. Um, and uh, that's really where I started making this transition to a more technical understanding of things. Uh, because uh, it was essentially cookbooking it. Right. So I wanted to do this thing, uh, and uh, Google this, that or the other thing and you start to understand how JavaScript works and how it all comes together and how you can use it to uh, to uh, to get to the result that you want in an interactive way, to create an interactive experience. Really the most amazing part about that was all that code, uh, and what emerges from it was this, uh, this procedure and this experience, uh, that gave I, I felt someone. An insight into who I was beyond the uh, the uh, the COVID letter in question. Right. Um, so that was my experience there in addition to the uh, the analytics that I had been doing as part of um, uh, the web development work that gave me pocket change during high school and college. So I always did have a bit of a technical bent, uh, but it wasn't something that I went to school for. It was something that I learned because I was interested, because I wanted to achieve an effect. Right, right. So it wasn't like just for the technical uh, thing in and of itself. It was because I wanted to use that in order to drive uh, some experience in, in uh, in either in myself or in others through a website or, or a game.

Speaker B: So I think this is really interesting because there's so many layers to this. One is that you getting into the web work that kind of came out of it was just. It was a practical thing to do, like you said, for money. It was something that was fairly accessible at the time and maybe still is for many people. And you were building basic websites when you got into the school classes. Now you're applying some of that knowledge, you're layering on top of it more advanced JavaScript, uh, interactive design. So now you're kind of taking it uh, to the next level beyond just basic brochureware webpages. And you're thinking about it uh, very differently through the lens of the procedural rhetoric. And some of what you were doing in that class, you're thinking about what people are taking away from a more interactive experience. So now you're in grad school, you're creating interactive experiences with uh, an intention to help steer perspective or to help people delve into it. Um, so how did this kind of take you to your next stage?

Speaker C: Yeah, so after graduate school I came home and uh, I didn't want to sit on my hands. I wanted to get working right away. Uh, and of course it would take time to get a job. So I decided to temp.

Speaker B: Okay.

Speaker C: And I temped at uh, and uh, an academic publisher now called Springer Nature that had an imprint called a press, which still exists, uh, which publishes specifically, um, programming textbooks, uh, and things like that. Um, so that there was Also an exposure to um, to um, all different kinds of programming languages out there through that job. But um, what they hired me to do was on the basis of my HTML and css, um, skills that I had developed, uh, uh, as part of the various side gigs, they hired me to put together their marketing emails. And so they asked me, hey, you know, you know, HTML and css, we want to have sales, uh, as in like, you know, we want to discount certain books at certain times. Uh, and we want uh, we need to blast our uh, customer base with uh, these emails, normal stuff. Uh, and what I took that as an opportunity to do was not just to put together the emails, any HTML and CSS, but to put together a web app using JavaScript that would let anybody put those emails together. Uh, yeah, yeah. And that was the, uh, that was the point at which I, uh, started establishing myself as a more technical person. Uh, but again for a reason. So not just to build uh, a web app, but because this web app would help folks do something that they thought they needed to hire a temp for. Right. Um, so always thinking about what the objective was and not the technical stuff in and of itself.

Speaker B: Right. So you effectively, there's so many layers to this. So first of all it's an imprint. So now you're technically working directly for a publisher. So now you're in the publishing business.

Speaker C: That's right, yes.

Speaker B: Right. So, so this is, this is part of how your journey, you know, played out. You're doing more work in a technical role that requires you to understand interactivity. Now you're thinking through in more detail how to make a better experience. You're writing these emails which is actually a channel directly in and of itself that might have its own goals. So there may be different KPIs and things that are already starting to emerge of what makes a great email great. And then add on to that, you're building tools that help you standardize how to produce these items in a way that isn't just again going temp to temp, but you're kind of improving. You're creating scaffolding for them to be able to produce these in a more straightforward way moving forward, all while furthering your technical skills. So, so that's where you are. You're still not quite branded as an analytics professional yet. Right. But we can see kind of how this is building.

Speaker C: Yes. Yeah. From apress, I, uh, I went to work at Gartner, which is an IT research firm. Uh, so I was coming back to the world of research to Some extent, in fact, part of the application process, part of the interview process was submitting the papers that I had written in grad school and presenting it, uh, presenting those papers. So it was very much um, a uh, qualitative job. But what they had me do was work uh, with survey data. And so um, the way it worked was it's something called the Gartner Research Board where uh, it's essentially um, a group of chief information officers who come together and commission research. Uh, but they also want to ask each other questions. And so there's an aspect of developing a survey based on the questions that they're asking. Right. So taking the question that they're asking and unpacking into smaller questions that you know, will be, uh, will, you know, will result in answers that uh, can be quantified and can be uh, therefore analyzed in a systematic way that will give someone an insight into what percentage of CIOs are doing XYZ, exactly, um, et cetera. So that is what I ended up uh, doing next, uh, going back to my roots as a researcher, staying technical, staying quantitative. Uh, uh, because I was focused on developing surveys including in, in various tooling, getting the data back from the surveys, wrangling that data in a spreadsheet, uh, and then learning how to use a spreadsheet to crunch numbers in a scalable way. Ah, so that ah, I could produce uh, analysis efficiently against deadlines.

Speaker B: So now we're in quant with a heavy qualitative and research based, you know, component to it. But now you're actually dealing with quantifying all of the different results and comparing them and doing, you know, deeper analysis on them. So you've kind of crossed into something that is even closer. You're now getting even further to more of an analytics role. You're using spreadsheets.

Speaker C: Yeah.

Speaker B: You're dealing with data on a regular basis. You're even constructing sort of how it's collected to a degree or at least working with the various survey, you know, the survey pieces and trying to figure out what's going to give you the best signal. I think this is an interesting place. I mean, so we use Gartner reports for various types of pieces to get points of view on uh, you know, different tools or different technologies or how like you said, um, ctos might be using different things. Also Forrester reports, there's a bunch of other kind of published pieces and for our audience, like sometimes these things can be, for sometimes these things can be free or if you just enter in a, um, you know, Sometimes some, some of the gated content that we see on various, uh, you know, tools or, you know, businesses, websites, you can find some of these reports or get access to some of these findings. But I know that these are generally a premium subscription type type piece, uh, that's highly regarded within kind of the enterprise world. So now you're getting exposed to effectively a lot of perspective across the industry among people that again might play a role in your future. Um, you're kind of seeing things through their eyes. You're doing deeper analysis and now you have, you're acquiring more information that you could bring to the table in a conversation with these folks, but still putting together a lot of that academic rigor that you had earlier. But also the, you know, the rhetorical positioning and uh, is also getting layered in here. So I, again still building up this scaffold. So now you've been working for Gartner. You're working on these various, uh, surveys and exercises kind of where do you, where do you go next?

Speaker C: Yeah. So at this point I'm asking myself, what am I doing? What, what do I really care about? Um, at each and every one of those companies I cared about what I was doing, um, as a discipline. Um, but I asked myself, uh, or I reminded myself that what I really cared about all along is media. Uh, and so I literally went to Disney, um, dot com.

Speaker B: Okay.

Speaker C: I was a huge fan, uh, of animation, hand drawn animation, and again, the effect that these movies can have on people. And so I said, you know what, let me just go to disney.com jobs and see what's available. And lo and behold, the introduction of this concept of audience development.

Speaker B: Okay? So now we're going after. Pick a dream brand or something that you, you know, do something aspirational. You've built up a lot of credibility and credentials. You were confident enough to go and say, I'm ready for this level. And you went and you applied for a global brand, which is a game changer. Now was that position out of, uh, you know, was that out of, you know, Burbank or you know, out of that part? Or was it a remote position? How did that work?

Speaker C: Well, so it was actually at ABC News.

Speaker B: Okay, all right.

Speaker C: So, uh, my goal was ultimately to work, uh, let's say on the more creative side. But this role was at ABC News, which was located on the Upper west side of Manhattan. Uh, so it was, uh, where I was living nearby at the time. Uh, and so, uh, it was local in that respect. Yeah, it was, uh, ABC News and working in the newsroom, uh, next to all sorts of journalists that I had seen on tv, uh, who would come up and ask for data about how their stuff was doing.

Speaker B: Okay, so for a lot of people this is the dream job. They just want to stay right there. That's kind of, it's amazing. So now you're working for ABC News, um, it's not even cable. You're dealing with general network news under Disney, under the Disney umbrella. And you are answering questions, doing research and providing points of view for, you know, um, for serious journalists. So now you are in the thick of it. So how did that help shape your analytics career?

Speaker C: So it was first of all very exciting. It was very exciting to be uh, in proximity to uh, these brands, these personalities, uh, and uh, this kind of media which had a large audience and seeing large, large numbers, right? In terms of web traffic. For example to ABCNews.com, the numbers were very large. And you start to realize, hey, wow, uh, there's a lot of scale here and this is really interesting. So it was first of all solidifying uh, my interest in all this. Uh, and it was also pretty, uh, pretty early on, not necessarily in analytics, but in this concept of audience development, which again was figuring out first of all who your audience was. So thinking about, okay, there are these different kinds of users, uh, these different kinds of segments of users, uh, whom you want to appeal to with different kinds of content. And so even just building up this, this vocabulary and this terminology of um, the who, what, where, when, why type stuff and really building that out. And then, uh, because it was so early on in uh, in this concept of audience development there was ah, a lot of learning on the job for everybody figuring out what does this practice look like? Uh, and so uh, there were lots of opportunities to start using analytics tools. We used, um, uh, Adobe analytics, uh, there and figuring out for example how to scale reporting when properties, uh, in an analytics tool are siloed. Uh, and you need to figure out how to tie a piece of content across these different properties using a content id, uh, and essentially strategizing how are you going to measure, uh, the performance of this content that ultimately generate this experience of either being informed or being entertained. Uh, and so it was sort of always the motivation of achieving that effect and knowing that I was playing a role, if not as someone who was producing those effects, uh, at the level of the content itself, enabling the content creators to do their job better, uh, uh, and then using that um, to learn as much as I could about how to crunch Numbers in such a way that uh, the reporting I produced could be useful. Uh, and so that involved suddenly SQL beyond spreadsheets. Uh, and again it was always sort of figuring out opportunities to uh, learn technical skills secondary to uh, this interest I had in the more qualitative aspects of media rather than the other way around. So in other words, it wasn't like I need to learn uh, XYZ technical skills so that I can apply them wherever I can. Maybe it's media, maybe somewhere else. It's just being driven by uh, a, uh, like a sincere interest that you have, which could be the technical aspects itself. But for me it was uh, the qualitative stuff.

Speaker B: What's interesting is when you join this. For example, if they had said on the job description that you must be an expert with Adobe analytics, that might not have worked. Right? Like you could have run into some, some different challenges. So what's interesting is to kind of see how you were able to take the experience you did have. And sort of as you came to some of these interviews you got, you put yourself in a position where then you could get exposed to new tools firsthand, but with purpose, with sort of a uh, drive behind it. And so, you know, when people are uh, you know, the flip side is I feel like a lot of people as they're trying to advance their career, they start with, let me learn all the skills, what skills do I need? And they're doing it without necessarily a solution, context in mind. They're not really, they don't really know how to apply it, you know, out of the gate. What you're doing right now is you leaned so hard into the world and, and serving ultimately the people receiving this information, the, the, the writers and the, and the publishers that, that drove uh, everything that you did with the tools, it drove, you know, maybe a more focused path to becoming an expert with the tools.

Speaker C: Yeah, I think, I think that uh, fortunately for me, uh, is uh, exactly what happened. Uh, it was always, uh, you know, identify a problem you want to solve and then figure out how you're going to solve it. So it could be that you end up solving it by learning XYZ technical skills.

Speaker B: Ah.

Speaker C: But it's not starting with the tooling and in search of a problem to solve. It's starting with the problem that interests you that you want to solve. And then you figure out what do you need to know, uh, to solve that problem, um, how do you unpack that problem? So do you understand all its different components and how each component can be addressed? And, uh, just generally doing analytical thinking, uh, in order to get to the actual analytics and the data and the tool.

Speaker B: Right. You're starting with a drive for the insights that you'd like to be able to draw out first and using these as tools and vehicles to get there.

Speaker C: That's exactly right. Yeah.

Speaker B: Okay, so here you are, you are doing amazing work for a dream company. You're helping all of these different, uh, writers get the insight that they need. You're learning lots of tools, you're expanding your, you know, your entire toolkit. And that became sort of a platform to kind of launch you into this newer role or to the next stage with Conde Nest, where you've got a very large, uh, set of properties and brands underneath there. So tell me about what it's like to kind of, you know, how you transition from maybe working under the ABC News brand to a holding company with many brands, you know, to serve and support.

Speaker C: Yeah, yeah, it's a great question. So, um, so even at ABC News, there were different sub brands, let's say. So you had World News Tonight, for example, or you had 2020, or you had, um, all various, uh, news programs that all were under the umbrella of ABC News. And so I was already familiar with the challenge of figuring, uh, out how to report across all of those sub brands. Uh, uh, and so, uh, for example, there were things about each of those brands or sub brands, uh, there were things about each of those brands, um, that uh, were unique, uh, to those brands. But then there were things that we could look across all of them and see something in common. And something in common meant something that you could standardize and something that you could standardize. Uh, it became something that you could automate, uh, and scale. And so figuring out, okay, what is specific to the New Yorker or to Vogue, uh, that we need to address in a more bespoke way. But what did they have in common? For example, they probably share a certain set of KPIs, uh, they probably share certain, um, tactics when it comes to content distribution or on a particular platform like YouTube, for example. Uh, they certainly share, um, the same challenge of figuring out what the algorithm is prioritizing, uh, and figuring out at the platform level, how do I make sure that each of these channels succeeds even if each of those channels is doing something slightly different from, uh, their respective brand voices. So it really is the challenge of figuring out, okay, there are all these different things, what do they have in common? Because they get. The thing that they have in common is, uh, when different things have Something in common. It provides an opportunity to standardize something, to automate something, to scale something like reporting around those things such that all of them can tap into and then where are the areas where you really need to understand each of those brands individually in order to provide uh, them with something that will give them uh, uh, a distinct advantage in their specific space.

Speaker B: Right. To kind of move the ball forward specifically with that brand. Um, and there's a lot of nuance to this. So you moved from ABC News, obviously dealing with a lot of sub brands there. Now you're Conde Nast and you're dealing with very distinct different brands even across fashion to uh, all different forms of culture effectively with large legacy, weighty brands. Um, but you're looking at again the similarities across brands, across publishing, across uh, you know, the various challenges that you're dealing with. And you mentioned a few things earlier, inform or entertained as being sort of the guiding light of what success is for some of these different items. I'm um, kind of curious now that you're you know, in this space, you're working at publishing at this level. You've made your way there from such an interesting path, from sort of deep academic, um, you know, thinking around literature and media and ah, various art forms, you know that, that people produce all the way through to a lot of deep research. You've been kind of forced to learn with a lot of rigorous to go and build out, you know, larger cases and extrapolate and create um, much deeper insight that you build out all of your references that you've done, surveys that you've done a lot of quantitative analysis. You've worked directly in several cases even before Conde Nast working with publishers. Um, so you've learned kind of the back end of the business and all of the terminology and vocabulary through those experiences. And now you're at conde nest kind of solving portfolio level, you know, uh, challenges and you're talking a lot about building tools and automations.

Speaker A: Yeah.

Speaker B: Now was when you took on this role, was it like a natural curiosity for you to start to target, to like set your eyes, to look for these opportunities for automations and end things? Is this something that's sort of like your own curiosity or your own interest in maybe problem solving brought you there? Is this kind of what they brought you in to do specifically? Like was this a role that was that, that was advertised?

Speaker C: Yeah, so I don't think they brought me in to do that exactly. However, in effect, in effect they did because um, because again the, the, the role of a Director of analytics is really about getting answers to people and giving them insight into how something works such that they can change it. Uh, however, um, there are lots of obstacles to generating insights uh, in a role like that because at the same time you may have um, a um, a finance department that needs to understand how many, how many page views, how many video views, because they need that uh, as the basis for their modeling for how much revenue they can generate and how they can plan their budget. So there is a lot of reporting that goes on that is not necessarily insightful. Uh, it is about getting your uh, stakeholders the information that they need to uh, build their models or otherwise, uh, to uh, put together RFPs for advertisers. We had X many followers on this social platform, uh, as a way to convince them to advertise with you. But it's really just uh, pulling numbers. Right? And so the goal needs to be, if you want to get to a place where you're actually doing what you were hired to do, which was to give people insights about their business and how to improve it, you need to figure out how to get all that number pulling out of the way. You need to figure out a way to make that as fast and as efficient as possible. Uh, and so uh, there are various ways to do that. Um, uh, and it all starts with for example making sure that your data foundation is solid and clean, uh, such that you're not spending uh, inordinate amount of times wrangling your data, that it's standardized to a certain extent so that uh, so that you're not mapping uh, uh, and trying to normalize different dimensions. Uh, and so it's again starting with the problem of how do I stop doing this more tactical stuff so that I can focus on the more strategic stuff. I would argue like it ties back to uh, the experience at a press where it was like well it's not about putting emails together, right? Uh, let's figure out how to automate um, that as much as we possibly can so we can think more about what are the different segments um, that we want to send those emails to, um, which books we want to feature based on what's trending on Stack overflow or uh, other places that give you signals of interest. But again, um, I would argue that if you want to grow your audience, for example, the first thing you need to do is to figure out how to stop doing the stuff that is keeping you from doing the deeper analysis that actually gets you to the insights that get you to grow the audience

Speaker B: that makes complete Sense. I, um, do see a lot of people maybe get stuck at the superficial level. And so there are a lot of times when people maybe out of just needing a starting place, they throw out some vanity metrics. And if you just take them at a surface level, um, you know, you can optimize things maybe to get some of those metrics to look better. But then you run into this challenge where um, you know, you're kind of missing the point. Right? Like something deeper about how all of this works or what we're actually trying to accomplish here to make, make put the business and the property and the, and the folks that you're working with in a better position is, is getting lost. So tell me a little bit more about that.

Speaker C: Yes, it really is, uh, a big challenge and there are a number of ways of thinking about it. So first I would say there are some vanity metrics that are necessary, uh, in the context of again, uh, pitching an advertiser. And so they want to know the big flashy number, figuring out how to tell a story with vanity metrics in order to paint a picture for a potential client of why they should go with you and not with somebody else. Uh, so there is certain value to it. But really the biggest challenge with vanity metrics is that um, if you think that reporting on those metrics means that you've done your job, then uh, uh, you can feel like you've done your job, but really you haven't because ultimately those metrics matter. But what matters more is understanding what is driving, uh, those top line metrics and understanding, uh, that a page view is not the same as a user, that a user is, uh, uh, a person somewhere reading your website or visiting your website, um, it becomes very easy to flatten uh, everything at the level of that vanity metric, uh, and uh, to check a box on a piece of reporting without thinking about what is the meaning of this metric, what is under the hood for this metric that we can understand better in order to drive, drive, uh, the kinds of numbers that we want to drive. So it's understanding, uh, it's not just about reporting a number, it's understanding what drives that number.

Speaker A: This podcast is powered by Brand New, a digital marketing agency that not only provides a diverse mix of digital services, but offers guidance, experience and true partnership to bring your business to the next level. We offer expertise in analytics, paid media, web development, SEO and design, just to name a few. We've worked with businesses on every level, from local operations to Fortune 500 companies across a variety of industries. We have Expertise to help strategize and execute your digital marketing needs. No matter what step in the process process you're at, we're there for you. From wireframes to paid campaigns, Brand new experts in everything digital. Please reach out today to learn more about how we can help your business grow.

Speaker B: You know, if I were to think about some instances here. Yeah, I um, think about for example, okay, we have more hits on our, our website, but there's no depth to it. There's no uh, you know, it's a shallow or superficial relationship versus larger relationship, you know, a deeper relationship. And that can matter. And so when you think qualitatively, what's the makeup of this number and how does it work and how did we build it, it sounds like that is team, that's the more important piece to kind of driving the growth that actually makes that number mean something.

Speaker C: That's right. So maybe, um, what we could do is think about uh, an example of a vanity metric. So let's take page views for example. Page views are extremely important. It's a KPI, honestly because it's page views that correlates with ad impressions, for example, uh, uh, for that kind of revenue stream. So optimizing page views matters uh, a lot. And it's a number that you end up reporting a lot. Uh, but behind the page view is a user. Uh, and that user might generate one page view for you or that user might generate ten pages for you depending on how engaged that user is, uh, and how far down the funnel, uh, uh, that user is. And so it's important to understand the behaviors that are underlying the top line metrics that again matter. Um, but not to stop at that top line metric is really thinking about what does this mean, how do I increase this number? Um, and typically the way to increase those numbers is to understand the kinds of behaviors uh, that users are engaging in that uh, are resulting in those numbers. Uh, and so it's important to be careful not to get stuck in this swirl of reporting and vanity metrics, but to uh, understand uh, and unpack what is behind the behaviors that are behind those numbers.

Speaker B: Right. And so I think like sometimes about when I think about page views and, and advertising, I think a lot about those clickbait articles that have, you know, top 59 ways to, I don't know, optimize your house and you know, they take something that could have been a straightforward list and they, they turn it into tons and tons and tons of page views. And now when they report the page views, it sounds amazing. Except each of those page views was effectively a quick slide.

Speaker C: Exactly.

Speaker B: Uh, you know, you know, it was, uh, and so you know, the comparable body to something where you know, maybe it's a little bit longer and you could have served plenty of ads along that journey, kind of going through, through a longer form version of it. Uh, the one gave you a vanity metric that looks like you now have 59 page views. The other one only looks like you had one page view.

Speaker C: That's right.

Speaker B: But scroll depth, when you look at the engagement with that page, when you look at how they, you know, the different content and the time spent there, Completely different picture.

Speaker C: Absolutely, absolutely. Uh, that's right. So it can mask what's really going on. Right. A gallery can have those 59 pages but to one gallery, uh, and it might be drawing users from channels like Search or Facebook who aren't necessarily loyal to your brand. Uh, it's service content, uh, that is clickbait that um, that gets a click, gets uh, a page view. But then that user has generated, let's say those 59 page views for you, but really was effectively just one page view. And maybe that user never comes back. And so now you're in trouble because there's um, a period of time when um, uh, that kind of scale is achievable, uh, in ah, a particular environment where Facebook is still linking out to publishers and not focusing on short term video, uh, or Google search is still showing you blue links and not just answering your question with AI.

Speaker B: Right.

Speaker C: When you're getting into a world where uh, that scale suddenly gets turned off. Now you really need to think about what kinds of behaviors should I be optimizing for such that I have users who come back to the site on a regular basis, spend time with us and generate many pages for us but more efficiently rather than sort of one and done. Uh, world that we are quickly uh,

Speaker B: seeing behind us, transient, you know, like you know, no, not even looking at maybe what brand they're on, just consuming a piece of content and discarding it. To your point, that's very different from trying to build an audience that will survive media changes, changes in the media landscape, changes in you know, social media or other places where these things could be published. So that makes complete sense. Um, it kind of, you know, leads to these questions around how to build that, you know, for publication, how to build that more consistent relationship. What does it mean to move beyond, hey, I might have a page that can rank in search engines for a keyword, but doesn't really sell them on My brand to. I've got people that are going to come and see what we wrote before they even know what the topics are. They're going to come and check us out and follow us.

Speaker C: Yeah, yeah, exactly. So I think that let's say the uh, accidental audience, uh, that comes in from the top of the funnel, you still need to optimize for that, making sure that folks discover you, uh, so that's important. But then once they're on the site, what kinds of experiences are you um, giving to those users such that they discover more of your content and more importantly, uh, establish uh, in their minds the brand's authority in particular categories such that they begin visiting or engaging with those brands not because they have any particular piece of content in mind, but because they just want to see what's new from you. And um, what are you saying in this overall category? Uh, so not expectation of consuming uh, a particular uh, story, but simply to understand uh, whether your brand is saying something or producing content in a particular area that they now trust you for. And so it's really so top of funnel you get folks in discovering your brand, uh, how do you drive them down the funnel such that they uh, start trusting you and start building a relationship with you and start visiting your sites directly, uh, uh, not because they know what they're going to read, but because they will be delighted by what they find they can read and be engaged by and uh, continue that relationship with your brand.

Speaker B: So now we're at what are some of the metrics behind the metrics? So when we think about those loyal customers and obviously they contribute page views, they contribute there, there are lots of maybe more superficial metrics we could have on them. But what are some, maybe interesting uh, metrics that some people in publishing or you know, that are publishing content might overlook or not think about that are actually more important?

Speaker C: Yeah. So I would say that it's important to think about different uh, rates of visitation, of consumption, uh, of stickiness, uh, for example, how often uh, are users visiting your site? Is it once a week, is it once a month? Um, there are certain uh, rates of consumption of visitation and things along those lines that are underlying the top line metrics like page views. So for example, with page views, uh, it's really important to focus not just on page views, but page views per user. How many page views is each user generating for you? Which is ultimately going to be a function of how often are they returning to your site. So uh, looking at what percentage of your users are coming back to your site within a given month, over the course of their uh, relationship with you over the course of that lifetime. Um, or you might measure for example how many users uh, did you convert from a non returning user to a returning user or someone who came, would come in from an acquisition source like search or social media, who all of a sudden start visiting your site directly without needing to be referred from these platforms that you don't control. Um, and so how do you quantify that? How do you look at that? Um, and so typically it's really just understanding conversion, right? It's how do you convert a user from uh, accidental to direct or um, how do you look at uh.

Speaker B: Yeah. Now what I think is interesting here is um, you said the word trust, you know, and so when we think about that, you know, these are all proxy, these are getting to proxies for trust. They people that come back and keep looking at your content must trust your content is going to provide them information they're going to be interested in. Um, and so, and, and when you mention these things around um, you know, the users and the average pages per user, I think about like clusters. Like um, sometimes if you just take an average, you know, you can thin out the average and the average goes down because you have more of the superficial activity going on or the average goes up because you just kind of turned your upper funnel things off for a little bit. Right when you know. And so I do think about like clusters of like behavioral profiles or things that could be, you know, that ultimately could be more useful.

Speaker C: Yeah, yeah. So I think that's the challenge with looking at rates. Uh, so for example, if you looked at something like time spent per user, uh, the trouble you might run into is that let's say you have uh, a viral story uh, from a particular traffic source where users are not as engaged. Um, and so all of a sudden, because your denominator um, is so all of a sudden that rage will be misleading because uh, because it's being driven by a particular uh, kind of audience or uh, it's being skewed by a particular kind of user, uh, that you may not be interested in. So it is important to understand um, these uh, different kinds of rates of conversion, but contextualized as part of an analysis of different segments of users, uh, and understanding in the first place what are the kinds of users that I want to uh, develop more of and figuring out uh, their different rates of consumption or visitation rather than looking at an overall picture that might muddy the muddy, um, the insight.

Speaker B: Absolutely. So I think we've covered a lot here on, on that front that seems to be at uh, the forefront right now. I like the fact that you brought in, you know, the AI, ah, overviews, kind of taking some of the traffic away or social media algorithms and what they seem to value, kind of shifting things around to the game plan isn't just to keep chasing the next social media algorithm. That might be a transient thing, but it's really about chasing audience, it's really about chasing loyalty and finding different ways for publishers to stand out so that they seek you. They'll download your own properties, your own apps, they'll, they'll go to you by name instead of, you know, um, you know, other forms of cross promotion. So I know we've got a, you know, as we're going through this right now, you know, I know we had a few other areas that we could cover that we talked about before. Are there some areas that you feel like the audience should definitely, you know, that you'd like to share with the audience things that you're excited to share?

Speaker C: Yeah, I guess. I um, think what I would love to share with the audience is uh, a particular framework that I'm uh, excited about, uh, which is uh, something called user, uh, pathing. And so essentially if you um, uh, if you figure out a way to unpack the uh, the series of behaviors that particular kinds of users engaged in in order to get from one state to another. So for example, to get from the state of being an accidental visitor to your site because they found you on social or search, uh, getting them from that accidental state to a more directly engaged state where they're visiting your site directly. Uh, and if you take that same user and you try to look at all the behaviors in between that beginning and end state, uh, then you will have insight into how they become more directly engaged users from that accidental state. Uh, and so from an analytical perspective, from a data perspective, it's figuring out how do you create a data set that will show you that journey. Uh, and so uh, for publishing at Conde Nast, that journey is often in terms of the kinds of content that a user is uh, engaging with, uh, uh, along that path to becoming more engaged. Uh, and so uh, I'm really excited about that kind of approach to things where again you are moving away from what is ultimately correlated with something like um, advertising, which is the page view ultimately, right? You're serving ads on a page. And so uh, the bigger that number, the more ad impressions. And you're unpacking that vanity metric and saying, okay, uh, there are users behind this number and these users are engaging certain behaviors. But not all users are the same. Some are more engaged than others. Let's look at the ones that are more engaged. For example, the ones that we see are visiting the homepage directly, or the ones who are subscribing to our newsletters and visiting on a regular basis from those newsletters. Let's segment those users and understand how did they become those users. They weren't always that way. Um, and so just thinking along the lines of that journey that these users are um, participating in in order to become more engaged and become more loyal to the point where it is no longer about a specific piece of content, it's about uh, uh, building a relationship with your brand based on trust, in particular, uh, categories that they want to know your perspective on. Um, so that's what I'm most excited about, is thinking in those terms and I'm be happy to talk about um, some of the technical aspects of that or how, how to dig in from there.

Speaker B: I think that's super interesting. I feel like it can be overwhelming. So for example, the path between, first of all, just to define the milestone for some of the different conversion pieces like, and now they are a loyal use. It's like you have to decide even how to cluster together what that actually means. Do they view, come back to your site a certain amount of times, over what time frame, how many times over what time frame, in what, in what capacity, doing what, which actions. So there's a part of like profiling even just how to create the, the end state before you can even say, now how do I look at and qualify all of the different paths and maybe like cluster them together in a, in a meaningful way so that they're not just all individual stories that are disconnected from each other so that you can talk about going between those, those end states. So tell me, just, you know, especially for a publisher that was just like, I don't even know where to start, like where would, where, where should they maybe consider beginning?

Speaker C: Yeah, I think that's, that's exactly right. So you do need to start with that end state in mind and have some ideas about what that looks like. Uh, have some hypotheses. Uh, and so uh, it's essentially working with, uh, working with your stakeholders to understand uh, what potentially are the most engaged kinds of users. So for example newsletter users, that's pretty straightforward. We know that if someone is signing up for a newsletter and visiting from it, that's one profile. It's the newsletter Visitor. Another profile is someone uh, who is visiting the homepage directly. Another profile might be someone who is engaging with more uh, visual formats on your site because that could involve galleries for example. And the galleries are engaging, uh, and that engagement is going to translate to habit formation, uh, such that they are returning, uh, uh, and uh, generating more page views. Again that top line vanity metric. Uh, so it is a bit of brainstorming on what kinds of profiles do we think are most engaged? Let's look at the data and confirm that. Right. So once you have all these profiles you can sort of compare them side by side using uh, uh, a metric like uh, page views per user or time spent per user or some metric that will, that will reflect engagement and then just compare those profiles, those segments and say okay, this one is the most engaged for this particular site. Now let's dig into um, uh, the behaviors that drive a user to become that kind of, uh, to dig into the kinds of behaviors that result in a user joining that kind of segment.

Speaker B: So, so you create those profiles. And what's interesting, kind of going all the way back to your research career is that it does sound like you have to really think about the users. You have to really think about their, what they're doing. So if you were just comfortable saying I am used to looking at page views, that's not enough. What makes, how do these page views cluster? What's the different about the user? What might be going through their minds that they become this you know, gallery focused piece? How does that connect to the fact that maybe this is, you know, a very visual uh, topic that we're covering here versus something that might be more of a thought piece? Or you know, it could be different kinds of publications might have different clusters or patterns that you might want to look for that are a little more bespoke.

Speaker C: Um, yeah, yeah, yeah, yeah, that's, that's right, that's right. And uh, and it's, it's clustering users, but it's also clustering uh, the, the kinds of content or pages that those users are looking at based on the story that each kind of content is trying to do. So it could be that um, some content is looking to entertain, some content is looking to inform, um, some content is looking to uh, educate on how to do something. Um, and so in general, uh, the more you can come up with frameworks for doing uh, these kinds of clustering, whether it's of users or of kinds of content that you're distributing to those users, uh, then the um, the easier it is to analyze and uh, to synthesize an insight. Um, because if you have, unless you have a way of summarizing the kinds of content that particular users are uh, looking at before they start visiting your site directly, uh, then uh, it's just uh, a bunch of URLs that don't tell a story. You need to figure out um, how am I going to summarize these URLs either by category or by tag or something that is going to give you a foothold, uh, into uh, some activity that you can then ramp up like producing more of certain kinds of content and maybe less of other kinds of content that may get you that skill at the top, but ultimately uh, uh, is not resulting in the kinds of behaviors that drive loyalty and trust, uh, and ultimately result in uh, uh, a business that might not be sustainable as the landscape changes. So it's important to uh, figure out ways of looking at it um, in a more synthesized way that makes complete sense.

Speaker B: Um, so I guess you know, based on your background and again we, we have a lot of folks that are learning some of the tools that you're using to do this kind of work, but not necessarily. They may not fully know as much about research, they may not fully have maybe some of the, the other toolkits that you got that you had from the humanities that sort of brought you here. Um, you know, what's some advice you have for them to be able to enter into this world?

Speaker C: Yeah. So I would say ah, that uh, the most important thing is to be honest with yourself about what matters to you about uh, this kind of work. So in other words, uh, if you're looking at any particular domain as just uh, uh, a new set of widgets to learn how to count and to analyze, uh, and ultimately you're agnostic to what those widgets are and the context that those widgets are in, um, then it will be less sustainable than if you start from the kinds of domains that motivate you, that interest you, that get you excited and then figuring out what kinds of problems uh, are inherent to that domain that you can solve with data, uh, and with analytical approaches. Um, so starting with uh, something that you care about, identifying uh, um, the challenges, uh, that uh, are potentially keeping that thing you care about from reaching uh, more audiences, uh, or just generally being more effective, less clickbait, more uh, content that uh, really gets people thinking and feeling uh, and thinking about. Okay, um, how do we go from clickbait to something more engaging? What is that? Let's name that Problem, first of all. And let's think about uh, the components of that problem. Let's get insight into, uh, what is preventing users from becoming or engaged with your brand. And then from there you can say, okay, data, do we have to marshal here to give us an idea of the kinds of behaviors that we want to drive versus the kinds of behaviors that we want to move away from? Uh, and then coming up with the analytical frameworks for, uh, for analyzing that data in a way that will get an answer to the stakeholders who uh, have their hands on those levers and give them an idea of what to do next and how to develop their audiences. Uh, it's really thinking about what is the end state that you're trying to achieve, first of all, and working backwards from there. And uh, in working backwards, figuring out what are the different tools I need, what are the different kinds of thinking I need to in order to achieve that end state, rather than uh, being agnostic to what the end state is.

Speaker B: I really, really like that. And you know, again, your um, curiosity around media, your interest in media very early on turned into this entire career and that's been sort of the, the, you know, the thematic glue, the way that you've approached it means that things can change. New, new, different ways for these brands to express themselves could come out. Uh, you know, things could change in the social media landscape or how they discover or find this media. But the approach, the analytical approach that you're taking to kind of framing in and solving these problems and sort of that attitude of uh, that you're here to solve, you know, their constraints or their challenges or their bottlenecks that's going to carry through, that's going to translate into the future with tools we haven't even thought of yet and techniques we haven't even, you know, challenges we haven't even, haven't even faced. And so more people think more about, well, finding that spark that you had with your, your interest in media early on, that can be a driver and a lot of these other areas, building out frameworks that, that's building out structure to be able to really provide value, to be able to help.

Speaker C: That's right. Exactly right, yeah.

Speaker A: Yeah, I couldn't agree more. Anybody in the audience who is looking to get into this kind of thing or just absorb and learn more about marketing in general, it is always very cool how the landscape is always changing. And I feel like you never know exactly where you could land because there's so many places to go. So, um, Andy, I really find that uh, you know, your personal professional journey is very inspiring to me personally. So, uh, this has been great.

Speaker C: Thank you for spending time with us.

Speaker A: Learn more about Braindew and our marketing services on our website at www.brain.de. if you'd like to see more from us, please consider subscribing or giving us a follow. Uh, we are found on our social media platforms at Brain do under that handle. If you learned something helpful from this episode, uh, just please consider giving us a review and just following along. Otherwise, we'll see you next time at the roundtable.