Stephanie 0:04 Alright. Sorry, guys. When I didn't have I wasn't quite set up, but I'm gonna go through our intro now. Make sure I'm centered. One sec. Yep. Looks good. Okay. Welcome back to the Curiosity Currents. Today, I'm joined on the hosting side by Brianna Boyer, senior director of solution strategy at AYTM and a long time friend and colleague of mine. We've been working together for twelve years. Brianna, thank you so much for joining today. And even more exciting on the guest side, Brianna and I are joined by Lina Doshi, senior manager of research at Electronic Arts, where she leads the charge and market research strategy to inform business decisions and elevate customer experiences. Lena brings a wealth of experience from her time at EA and U Ship, where she has been instrumental in building market research functions, leading global research projects, and leveraging data to drive innovation and growth. In our conversation today, we will explore the evolving role of market research in a fast paced industry like gaming, uh, explore the difference in solving data mysteries versus I'm gonna start over on this part. In our conversation today, we'll explore the evolving role of market research in a fast paced industry like gaming. We'll talk about the differences in solving data mysteries versus data puzzles and balancing insights that honor complexity and individuality in gaming audiences with universal truths that can drive action. We cannot wait to dive in. Lena, welcome to the Curiosity Current. We're excited to have you with us today.

Leena 1:46 Thank you. I appreciate it. I'm excited to be here.

Stephanie 1:50 Wonderful. Well, to kick us off, there, uh, is a a question that we often start with. Um, in this case, you know, you've had such an interesting career so far spanning, you know, several different industries from gaming at EA to logistics at U Ship. What initially drew you to market research? How'd you how'd you get into the field, and how has your journey evolved over the years?

Leena 2:13 So it's, uh, kind of a funny story because I literally just stumbled across marketing research as a function. I was out looking actually for MBA programs. I was in in the Dallas Fort Worth area at the time, and I was just wandering around looking for MBA programs. And I stumbled across the master of science in marketing research at the University of Texas at Arlington. Yeah. And, um, I met with the adviser, and he told me all about the program. And I was in. I was hooked. I loved the idea of being able to combine data and kind of the human story. And, um, it's been amazing ever since. And kind of over the span of my career, the passion hasn't changed. But I think my role in the process definitely has changed a little bit. Gone from more of the the doer, like, in in the weeds, do getting into the research, where now it's more the strategic, uh, leadership thought leadership role.

Brianna 3:10 I love how we all just stumble into this industry.

Stephanie 3:13 It's such a common theme. Yeah. I love it. changed a little bit. Gone from more of the the doer, like, in in the weeds, do getting into the research, where now it's more the strategic, uh, leadership thought leadership role.

Brianna 3:10 I love how we all just stumble into this industry.

Stephanie 3:13 It's such a common theme. Yeah. I love it.

Brianna 3:16 Yeah. We've all got our own journeys of stumbling, so it's always cool to hear. So with your extensive experience in shaping research strategies and driving customer centric decisions, how do you define consumer insights in today's rapidly changing market landscape, especially in industries as dynamic as gaming and shipping?

Leena 3:34 So I really thought long and hard about this question and how I wanted to answer it. And I think that what is consumer insights, I don't think that part changes. Humans are complicated and can be hard to predict, which is kinda why we study them and why we have jobs. So I think as researchers, in a nutshell, we study human, like, needs and wants and perceptions and behavior to better understand them. And we also kind of sit in a unique analytics position because we are able to create data to solve problems. So for example, at EA, we have large analytics teams, but their jobs are all about analyzing data that already exists.

Stephanie 4:18 Right.

Leena 4:18 So they are looking at telemetry data, marketing funnel data, metrics, stuff like that, and analyzing it. Whereas researchers or insights professionals, we have the power and ability to go out and create new data new datasets to help solve these human problems and challenges. So I think the core of what we do doesn't change even with the rapidly changing technology and industry environments. What does change, though, is how we are gonna meet these challenges, these human challenges. So the tools in our toolkit are rapidly changing as technology continues to evolve, and we're gonna have to evolve our methodology with it. do doesn't change even with the rapidly changing technology and industry environments. What does change, though, is how we are gonna meet these challenges, these human challenges. So the tools in our toolkit are rapidly changing as technology continues to evolve, and we're gonna have to evolve our methodology with it.

Stephanie 4:59 Absolutely. Um, and we're gonna get into that a little later in the discussion. So I'm looking forward to unpacking that a little bit more. Before we do that, there's there's kind of a a topic that I wanted to chat with you about. And, uh, so to start, I think anytime you move from you know, to a new org or a new industry, there's change. Right? You're learning and adjusting to new things. But I there's something about your journey that I have to imagine. You know, there are some pretty big differences in consumer behavior and even research needs between an industry like logistics versus one like gaming. And this is where I went down a little bit of a rabbit hole, uh, last night thinking about games like college football versus Apex versus The Sims and how complex and different your audiences can really be in gaming. And so I wondered if you could talk a little bit about how you've adapted your approach to insights for the gaming industry, and how do you navigate this is kind of a two parter. How do you navigate the complexity of audiences in gaming to find that balance between honoring the diversity, but still pulling insights that are generalizable enough to make an impact?

Leena 6:12 Uh, it it is not easy. That's the answer. It is hard because you're absolutely right. We've got such you know, our games are our products, and we've got such drastically different, you know, products. You can go from Apex Legends to the Sims or to any of our sports games. And like you said, the audiences are completely different. But a lot of it is really just recognizing that they are different and not going in with the assumption that, oh, well, I can just make you know, I'm sure the the Madden player is close enough to the the Sims player. And so it's really just just acknowledging that there are differences in issue, do the research, making sure that you're accounting for those differences and not making assumptions about what is or isn't true because that happens a lot. You know? Uh, folks get into the habit of just making assumptions about who the player is or what they do. And so as the insights professional, it's kind of it's really important that we're able to take a step back and help the business have that awareness about the distinctions and the differences in the player bases. Um, so I think so you were asking about how, you know, we customize it, and I think it's it's more about working with the business and making sure that they are not lumping lumping people together that they shouldn't be. It's more about the differences or how we interact and how we help the businesses as each of the products kind of work a little bit differently. So we have to make we have to customize that to each of the teams, essentially. iness and making sure that they are not lumping lumping people together that they shouldn't be. It's more about the differences or how we interact and how we help the businesses as each of the products kind of work a little bit differently. So we have to make we have to customize that to each of the teams, essentially.

Stephanie 7:45 It makes sense. Do you ever are there ever times where you think about, like or or do research where you you are thinking about gamers a little bit more monolithically? Or do you find that you pretty much always need to be thinking at the product level and the audience for that particular game?

Leena 8:04 It kind of depends on what you're talking about because, obviously, our products in our different games are their own brands, and it's important to keep the players, you know, kind of in their own buckets for each of the products. But we're also we're EA as a brand as well. Right. And so it's, uh, yeah, which is hard because EA as a brand is, like, almost the entire population.

Stephanie 8:27 Right. Right. Right. Right.

Leena 8:28 All of the kingdoms. Um, and so it makes it it just makes it it's just complicated, and you have to keep all of these things in mind when you're talking about it. So it really just depends on the objectives and what you're after, and are you talking about the the, you know, EA as a brand, or you're talking about one of the products, and you just have to kinda customize your approach depending on what it is you're after. Like anything else we do, it's the answer is it depends.

Stephanie 8:52 It depends. Yeah. No. Very reliable answer.

Brianna 8:56 Yeah. The classic one for sure. Yeah. Um, so in your recent YouTube miniseries on solving data mystery versus puzzles, which was fantastic. I really enjoyed watching that and recommend everyone go check it out. You discussed how data of course. Yeah. Uh, you discussed how data can be approached differently depending on whether it's a mystery or a puzzle. Could you elaborate on how understanding this distinction changes the way market researchers should approach problem solving? ing that and recommend everyone go check it out. You discussed how data of course. Yeah. Uh, you discussed how data can be approached differently depending on whether it's a mystery or a puzzle. Could you elaborate on how understanding this distinction changes the way market researchers should approach problem solving?

Leena 9:21 Yeah. So this was I loved doing this, uh, that YouTube series. It was super interesting. I got great had great conversations about it. And in a nutshell, a puzzle is relatively easy to solve. You just find all of the puzzle pieces, and you put them together, and then you have your answer. A puzzle typically has a single solution. Or in research terms, we go conduct it. You have a problem, you conduct a study, and then you have your answer. So that's typically a puzzle. On the other hand, you have a mystery, and a mystery is complicated, ambiguous, and doesn't necessarily have a solution or have a single solution or even a solution at all. Because of the ambiguity and complexity, it's best to approach a mystery by gathering and reviewing all of the existing data that you have on the problem. So we live in a world where we almost have too much information, too much data at our fingertips. So it's really important to review what you already have before you start adding data to that existing pile. And this is especially true, I think, when you're leveraging any kind of technology. Like any like all of our other tools, technology is a tool. And like any other tool, it's only as good as its operator. So you wanna make sure you gather if you haven't think you have a mystery on your hand, the way to approach it is gather everything you have and analyze that before you do anything else versus a puzzle, which is you have a problem, create a study, put all the pieces together, and then you have your answer.

Stephanie 10:54 How did you develop that framework? I'm so curious because it's super intuitive. Like, as you talk about it, I'm like, of course. That is and I can map a lot of experiences to it, but I have never articulated that, and I've never heard it articulated in that way. r, and then you have your answer. How did you develop that framework? I'm so curious because it's super intuitive. Like, as you talk about it, I'm like, of course. That is and I can map a lot of experiences to it, but I have never articulated that, and I've never heard it articulated in that way.

Leena 11:11 So the I the idea came from a book that I read called Intelligence for an Age of Terror by Gregory f. Travartin. And that book is all about data and security at the national level. So this he was the, um, the chairman of, um, basically, of I've forgotten exactly the name what he was the chairman for, but he was so he wrote this book that was all about, like, data and technology. So for example, he said he talked about why did nine eleven happen in terms of data? Like, who had what data and how it, you know, crossed or didn't cross, left hand didn't know what the right hand was doing kind of thing. And in that and so I read that book, and I was like, wow. That's really interesting. And so I took a lot of the the lessons he learned from data at the national security level and then said, alright. How does this apply to research? How does this apply to the data and the analytics that we do every day? And so that's one of the ideas that I came up with from reading this book is that and he's the one that coined, like, the puzzle and the mystery, so I cannot take credit for that. But I took all of the learnings that he shared in that book and then applied it to insights professionals in research. And one of that was saying, okay. If you define something as a puzzle, then just go out and do the re execute the research project, and then you have your answer versus the mystery, which is you likely have way too much data already, and make sure you're you're analyzing and collecting everything you have before you go and add more data by doing another research study. That's kinda how that came about.

Stephanie 12:47 Very cool.

Brianna 12:49 It's so interesting. It it's fascinating also that you were able to take this government level perspective on data and translate it to consumer insights.

Leena 12:59 Yeah. And for anybody who's interested, I highly recommend the book, but it is not an easy read. Like, it's it's a tough like, it's so detailed and so technical. It's it's a tough read, but it's fascinating because it's all about how the federal government uses data and all the different the CIA and the FBI, and how they all do it differently and how they work together. And some of the challenges, I think, are similar to us in in as insights professionals because I know I mean, EA's got over 10,000 employees, and one of my biggest challenges is always how to get the right person, the right data at the right time. And and then he talked about that a lot too in the book. So rk together. And some of the challenges, I think, are similar to us in in as insights professionals because I know I mean, EA's got over 10,000 employees, and one of my biggest challenges is always how to get the right person, the right data at the right time. And and then he talked about that a lot too in the book. So

Stephanie 13:43 Yeah. That's super interesting. Um, okay. So you've you sort of have hinted at this so far along the way, but I'm curious just to dive into it directly. You know, given the diverse methodologies that are available in market research from in home ethnography to focus groups and quant surveys, How do you see the balance among the various methodologies we have access to evolving in the gaming space where, you know, I have to imagine the attitudes and behaviors and even those audiences are changing kinda rapidly?

Leena 14:14 Yeah. My philosophy for technology, which includes the huge, um, explosion of AI, is that technology needs to focus. I hope that we are able to allow technology to focus on what it's good at, which frees up the humans to do what they're good at. And, typically, what the AI is good at and what the human is good at is not the same thing. So it's real that's why it makes a really great partnership.

Stephanie 14:42 Yeah.

Leena 14:43 One of, I think, the one of the easiest examples is unstructured data. So we let the AI take the unstructured data and create summaries and create, you know, uh, categories of, uh, themes and stuff like that. But it takes the human to go back in there and review all of it. The human, obviously, is super difficult and time consuming for the unstructured data, but it's easy for the AI. And then the human can come in and do what they're good at, which is looking at the data, do the critical thinking and the problem solving, and being able to come up with a a final deliverable for that unstructured data.

Stephanie 15:22 Makes sense. Is and it's like contextualization a big part of what the human can do too. Right? That's that's not something that yeah. AI is gonna be able to easily do, especially the contextualization of, like, your company and your values and what, you know, your goals are. Yeah. Things like that.

Leena 15:41 Yeah. So, like, a great example in gaming is we've got, um, games where there are words that, like, the AI think is bad, like, murder, death, kill, for example. Yes. And it's actually the good thing, not a bad thing. So, you know, it's that's why it's just a good example of why the it's so important to still have the human involved in this process because the humans are complicated. Humans, you know, are not easy to solve, and so it's still gonna take that humans working with the AI to produce the best output and the best deliverables. Makes a

Stephanie 16:17 ton of sense. ample of why the it's so important to still have the human involved in this process because the humans are complicated. Humans, you know, are not easy to solve, and so it's still gonna take that humans working with the AI to produce the best output and the best deliverables. Makes a ton of sense.

Brianna 16:19 Yeah. I'm leaving a gap there for a second just because they might wanna cut this. But, um, it is really interesting you talking about the the difference in meanings of words, uh, given gaming versus non gaming context because, uh, when my Friday night gaming group gets together, we we are very carefully phrasing how how we want to, you know, in a fun way, ask if people are ready to to jump on and, you know, click heads or something like that. Um, so, yeah, we might wanna cut this especially given recent events. But, anyway, so you've been instrumental in building market research functions from the ground up, notably at EA and UShip. What do you think are the core pillars of establishing a successful, scalable research function in a large complex organization? And then how do you ensure that it adapts to those rapid technological advancements?

Leena 17:11 Uh, that's a great question. So I have learned, and in some cases, the hard way, that the key to building a skate scalable research function is really has nothing to do with the research itself. And it's all everything to do about understanding the needs of the business and your stakeholders and how it operates. Do people want for example, do people want their findings in just a a report that you hand out? Do they want to be have a presentation and have them handed it presented to them, or do they prefer to use vendors? Do they wanna do it? Everything in house. So all of these questions are really how you build an effective and scalable research function. The research itself doesn't really change, but it's how that function interacts with the business, I think, is the is the important piece. Um, and especially in large organizations like EA, flexibility and adaptability and trust is key. So I think the adaptability and the flexibility part is pretty self explanatory, so I'll elaborate a little bit on what I mean by the trust piece, which is also essential. But put simply, it doesn't matter how brilliant or amazing the research that you do is if the business doesn't trust you. What you deliver will have no impact because they'll read it. They'll look at it and go, yeah. Okay. Whatever. And they put it down. So that's why I think that building the the trust and the relationship with the businesses and your stakeholders is a key piece of doing that. And I think that also leads into you asked about, like, keeping up with the technology. Um, it is not easy. Everything is exploding so fast these days.

Stephanie 18:54 So fast. t's why I think that building the the trust and the relationship with the businesses and your stakeholders is a key piece of doing that. And I think that also leads into you asked about, like, keeping up with the technology. Um, it is not easy. Everything is exploding so fast these days. So fast.

Leena 18:55 And it it felt overwhelming to me really at first. And so what I try to do to try to keep make myself feel like at least that I'm keeping up with the technology is that I try one new thing. My goal is to try one new thing every quarter. So whether that's a new vendor, whether that's new technology, whether that's, like, reaching out to somebody else even within the company who's trying a new thing, but I try to investigate one new thing every quarter. And because I have a pretty solid understanding of the needs of the business and and the challenges that I face and where technology might be able to help or alleviate some of these challenges, it's relatively easy to do a quick evaluation and decide whether or not it's something to move forward with. So it's not necessarily a huge, like, time sync. It's just, like, making sure because sometimes it'll fall on the to do list. Like, it's like, oh, I'll just do that later. I will just do that later.

Stephanie 19:51 For sure.

Brianna 19:52 Yeah. I love that you schedule that, and you just say, I'm going to do this and you create that routine helps you stay curious, which I I know you mentioned at the end of your your YouTube series videos. And, uh, curiosity is a a big value for us here at a y t m, so I love that.

Leena 20:09 Yeah. Uh, stay curious. And, um, it's actually I mean, it's to the point where I put it on one of my of course, we have, you know, goals. And so it's one of my personal a little bit of work, but also, you know, a little bit of personal goal is making sure that exploring options. There's just so much out there and changing every day.

Stephanie 20:30 For sure. Yeah. I would if you don't mind, can we go back to the to the trust issue again? Because I loved the the way you talked about that. And I was curious, where do you think the and and maybe just in your experience. I don't wanna force you to talk about insights across every, you know, organization in the world. But where does the lack of trust come from? Is it typically like a like, if that's the starting point, is it a cultural thing that just has to be overcome within a company? Is it like, what is the root of that, do you think, between an insights function and, like, decision makers or stakeholders? nization in the world. But where does the lack of trust come from? Is it typically like a like, if that's the starting point, is it a cultural thing that just has to be overcome within a company? Is it like, what is the root of that, do you think, between an insights function and, like, decision makers or stakeholders?

Leena 21:08 Um, I think the root of it is is here, honestly, because as a stakeholder, if I give if you're my stakeholder and, um, I give you data, and if you take that data and now you have a choice. You can you take my data and my recommendations, and you just you trust me to and you're like, alright. She said this. I trust her. I'm gonna go do it. But if you do that and I'm wrong, then it's kind of on your head because you've made the decisions. You've, you know, actioned on x, y, and z. And so I think it's a it's a fear of making a wrong choice. Uh, it comes from a fear of making the the wrong choice. And some of it is cultural, I think, for sure. Some of it, you know, typically, I think what what happens is somebody's been burned at some point.

Stephanie 21:57 Yeah.

Leena 21:57 Whether or not, you know, the the data didn't, you know, get in there accurately, whether or not the recommendations were not accurate. Like, all of that can be whatever, but they're usually been burned at some point. And so if they have, whether it's by you or even if it was somebody else, you know, getting over that hump and building that trust is gonna be even more critical because they're not gonna listen because we're afraid.

Stephanie 22:23 Right. It really, uh, sort of calls to mind and brings to the forefront just the importance of being really good stewards of insights. Right?

Leena 22:32 And Yes. Yes. Absolutely. Yeah. And helping and if there if there is a lack of trust, having the patience and the empathy to work through that can be really, really frustrating and hard, but it's absolutely worth the effort Totally. Bring stakeholders along for the ride.

Stephanie 22:53 Yeah. That makes a lot of sense. Um, I'm gonna pause for a second just to ask. Brianna, did you ask your question about yes. You did. We just talked about that. They'll cut all of this, Lena. Don't worry. Okay. Um, one of the things I wanted to ask you about is a specific project, which is rare. I don't get to do this very often. But at EA, you led a global research project with 10,000 responses across seven countries. And of course, let me know if I got any of that wrong. But my real question is, what were some of the challenges that you faced managing such a large scale, multi phase kind of project? And then to follow that, how did you balance the need for a core set of actionable insights with the cultural nuance that Shirley must have arisen across such a large number of markets? ng. But my real question is, what were some of the challenges that you faced managing such a large scale, multi phase kind of project? And then to follow that, how did you balance the need for a core set of actionable insights with the cultural nuance that Shirley must have arisen across such a large number of markets?

Leena 23:47 Yeah. That project was a beast for sure. Um, I it was a project was a beast for sure. Um, I it was about five years ago, and so we didn't have like, I wish we had what we have. Even five years ago, I wish we had then what we have today because it would have made it so much easier. But I think the key to this project was really leaning on my partners, both internal and external for advice and feedback because this certainly wasn't anything that I was gonna be able to, you know, sit in a room and do in a silo. Yeah. There were just so many teams that I had to work with and ask for feedback and really try to you know, it was not gonna be perfect. Like, we knew that going into it, that perfection was never gonna happen. We had to do our best to culturalize each one, but still maintain the same thread through everything. So then when we got to the reporting, it wasn't like, well, this is true for this country, but this is true for this country because we couldn't, you know, measure them together. So it was a huge, yeah, a a huge challenge. Um, but the partners that both internal, external were were critical to that process. And then as far as the the actionability and the cultural relevance, I did the same thing when it came to the analysis and the reporting and was leaning on my partners again, both internal and external. And one thing that I did that I don't normally do when it comes to, like, the readouts in the presentation was that I actually customized the reports to the major teams, like, around the business. And so when I did the presentation, I knew what that team specifically, what mattered to them, what was important to them, and so I could have those insights already customized to them. And now, obviously, that was really time consuming, and it is not something I would even I would recommend or even do myself for every single project. But because this was so huge and so important and so critical to almost the entire business, it made sense, at least at a high level, to, you know, have some level of customization for the different teams. And they were the so the output of the deliverables and the presentation, everybody really appreciated, and it was much more impactful because I was able to say things that mattered specifically to them. So I certainly wouldn't do this for every project, but in this case, the what did they say? The, um, the oh, the juice was worth the squeeze. This took

Stephanie 26:18 her out. Yeah. Yeah. Yeah. It sounds pretty critical to to that project success. That's yeah. Makes a lot

Leena 26:24 of sense. Yeah. hem. So I certainly wouldn't do this for every project, but in this case, the what did they say? The, um, the oh, the juice was worth the squeeze. This took

Stephanie 26:18 her out. Yeah. Yeah. Yeah. It sounds pretty critical to to that project success. That's yeah. Makes a lot

Leena 26:24 of sense. Yeah.

Brianna 26:26 Yeah. So kind of talking more generally now, but I think that that project might be a good example of this. Market research is often seen as a function that forms business decisions, but how do you see the role of insights evolving to become more proactive, like maybe tailoring those reports to make sure people are getting those answers to what matters to them, um, to be more proactive rather than reactive to market shifts?

Leena 26:51 Yeah. So it's insights professionals, I I know we don't like to guess. We want data to prove or disprove any hypothesis that we have. And I know the one of the challenges I know I face is that historically, research moves too slow. The business is asking questions that require almost immediate answers, not, okay. I'm gonna go execute a research project. I'll get back to you in four months with the answer. Right.

Stephanie 27:16 That's never

Leena 27:17 gonna work. Right. Um, and that was actually a big problem that we had with the project. The 10,000 that we just talked about was it was so big and so long that in some cases, they were like, well, it's too late now. Like, we've moved on with our lives. And so that's another reason why kind of the customization was necessary. I had to kinda go back and figure out what the new objectives were, what the current challenges were, and kind of, uh, adjust to that a little bit. But as far as how it's changing, in many cases, I think we're moving so fast that it's no longer about what do customers want today, but what's what do customers want tomorrow? Because that's just how quickly things are moving. So we're gonna have to start figuring out ways, I guess, to be more predictive ball certainly isn't very accurate at this point. No? I think, um, as in size professionals, we're gonna have to be we're gonna be critical to making helping the businesses make these more proactive, not just reactive decisions. And, um, to play a more reactive role, we have to be strategic partners with the business. And so I know I'm always pushing my stakeholders to treat us as, uh, the consumer insights team as partners in the process and not just somebody that kinda hops in and out of the process as they as as needed. And we really need a seat at that proverbial table to really guide the company and to make more proactive decisions and create that proactive capacity. And I think, uh, trust is plays a big role in his comeback and and deploy too.

Stephanie 29:05 Yeah. Yeah.

Brianna 29:06 Now in my mind, I'm just thinking about the magic eight ball. I just need more experience. I just need to level up, and then it will turn into that beautiful crystal ball that it's gonna give me all the magical answers. big role in his comeback and and deploy too.

Stephanie 29:05 Yeah. Yeah.

Brianna 29:06 Now in my mind, I'm just thinking about the magic eight ball. I just need more experience. I just need to level up, and then it will turn into that beautiful crystal ball that it's gonna give me all the magical answers.

Leena 29:15 That's right. Yeah. I'm still working on that. Until until technology makes the magic eight ball accurate, we're gonna have to use data and insights.

Stephanie 29:24 We're gonna get there. I can feel it. Um, it's something you said reminded me of. We had a guest on recently. I don't think that podcast episode has been released, but I asked a question about, like, here's how this applies to insights, something he just said. And I was like, how do you think this applies to foresight research? And he was like, insights is foresight. And it's like what you it's something that you just said. You were like, it's not about today. It's about the future. That's where we are now. Right? Like, it's just a reality.

Leena 29:53 Yeah. It yeah. It is a reality. It's all about tomorrow. Yeah. Because today is too late. It's too late. Yep.

Stephanie 30:05 Oh, gosh. Yeah. Let's we do. We'll do our closeout.

Leena 30:09 At 10:30. So we got yeah. Yeah. 10:30. Sorry.

Stephanie 30:15 We're good. We'll cut all this too. Okay. You're up, Brianna,

Brianna 30:22 Oh, yes. Sorry.

Leena 30:24 Oh, you're fine.

Brianna 30:25 Alright. So one of your many accomplishments includes optimizing survey systems to improve both the data collection and then the reporting processes. So in your experience, what is something that survey systems typically get wrong or miss?

Leena 30:41 Uh, as far as systems, so I think there are I think we tend to want especially the stakeholders, they wanna put everything in but the kitchen sink in a survey. And so I they I'm sure there's my stakeholders are sick of me saying it because I'm always telling them you can't boil the ocean with a single survey.

Stephanie 31:01 Yep. ems, so I think there are I think we tend to want especially the stakeholders, they wanna put everything in but the kitchen sink in a survey. And so I they I'm sure there's my stakeholders are sick of me saying it because I'm always telling them you can't boil the ocean with a single survey. Yep.

Leena 31:01 And that's their reaction. And so one of the biggest challenges with what I did at EA with that process was one of the hardest things was getting people to um, land on what are you trying to accomplish with this? What it what what is going to bring you actionable data? What questions do we you know, what can if we had a player sitting in front of you, what would you ask them to make a decision about? Whatever decision is that you're trying to make. And so but getting them to that to be razor sharp with those objectives and what they really needed to know was incredibly hard. And so I think a lot of times, misses happen because they're not putting the time and effort, and it is a lot of effort in that upfront question and definitions, in in deciding what the objectives are and what the definitions of the metrics that you need to make decisions. So I think that is typically the biggest, um, gap. And, also, if you don't know what your your objectives are and what you're trying to solve for, then you can't action on it. So you're you know? That's why that that first bit is the big is, I think, is the biggest gap and the biggest challenge.

Stephanie 32:16 It becomes your map across the entire project. Right? And if you don't have that anchor, yeah, it's challenging.

Leena 32:24 Because a lot of times they'll say, well, I just wanna know. Well, that's good. I mean, I understand that you want

Stephanie 32:32 you know,

Leena 32:33 you wanna know more. You wanna understand more. But do we need to take up the player's time, which time is money, by asking them things that you need to know versus giving you a data point when with with which you can actually make a decision. So it's hard. It's it sounds easy, but it's it's it's hard. It's and it's important to put that effort into that upfront work.

Stephanie 32:59 For sure. And I think, like, Brianna and I, we can probably speak to that challenge playing out with our client base because I I think that our our sometimes our insights friends are not successful at getting that distilled with their stakeholders because a lot of times what we're having that conversation at the supplier level once we get the brief. Right? Like, what are we trying to do here? You know? Like, at at the core, at the end of the day, what are three things that you would be able to action on coming out of this? You know? And and Correct. Trying to continue that conversation in the same way. So t conversation at the supplier level once we get the brief. Right? Like, what are we trying to do here? You know? Like, at at the core, at the end of the day, what are three things that you would be able to action on coming out of this? You know? And and Correct. Trying to continue that conversation in the same way. So

Brianna 33:34 And and maintaining that throughout the project too. I think that another stage where we tend to run-in to maybe a little bit of a conversation that needs to be had is, okay. We've we've lined on what are the core objectives in the brief. Work on that survey design. Review it. Okay. Well, now they wanna send it to their stakeholders. And each stakeholder is like, can I put in this question? I have two more questions. Right? And it's like, no. No. No. We need to get back. What's the core? What's our North Star? Learning. Yeah.

Stephanie 33:58 Yeah. Yeah. Just curious.

Leena 34:00 Yeah. That North Star. And but, honestly, I I, um, I think that's why we have jobs because Yeah. They're not research. They're, like, they're not you know, this is hard. It is hard work, and it is our job. I think it is my job. It is my job to help them through that process and get to a point that you can come up with effective, actionable objectives, um, because it is hard. So Yeah.

Stephanie 34:28 Yeah. And I and we feel the same way. You know? Yeah. It is it is it's it's good for everybody to have that understanding and to be on the and be on the same page. Right? Otherwise, you're just not gonna have a successful project. So

Leena 34:41 Right. Exactly.

Stephanie 34:44 Well, Lina, uh, the conversation has been absolutely illuminating and what a fun and cool industry you're working in and sounds like you're doing so many cool things. There is a question that we really do like to ask virtually everyone who comes on the podcast. Uh, what is a piece of advice that you would offer to somebody who's just starting out in the world of insights?

Leena 35:11 I my recommendation for anybody is listen and learn from anybody and everybody you can, but don't be afraid to try something new. Experiment, test and learn. I'll share one of my favorite quotes that was from the puzzles and mysteries talk that I did, and it was from Doug Altman, who is a statistician. And he said, everyone is so busy doing research that they don't have time. Wait. Uh, let me make sure I get this right. So they don't have time to stop and think about the way they're doing it. So my advice is don't be everyone. Be somebody who does think about the research, does think about, is there a better and different way to do it?

Stephanie 35:57 I love that. Yeah. Highly, highly applicable. Great advice for anybody starting out. So, uh, Lena, thank you so much. This has been a pleasure for for both of us, I'm sure. So, uh, Yeah. Thanks again.

Brianna 36:10 Yeah. It was so much, uh, so exciting to get to talk to you. Um, I know we mentioned this off camera, but I'm a big gamer myself. Put a lot of hours in Apex Legends, uh, cried many beautiful tears, uh, It Takes Two, uh, which is a lovely game. So

Leena 36:23 It is. o, uh, Yeah. Thanks again.

Brianna 36:10 Yeah. It was so much, uh, so exciting to get to talk to you. Um, I know we mentioned this off camera, but I'm a big gamer myself. Put a lot of hours in Apex Legends, uh, cried many beautiful tears, uh, It Takes Two, uh, which is a lovely game. So

Leena 36:23 It is.

Brianna 36:24 Yeah. It It was really great to to talk to you today, Lena.

Leena 36:27 Well, thank you. I appreciate the time, and I appreciate you having me on. Thank you. Do we

Stephanie 36:42 need to wait for upload, Tiff?