128 — Packing Smarter: AI, Research, and the Evolution of Away’s Soft Side Luggage

Karen: 00:00:00

Hello everybody. Welcome to another episode of the Greenbook Podcast. I’m hosting today; it is Karen Lynch, and I’m excited to have two guests joining me today. In a moment, I’m going to let them introduce themselves to you, but let me give you the spoiler alert. Today we are talking to Jennifer Lien. She’s the UX research lead for Away luggage, which if you’re not living under a rock, you know it is sort of the luggage to have at this point in our history. So, glad you’re here, Jennifer. And Aaron Cannon. He’s the CEO and co-founder of Outset.AI. So, the two of them collaborated on some amazing work, and I’m just so glad to talk to you both about it. Welcome to the show, both of you.

Aaron: 00:00:51

Thank you.

Jennifer: 00:00:52

Thanks for having us.

Karen: 00:00:54

It’s great to have you both. I’m going to let us talk in sequence so you can introduce yourselves to the audience in a way that you can do best. And also, you know, you’re kind of introducing yourself to me. Full disclosure, folks, we haven’t had that many opportunities to meet, certainly not in person. It’s great to be with Jennifer and Aaron on the show. So, Jennifer, why don’t we start with you. Tell us a little bit about yourself, about your role there at Away, and then we’ll move over to Aaron and take our conversation away.

Jennifer: 00:01:23

Awesome. Yeah, so I’m Jennifer, and I’m the UX research lead at Away, like Karen mentioned. I oversee user research for the Away website, so I partner really closely with the digital and tech team on providing user insights and building our website to meet where our user needs are. I started my career in more of a traditional customer insights role, working at a market research agency, so I had a chance to kind of work with a range of different clients sitting at different parts of the organization, and then eventually shifted my focus more into the UX research role after partnering with some tech clients, including Google and Waze. So, that’s a little bit about me, but I’ll let Aaron introduce himself.

Aaron: 00:02:07

Yeah, it’s awesome to be here, and it’s awesome to be here with you, Jennifer. Jennifer, I get to collaborate all the time, so now here we get to collaborate on a podcast. So, I’m Aaron. I’m the CEO and co-founder of Outset as what we’ll talk about. It’s an AI research tool, and we do qualitative research at the speed and scale of a survey using AI, so we’ll get into that. And my past, I used to be a research and strategy consultant for many years, and then I spent the last decade or so leading product and design teams here at Silicon Valley out in San Francisco with tech teams. So, a little bit of everything.

Karen: 00:02:39

Cool, cool. Well, thank you for that. What you don’t know about me, Aaron, is, I have a history as a qualitative researcher. So, I spent many, many years in this industry as a qualitative researcher, an independent consultant, and then I went to a full-service firm, and I began, kind of, their—or I shouldn’t say, began because they had one in place, but then it sort of dwindled, and then we rejuvenated their qualitative practice. And then found my way to Greenbook, to kind of change up my career after 30 years, if I must say, to kind of shake things up a little bit.

So, my background is qualitative. I really love all things qual, and I love what AI has actually done to enable people to do qual at scale. So that, in and of itself, is interesting to me, just so that you both know where I’m coming from. So, let me just ask you this question. Kind of, if you think about your role—and I want you both to answer this because it’s one perspective, Jennifer, to be on the client side, the brand side, and another perspective, Aaron, for you to be kind of a CEO and a founder—but what’s the thing that—it’s a cliché question—but gets you out of bed in the morning. What is it you love about your role? What kind of brings some excitement to it at this time, Jennifer?

Jennifer: 00:03:46

Yes, so I think I am someone that’s very curious about people to begin with. And I feel like a lot of researchers say this, but I genuinely—it brings me so much joy to just… understanding where people are coming from, and like, also drawing out patterns when I get to speak to our customers, and then also bringing that directly to the business to understand, like, okay, like, we know that our customers are really caring about one thing, and then, like, how can we build a feature or website that is more user-friendly overall? But I think all of that starts with just a genuine curiosity about, like, what drives people, why people make certain decisions, how they think, in terms of patterns. So, I think that’s, kind of, what led me to start in, like, a research insights role. Not super different from where a lot of researchers I met are coming from, but just a little bit about me.

Karen: 00:04:40

Yeah, we have that—definitely have that curiosity chip. We ask a lot of questions because we are truly interested. Aaron, how about you? Kind of, what is it that you know brings you that sense of purpose in your work, and, of course, led you to found a company?

Aaron: 00:04:54

Yeah. No, it’s a great question. And yes, I think if we didn’t all have a bit of that curiosity, we would not be in this business, right [laugh]? So, you know, it may feel cliché, but it’s probably very, very authentic. And so, for me, I think that the thing I’ll point to most is just building something out of nothing. That is something that drives me, it’s why I started a company—which I started it right after I had my first kid, which is a weird decision—but, you know, just, there’s something about building stuff.

And it’s the reason I went from consulting into in-house originally, which was the idea that, like, I want to put the blocks together, I want to create a thing out of technology that was never possible or never existed, something truly, kind of, you know, n of one, and to bring that to people. And I think that’s where, like, this has been such a fun ride, which is a new technology, and really building something with it that can connect with people. And so, it’s why I did research a lot, to build stuff. And so, I think I’m very much driven by that.

Karen: 00:05:50

Cool, cool. Now, I want to make sure that we get to, like, how did you two connect, because that’s also a curious point that I have. But Jennifer, take a step back for people that aren’t familiar with your brand, tell them about [laugh] tell them about Away because I know we’ll be digging into a bit of a case study you’ve done with the softside luggage, but what can you tell people to kind of level set for Away in general?

Jennifer: 00:06:11

Yeah, so if you’re not familiar with Away, we’re a traveling lifestyle brand. We’re launched in 2016, and really one of the first to disrupt a more historically stale category of luggage and suitcases overall, with the introduction of the iconic Away hardside suitcase. It can be spotted airports, train stations, really, all over the world. They’re really great. I’m not biased [laugh], I swear.

But when we’re thinking about Away, really, is it’s not just stopping at designing a beautiful suitcase that people recognize, but we’re also committed to kind of providing our customers and community with really thoughtfully designed products that help them travel smarter and travel better. Like, I personally hear from customers all the time, that travel can be stressful, and the last thing they want to worry about is, like, having a suitcase that is going to break down, wheels falling off, and everything like that. So, that’s really what drives the Away brand, is, how can we provide a better travel experience for our community and our customers? So, I can talk a little bit about how that led us to softside, almost ten years down the line, but I can also pause, and that’s a little bit about Away.

Karen: 00:07:22

Yeah. Oh, yeah, I definitely want to get there, but what I’m curious about is, before we talk about softside specifically, like, did you know Aaron, kind of, before you took this role? How did your paths cross? Was it work you were doing on softside, or, like, what happened there?

Jennifer: 00:07:38

Yeah. So, I can start and, Aaron, feel free to jump in. But I started out Away before I met Aaron. And so, being on the digital and tech team, we’re obviously really—we care a lot about what’s coming up next in the research space, and like everyone else, we are paying close attention to what’s next in AI. So Ben, who’s our UX director, actually found Outset on LinkedIn as an AI-moderated research platform.

So, we got very curious. I’m a one-person research team, so we saw the potential of leveraging Outset to scale our research, and really, providing more speed for us. So, we reached out to Outset and Aaron for an introduction, and then the rest is history. We also both went to the same college, so that is a little bit of a coincidence, but yeah, so that’s how we met. But Aaron, I’ll let you speak a little bit to that as well.

Aaron: 00:08:36

Yeah. I mean not much to add there, other than the small world that we’d later reali—we’re more than a few years apart, but we did go to the same university, and so that was a fun connection. And then we’ve gotten to build a relationship since. We just actually got drinks together in New York last week, when I was in town. So, yeah, the rest is history.

Karen: 00:08:55

Very cool, very cool. And I like that. I love the idea that… well, we’ll get to AI in general, right, but also, the idea you [laugh], I’m sure you give a lot of people hope with the mere thought that they, like your colleague, found them on LinkedIn. Like, isn’t that sort of like a social media success story in and of itself? So [laugh], good job, Aaron.

Aaron: 00:09:15

You know, I actually—I—we won’t take too much of a detour. I have lots of thoughts there because, of course, it’s the world I live in. LinkedIn is an incredibly powerful tool right now. We are actually at—like, a lot of people in tech talk about this, that we’re at this, like, really interesting golden age of LinkedIn. And it will diminish, right? Like all social media, it gets flooded, and eventually it’s not as useful. But, I mean, that is how—a lot of our business comes from LinkedIn. So, yeah, very interesting, anyways.

Karen: 00:09:41

That’s cool. Well, I just sent you a friend request because I just realized you weren’t—not a friend—a connection request because I just realized, like, we weren’t even connected. So, expect more of those from people listening, and we’ll make sure they can find you. At the end of the show, we’ll do a how can people reach you? What’s the location? So. Anyway, good stuff. Good stuff. So, Jennifer, yeah, let’s go back to Away, and what led to, kind of, the softside. How long have you been at the company? And kind of, were you a part of the whole thing, or were you new to it? Talk to me.

Jennifer: 00:10:08

Yeah. So, I’ve been at Away for almost three years, and we started thinking about softside a few years back after I had started. So, as I mentioned earlier, Away started with the hardside suitcase, and it’s been nearly ten years since Away has launched. That is crazy. But there has been a lot of competitors that emerged in the market, and have their own version of the hardside suitcase.

But the softside suitcase the, like, nylon material, really has remained relatively untouched. So, I think with Away, we are thinking about what’s next for us. We know that over 50% of the luggage sales happening in the US are softside sales, so we’re also thinking about that’s a massive portion of the market that we just haven’t had a chance to speak with. So, we had a, like, two-plus year time to really try to make sure that we develop the product that really meets our travelers needs, and research has been heavily involved as a part of that development cycle. And, yeah, I have been a part of the whole process of building this new product line.

Karen: 00:11:14

So, is all of the work that you’ve done, you know, in the UX space—right, kind of leading those initiatives and also having nobody else really supporting you in that—is it all sort of, like, online that you’re doing now, or are you literally, like, helping people with usability of the suitcases themselves, and kind of, you know, getting in person? Like, I’m telling you, the ethnography alone, as somebody who has been a bit of a road warrior in the qualitative space, like, the ethnography alone would be the most fascinating thing. But maybe that’s purely insights. I don’t know from a usability standpoint. Like, I would probably want to just sit at airports and watch people do their thing [laugh], like, and talk to them. So, talk to me about the types of research you’re doing in your role.

Jennifer: 00:11:55

Yes. So, I’ve managed more of the website and virtual, digital space of the research. We do have a separate insights team that does the actual, I wouldn’t say ethnography, but they did the physical prototype research. So, we obviously went through a lot of rounds of design iterations, incorporating a lot of rigorous testing, customer feedback, surveys to understand what customers are looking for. We even have, like, research participants to come in and look up prototypes of the physical suitcase, and we have them, like, pack clothes, and boots, and things that we prepared for them.

We know that softside just has a very different packing—I’m getting very technical, but it has a very different packing mechanism compared to hardside, so we want to make sure that, like, we really understand, like, how they are packing. Do they use packing cubes? Do they have a system? Do they have a packing list? So, all of that is—I partner really closely with our insights team to do that physical research part as a part of the product development cycle.

But also a part of what’s really important for my work that translates onto the website is to understand, like, when a softside customer is looking for their next luggage, what type of information are they looking for? How are they approaching understanding their options online? Do they start with Google? Where do they go for reviews? So, understanding of what that shopping journey and comparison looks like, and then making sure that, like, we are addressing some of their main questions, and information they’re looking for on the Away website. So, that is more of a focus of what I do. But yeah, and just throughout the whole product development cycle, we work really closely with all the insights producing function at Away to understand how to best bring all the research worlds together.

Karen: 00:13:39

Yeah. Cool. I love hearing about the collaboration, also, with the insights professionals, more than one. Maybe they have more of a team than you have [laugh].

Jennifer: 00:13:48

Yes, yes.

Karen: 00:13:50

I’m glad that there’s that collaboration, though. I imagine that would be helpful, and I’m glad to hear that you’re not kind of operating, you know, in silos, that there is that internally. Because that’s also unique, right? Some organizations, they’re not working so well together. So, I wonder if there’s something, either in the ethos at Away, or something that’s kind of cultural or values-driven that allows for that, that you can talk to?

Jennifer: 00:14:12

Yeah, so I think we have a relatively small team in terms of everyone that touches insights, so naturally, we think it makes sense to be collaborating together. So, what we do is that, for example, during the packing research, I note-take for a lot of them, so I can also, like, observe what is happening. And when I’m running usability tests, Whitney on our insights team, will also help me note-take and then, like, feed questions in real time to say, like, “Hey, I also saw this in my research. Can we probe on that?” So, I feel like, just because we’re all coming from a very similar place of being very curious and being researchers but practice, we just naturally collaborate very well together.

We also partner with, like, our CX analysts on understanding, okay, like, at post purchase phase, like, what are customers saying? So, I feel like we have a really good, like, collaboration throughout different points of all the people that are speaking to customers, and we try to build a bigger picture to provide, like, more strategic feedback on, like, okay, these are, like, the overall themes we’re seeing across the board. Maybe I am lucky to [laugh], like, be at a part of organization that has already been built. I feel like that chemistry is already there when I joined, so it was really easy to—and it makes sense to partner with other insights team in that sense.

Aaron: 00:15:31

I was just going to add, I mean, I think Away is incredibly creative within resource constraints. And, you know, I get the advantage of talking to hundreds of different research teams, and usually when they’re siloed, it’s about bureaucracy and size. And so, in many ways, with resource constraints, Away has been incredibly creative with what they’re doing with those constrained resources, right, note-taking for each other, and collaborating. That’s why they wound up using AI, for example, right? It’s all part of that creativity within constraint that Away really has that a lot of other companies haven’t.

Karen: 00:16:03

I love that concept of creativity within constraint because, yes, when you’re faced with a challenge, and you work for solutions, you find them, and often the solution is with how you allocate your resources, even internally. So, thank you for bringing that up. That’s great. So, I just have one more kind of tangible question around that, and it’s only for—it’s really for my curiosity. It wasn’t on our brief or anything, but in thinking about this, and then we’re—I want to get into, kind of, the work that you’ve done together, the case study and all—but in your organization, Jennifer, so you know you mentioned UX, you have insights. Do you all report into the same place? Are you reporting into other areas? Like, structurally, I’m curious about… that aspect of it too, that’s kind of allowing you to cross-collaborate so well. Just give me a little glimpse of the, I don’t want to say hierarchy, but you know, the structure that you have internally of who reports up to whom, which decision makers?

Jennifer: 00:16:54

Yes. So, we all report into different teams. So, I am under the digital and tech team because I’m a part of the UX team. And then our insights team, for example, reports into, like, the business strategy team. But the other thing I forgot to mention that I think really helped facilitate this collaboration is that we have this, like, Quarterly Research Council that we do… by quarter [laugh], but basically we bring all the people that I was talking about, that, like, speak with customers, and then we do a share-out with, like, people in the more senior level, and then just help them get a really quick roundup of, like, here’s, like, all the customer insights, here’s what users are saying. Even retail.

One thing I love, and my team loves to do is to, like, twice a year we’ll go into our retail location, and just talk to the people working there and be, like, “What are customers asking you about?” Like, we see so much, like, of these, like, themes when we talk to people shopping online, but like, does that replicate in store? So, I feel like that—I kind of strayed away from your original question, which is, like, how organizationally we work, but structurally we are on different teams, but we do have, like, this, like, platform, recurring chances to, like, really collaborate together across, cross-functionally.

Karen: 00:18:15

I’m just going to say the idea of that Quarterly Research—you called it Quarterly Research—

Jennifer: 00:18:20

Council.

Karen: 00:18:21

—Council—

Jennifer: 00:18:21

Yeah.

Karen: 00:18:22

—that is, to me, a best practice, in my mind now, about what all organizations that have these different silos and pillars, you know, and different ways of getting insights work, everybody should be doing that. It’s actually a very simple, yet genius idea that I think in a large organization might be harder to implement, but I think it’s really smart work. So, kudos to you for having something like that in place. And even if it started before you got there, it’s a smart idea to share those insights. So, and it sounds actually that it’s very conversational, too, not just, you know, “Hey, yeah, you can log into the portal at any time and take a look at the other research.” Like, that doesn’t bring it to life for people. But an actual council where you can talk, that does.

Jennifer: 00:19:05

Yeah. It’s also really fun [laugh].

Karen: 00:19:07

Yeah, [laugh]. Cool. Cool. All right, so let’s go back to, then, this project. I imagine that, you know, when the reach out came to you, Aaron, that was, you know, kind of a bit of a happy day, right? So, let’s talk about, kind of, the approach, what you were looking for. Was it for one specific project? Or was it just, I want to know this partner? Talk to me about the beginnings of this, and then we’ll get into, you know, what you learned.

Jennifer: 00:19:34

Yeah, so I think we reached out to Outset, just because of what I mentioned earlier, we saw the potential of this, kind of, helping me, as a one-person UX research team, on lifting some of the workload, getting a scale and speed that just, like, by, like, a human researcher can’t really replicate. So, we were just super interested by the tool and wanted to see, like, how—honestly, we wanted to see how well, like, AI moderators can do these days, also? We didn’t have a specific project like softside in mind, but I think the timing coincidentally worked out really well. But yeah, we just wanted to reach out to, like, understand the capabilities to begin with. So, yeah, yeah, that’s what drove us to reach out to Aaron.

Karen: 00:20:21

So, tell us kind of your side of it, Aaron. Like, chime in about what that was like and what you wanted to show them or tell them.

Aaron: 00:20:28

Yeah. Yeah, so I—we’ve now met so many times, I don’t really remember the first conversation [laugh], right? Like, it’s… it’s like, you don’t really remember the first, you know, time you met somebody. But I do remember there was a lot of interest. And this is not unlike a lot of other companies we work with that reach out to us. A lot of, like, curiosity, a lot of interest. There’s not always a use case in mind because you haven’t even thought about what could be the possibilities. It’s more of, like, you hear about it, you think about it. It’s like, I just want to, like, understand it.

And I think from our standpoint, what we look for in the first call, like, other than you, you know, is this a company a good fit for all sorts of, kind of, practical reasons, but ultimately, is like sharing that this is probably better than you think already, and it only gets better. And from our standpoint, if everyone in the industry, just like, adopted some form of AI-moderated research, whether or not it was with us, I think that would be a great thing for the industry, I think a great thing for us. And I’m happy to, like, talk more about what that means, but ultimately, it’s like for us, it’s just evangelizing the fact that this is possible, and it’s valuable today, and it keeps getting better. And like, that’s what our first conversations were about.

Karen: 00:21:36

So Aaron, I want to stay with that for a second because—

Aaron: 00:21:38

Yeah.

Karen: 00:21:39

—again, without, like, kind of going into, you know, this being just promotional for you, what you’re talking about is this evangelization, which I find really interesting. Why do you think that’s important to evangelize the possibility of AI assist for qual at scale?

Aaron: 00:21:54

I think that with any new technology, you have the, kind of, struggle of not just adoption because of, you know, skepticism, but just like people haven’t imagined the ways they want to use it. And so, from our perspective, again, like, not to be self-promotional, but from our perspective as a startup in this space, like, the more people are opening up their imaginations of what they could do, what they could theoretically accomplish, either about timelines, or about scale, or about net-new use cases that you haven’t even thought of, like, the more you open it up, the more everything will be adopted, all technology will be evaluated and looked at. And like, I mean, that’s the best case scenario is that we’re, kind of, super fast to adopt, you know, new technology across the board.

Karen: 00:22:39

So, and I want to pause there for our audience because you might have been starting thinking about it in advance, but October 2022, which is when generative AI—really, within weeks, generative AI hit the scene. So, the timing was right, right? Everybody started talking about this. How did you get people to—and don’t tell me anything proprietary; that’s not what I’m asking for—but the hurdle of putting money towards an unknown, I imagine, is a big one, right? And then, Jennifer, maybe you can talk about this in a moment. But how do you get partners to put money towards the unknown of something I’ve never tried before, we don’t know how it’s going to turn out, it’s hard to trust a brand-new partner, let alone a new-to-me partner. So—

Aaron: 00:23:28

Yeah.

Karen: 00:23:28

[laugh].

Jennifer: 00:23:29

[laugh].

Aaron: 00:23:29

It’s a great question. I have a couple of elements to it. So, you mentioned ChatGPT coming out. The beautiful thing about ChatGPT is it was this, like, way that you could start imagining what AI could do, right? So, like, I was out here in San Francisco, hacking away at cool AI stuff earlier, and like, we were all, you know—the tiny little bubble over here was excited about it, but the world hadn’t really opened up the imagination to it.

ChatGPT created this, like, oh, like, examples were hitting—you know, I don’t know if you remember social media then, but like, everybody was like, “Look at this thing I did. Look at that thing I did.” And so, suddenly it reached everybody. And I can’t remember, in my career, a moment in technology that so reached the, like, kind of, cultural resonance that ChatGPT got to, which was a benefit to every AI company that’s—or every company that’s incorporating AI. So, that was kind of step one to creating comfort.

Step two was the first six months of our business, it was really hard. Like, we were doing a lot of—you know, doing as much in the way of sharing examples, and case studies, and that continues to be a big strategy of ours. But it was tough. I mean, I would say in the early days, we were totally convinced by what was possible here. We had a working product that was valuable for the customers that would take us on, but I think in those early days, it was just so new and so difficult to be comfortable.

ow, during this year, call it: 2024

Karen: 00:25:36

Yeah. Cool. It does, it does. So, Jennifer, why don’t you talk to me a little bit? Because again, you took the risk, right, by, first of all, working with, you know, kind of a startup, but also in this, kind of, new-to-you methodology. And I’m sure there’s something appealing about a startup that I’d love to dig into next, but first of all, talk to me about the risk, and you saying, “Okay, we’re going to do this.” Like, what made it worth putting some dollars against to try something new when it could also be, you know, a financial risk for your company?

Jennifer: 00:26:03

A very fair question. So, I think, like Aaron mentioned, we reached out. I think, I believe, like, beginning of this year. So, at that point, we all have had a lot of time to play around ChatGPT. I think that, like, user interface that ChatGPT was able to create, made it, how do you say it? It, like, makes sense in our minds that, like, we can imagine a tool like ChatGPT doing a moderation, so it wasn’t that crazy to think about this idea.

We had a chance to work with Aaron on a pilot project to understand, like, okay, on top of what we were able to test on the interview side, like, what can we also use on the back end? Like, when we have so much data, how does the analysis look like? Because it’s very different when you’re analyzing data from 20 people versus, like, 75. So, we thought about using softside as, like, just kind of like the perfect timing as a pilot research. This was beginning of the year, and then softside launched this summer, so we had that six-month period where we had done a lot of research on softside, and a part of it, we thought it made sense that—we probably would have used a traditional survey for it, where we were like, let’s try out this tool that is literally giving us survey capability, but at that in-depth, like, interview, usability test level of qualitative insights.

So, I think that was the first thing that we felt comfortable enough with the constraints that we have that we’re able to use to help us understand, like, is this, like, an investment that we want to make for the long-term? So yeah, it made sense, I think, at that time.

Karen: 00:27:38

And was there anything about—the second part of what I was curious about—anything about, like, just working with a startup specifically? Like, did that bring anything to the table? You know, I can imagine, and therefore it feels a little as a qualitative researcher, a little leading, to say, “Talk to me.” But we do have a lot of startups, and wanna-be startups in our audience, and I think that there is something to be said for just calling it out, and saying there’s something unique about working with startups. What’s your point of view on that?

Jennifer: 00:28:06

Yeah, I think the sense of—it’s maybe less so about working with the startup, and more so working with the technology that’s so new. And we believed in what Outset was providing, just the ability to help us as researchers to do better research overall. But in terms of working directly with startup, I think it’s more of, like, a personal interest. Like, both our director, Ben, and I are very fascinated by, like, what’s next, what’s new? And that made sense, but I don’t know if it necessarily has to do with, like, the broader organization, or it was just us being very excited [laugh] about new technology and new companies.

Karen: 00:28:47

Yeah. Well, and I think what you said is key, is it starts with the personality of people that are just interested in what’s new and what’s possible. That’s a mindset, right? That’s a growth mindset that’s very different than somebody who wants and/or needs organizationally to stick with what’s tried-and-true, and potentially, you know, reliable because it’s been seen before. So, I think those are two different mindsets.

One is not better than the other, but one might lead to a different type of a partnership, so I love it. Let’s talk about what you learned, then, and whether there was any kind of breakthroughs, some great insights that you can share, anything that came out of the work. And then, of course, we’ll also talk about maybe some of the challenges along the way. But let’s start with some wins for the initiative.

Jennifer: 00:29:30

Yeah, so we worked on the softside project. So, like, taking a big step back to, like, softside, so this is not a product that Away has really had in the past. So, we know that there are people that are just softside people. They are very loyal to the type of material, and that type of suitcase that they’re comfortable traveling with, but we don’t have a lot of knowledge on, like, why they are softside customers, what drives them, and like, what specifically about this product and the features that are important for them. So, I think we wanted to use this research as a very exploratory research, early in the beginning, to understand, like, what do we need to—what product education do we need to provide? What kind of visuals do we need to provide on our website to speak to this specific type of customers that are interested in this very new product that we have not had, really, before?

t from having [unintelligible: 00:30:27

And the second thing is, also with the scale, we’re able to, like, have a better understanding of, like, from the insights we’re getting back, like, how prominent are each of the themes? So, we can say, like, everyone says that durability is important, everyone says flexibility is important, but like, how do we prioritize that, like, information hierarchy is also something with, like, a larger sample size, it gives us, that I found very valuable.

And then I think lastly, also this—yeah, speed is a big thing [laugh], like, obviously, with, like, every—I feel like, with every company, it’s like, you can always be faster and more efficient. But for us, having the speed with using a tool like Outset, we were also able to have insights that are early enough that we’re able to actually, like, request assets from other teams because we have this speed that, like, of the insights that we’re able to make. So, an example would be, like, we understand that softside customers, like, really care about if the material is waterproof, for example. And so we’re, like, okay, like, so many people mentioned that they want to make sure that their softside luggage can withhold, like, rain or something. And we’re able to use this piece of insights, and bring it to our creative team, and ask them if they can provide some type of video to show, like, how, like, the water literally, like, falls off the material, and it’s easy to clean, to show that in a very visual way on our website.

And this takes time. Like, requesting assets. There’s, like, scheduled photo shoots that happen, and so you really need to have that piece of insight early enough to provide that on the website. So, I think coming from that speed piece of using Outset this also just help us create, like more informed and, like, faster impacts that we’re able to bring to our product page when the product launched. So, yeah, I think that’s, like, kind of the impact of, like, having a tool that we haven’t had before was able to give us. And then in terms of specific insights, which I can talk a little bit more about, but I’m going to take a pause. I think I am personally really excited that we had this tool, and was able to, like, make a very tangible impact on the website.

Karen: 00:33:06

Yeah, and Aaron, I’ll let you talk more in just a second. One of the things that as I’m listening to Jennifer, I’m thinking, again, with my qualitative hat on, that prioritization of those themes, you know, as a qualitative researcher, if I was out there, and I was doing, you know, say we only had a couple days, and I could do, you know, 12 interviews. Maybe I could do, maybe I could do 20, if it’s—you know, but even that, like, there’s always that economy of scales with such a small sample size. You’re, like, “How many of these are we going to do?” And because it’s qualitative in nature, you don’t necessarily—you could share out what the themes are, and you can maybe use some creative intuition about—which is my new favorite phrase, by the way that I heard last week—but you can, you know, maybe glean of what you think, based on your experience, based on the passion that people talk about a theme with, or whatever. But I like the idea of that prioritization of themes bubbling to the top once you bump it out to scale. And I bet there’s a lot of qualitative researchers who are suddenly like, “Well, that’s interesting.” So Aaron, talk to me more about that functionality.

Aaron: 00:34:11

Well, I mean, I think the one question we often get from qualitative folks, maybe like yourself, is like, “So okay, cool. I believe you can do scale, or, I believe AI can give a scale, but why do I care about scale?” Right? And so, you know, I think that’s a—there are many cases where that isn’t important, right? There are cases where you’re like—and I used to do a ton of this in my—particularly as a consultant, we would do, like, these very deep ethnographic style in people’s homes, like, you know, that kind of research, and often you’re just picking out something very deep, and interesting, and some kind of tension that you would never have discovered, and like, that’s a beautiful thing, and you need that.

But then you have that, you have to go make business decisions around that. So, often the question is, what is our confidence in the prevalence of this? Or the questions are, what matters more? We have a trade-off, right? Or, you know, a big one that we get is, like, great, that makes sense for this person, but what about ten other segments and four other markets, right?

And there’s just—you wind up extrapolating very deep, interesting nuggets across large populations when you’re building, particularly for consumer, but even for a B2B. And, like, so you wind up in this tension. Which is why a lot of researchers bring mixed methods, and you bring a survey in, and then you bring this in, and they bring that in, a diary study, you know? And you just, like, wind up piling on seven methods because that’s how you’re able to get nuggets and extrapolate. And so, I think we have a lot of, you know—that’s ultimately what often is the question that comes up of, like, why does scale matter? And here, you can very quickly see, can we compress seven methods into one or at least a couple, right? And I think that’s a lot of what Away did.

Karen: 00:35:49

Yeah, it’s cool. No, it’s cool. I’m hearing everything with, again, with my researcher hat on—and to the researchers listening, I hope this is what’s happening with you, too—is thinking, like, yeah, it’s a pretty compelling use case in and of itself. So Jennifer, let me ask you then because one of the things that I know you had talked to our producer about was sort of how, you know, some of the results from this work actually increased your Add to Cart rates on your site. So ultimately, we got there, right? So, talk to me a little bit about the softside launch, and how it’s been a successful launch, and how you kind of were a part of that.

Jennifer: 00:36:27

Yeah. So, I think the two biggest things that we learned from the research is—about softside customers in general—is that durability is still very important for softside customers. We know that durability is, like, the most important thing for, like, hardside customers, but what came out from softside customers is at durability still top concern, but how they evaluate durability is very different from how hardside customers are thinking about it, just because of the material itself. So, as a result, we know that we really have to provide details about the materials that speak to, like what I was saying earlier, the material resistance to, like, weather, stain, tears. These are not something that hardside customers are thinking about.

So that’s, like, a piece of, kind of, concerns that, like, kept coming through as we speak to customer, either through Outset, or when I interviewed them, or through, just, like, all the research that we’ve done, that is very prevalent. And the second thing is that the softside customers are thinking about packing in a very different way, in terms of just, like, the different—like, clamshell versus, like, top lid opening, that is something that softside customers really prioritized as they were thinking about how they pack. So, I think, knowing those two things, we ended up building a specific page that’s just about, like, material education because in the past, we only had our polycarbonate hardside suitcase, which is the first one that we had launched with, and then we have aluminum, which is for, like, a very specific type of customer. So, now we introduced a third type of material, which is the nylon softside. We’re like, okay, we need to have a material education, or even some sort of comparison page coming out of the research that we saw earlier.

And the Add to Cart rate that we mentioned earlier was from that page, in terms of—it’s a very specific page for, like, people that are deciding between materials, and that are really thinking about—they’re more like mid to lower funnel, closer to thinking about a purchase, and that page, we want to really speak to that specific set of customers. So, throughout our research, like, we mentioned earlier, like, the durability and the packing piece, we were able to provide just information there that had a higher Add to Cart rate compared to our other landing pages. So, that’s something that I would call a success.

Karen: 00:38:43

Yeah. It’s just, it’s cool, and you know, I can’t help but think that there is information that you can compile qualitatively at scale that will then also bring to mind other questions you may ask down the road. And, Aaron, I’m going to ask you to correct me if I’m wrong, but we were talking about how a researcher might need to, you know, do some qualitative, and then they’re like, all right, but we have to, you know, validate this work, or we have to build on to it, add on to it, and kind of have this multi-method, you know, project where we’re doing a lot of things. Calling it a hybrid is, like, to say the least. But now we’ve got—especially if it’s exploratory, like Jennifer’s need might have been—to blow out the, what are all of the things we may want to look into down the road, like, it feels to me, like, it would be very holistic in approach. But, again, am I way off there? Or is there some truth to the holistic nature of what you’re doing at scale?

Aaron: 00:39:41

No, I mean, you’re not off at all. There is an interesting thing we see, which is like, okay, well, I’ve done 100, 200 interviews, and now my main things I’ve tried to learn, I’ve learned, and I’ve gotten them to scale, et cetera, but there’s, like, a treasure trove here of more data. And you ultimately, like… it raises lots of questions, which might spur the next set of Outset interviews, or next set of research period. You also have, just, like, they’ve answered questions you didn’t think we’re going to be asked, right, because of just the nature of a qualitative conversation. And that becomes a treasure trove for later, right?

And we’ve, like, even used that inside ourselves to build out more, like, chat with your data features where you can, you know, grab more bits that are interesting over time. But, yeah, I mean, it’s almost, like, a very pleasant side effect, right, like of, when you get a lot of qual for one purpose, and you wind up unearthing lots of other things.

Karen: 00:40:33

Yeah, yeah. Super cool. Super cool. Well, you know, remember, I think I said to you at the beginning of this, we tend to try to keep these at 40 minutes. And I tend to always, you know, look and want the conversations to go on and on, so this is the point where I pause and say, you know, to both of you, what do you wish I had asked that I didn’t ask yet? Because, you know, we’re running out of our time together here. So Jennifer, is there anything you wish I had asked you that I didn’t ask yet?

Jennifer: 00:40:57

Honestly, nothing comes to mind immediately. I feel like I spoke so much about this project, as well as our partnership with Outset and Aaron, so I don’t know. I’ll toss it over to Aaron and see if there’s anything else you want to share.

Karen: 00:41:09

Yeah, Aaron, for you, I’m sure you’re like, “Oh yeah, I could share a lot.” So [laugh].

Aaron: 00:41:14

[laugh]. Well, one thing I often get which I always like to talk about, which is, like, what is AI doing to research in general, right? So, like, I have a bunch of theories about this—kind of, regardless of Outset, right; it’s kind of outside of Outset—so I could talk to that for a quick second—

Karen: 00:41:29

Yeah, I’d love that.

Aaron: 00:41:29

Which is just, like, because I think there’s a lot of, like, there’s excitement about one foot in front of the other, how can I use this today, how can I use it tomorrow? We’ve, in the world of AI-moderated research, it isn’t that big of a step. As I said, it’s like a cross between a survey and an interview. Worst case, you’ve got, like, a deeper survey. It’s a pretty accessible thing to try.

But then we take a step back, and we all kind of get freaked out about what’s the world look like in ten years. And I think, you know, the case I like to make is, like, I very much believe that AI will actually expand the amount of research that we do, period. And isn’t that a good thing, right? Like, isn’t it good that we are more human-oriented, that we have more human voices in our work? And, like, a small example of just using today’s product of an AI-moderated research, it’s like, there are companies that are not doing international research. They just—it’s just too expensive.

But AI can actually speak any language, right? And so, you wind up, “Oh well, even if I’m not going to invest heavily, I’ll at least gather something from that market.” And then you’re like, “Oh, my God, there’s something there.” And so ultimately, I think it, like, has the ability to make surveys more qualitative, it can make analysis of lots of data much more doable by a person in very small amount of time, right, and third is, like, it can expand the footprint of research. So, imagine if you had a human researcher who could just jump on every customer support call you had, or you could send out with every shopper that enters the store, or every online, you know, shopper that’s, like, going through your flow.

Like, if you could just kind of put a little mini-researcher everywhere, imagine, like, how much more you would learn and understand. And like, we’re very much at the start of this. Like, this is a future, kind of, opportunity. But it’s not this, like, you know, zero-sum game, where we’re all just trying to chop up the same small pie. It’s like, I really, really believe that AI will bring us more of humanity, more of people and their input into our work and, like, then we’ll go build better stuff [laugh]. Like, we’ll go build the experiences, and the products, and all the things that are more, you know, more meeting people where they are and what their needs are. So that’s, kind of, my hopeful message that I’m really excited about, that I’ll share.

Karen: 00:43:41

Aaron, I’m just so glad we have that, not only on tape, but we’re going to share it out because I’m sitting here thinking like, yeah, man, that’s the TED talk, right there [laugh].

Aaron: 00:43:49

[laugh].

Karen: 00:43:49

That is so good. That was really good stuff. So, thank you—

Jennifer: 00:43:53

Can I add something on top of that, as well?

Karen: 00:43:55

Yeah, please.

Jennifer: 00:43:57

I feel like when it comes to AI, we have a very high bar for, like, what AI has to pass, and it usually has to be, like, better than human for us to feel like, safe and comfortable with adopting a tool like that. But what, like, this, like, Outset tool has, like, allowed me to do is that it, like, freed up the work that I have to do with a lot of time, and it actually frees up, like, me to, like, be able to do more, like, strategic and, like, foundational research to, like, translating the insights into, like, what does this mean for the Away business? So, I feel like a lot of people probably approach this with, like, “Oh, my God, like, our job is going to be replaced by AI,” but it’s actually, like, it’s totally going to take a long time for AI moderators to get to, like, a human moderator level, but I, like, how we had the chance to just, like, jump in and, like, see, like, what it can, like, help us free up space for, like, just, like, more, like, strategic research overall. And I think it’s like, super exciting to see what’s next. But yeah, very—just, like, fortunate timing, I think, also, with all of this project and where the technology is going.

Aaron: 00:44:58

Yeah, I think just to expand on the idea of, like, what is the role of a human like? That’s, again, is super-futurist, right? We’re talking about many years away, what is it—like, and I think across all industries, we’re looking at humans being more, call it—I like the analogy of, like, a symphony. Like, more of a conductor than a violin player, right? Which is to say you have at your disposal incredible tools and technology to get to the strategic outcome, the business result, the products that you want to build, you are in the—figuring out the right strategy to get there, and you just have incredibly powerful tools, incredibly talented musicians to play with.

So, that might mean sometimes playing an instrument or one or the other, but it also may mean bringing them together. And so, I like that, like, idea of, like, from the kind of pure, you know, kind of narrow practitioner, to the strategist, right, that can kind of shift in that. And so again, this is not today talk. We’re talking about in the future, but it’s another, like, element that fits into my broader TED talk, as you said.

Karen: 00:45:56

[laugh].

Aaron: 00:45:57

So, it’s an element that fits in nicely. It’s like, it is actually, like, a future is with more research and more humanity coming into what we’re building, and at the same time, the role becoming more strategic, more impactful in a lot of ways.

Karen: 00:46:11

Yeah. And you know, not only what you’re building, but also what companies like Away are building, like, tangible products, where that kind of feedback is critical for the R&D teams to, you know, do what they’re doing. Also, you know, so not only did you learn about, you know, getting those Add to Cart rates up there, but also, you know, I’m sure there’s nuggets in there for the R&D team who are now thinking about what’s next, what’s our next product innovation. Which I’m not going to ask you to talk about; obviously proprietary. But yeah, you know the possibilities for anybody who, you know, has any kind of design thinking in their processes, the possibilities are great when you get a little help. So, pretty cool, pretty cool stuff. Any other final words before we wrap?

Aaron: 00:46:56

I just went on a trip this past weekend with my kid and wife, and we brought, I think, three Away bags at once.

Karen: 00:47:02

Nice.

Jennifer: 00:47:03

[laugh].

Aaron: 00:47:03

And I just thought about that. The whole trip, I was thinking about this conversation because we were just surrounded. And every other person at the airport had Away bags.

Karen: 00:47:11

That’s great. That’s great.

Aaron: 00:47:12

I love to hear that.

Karen: 00:47:13

Yeah, I don’t have my first yet, and I’m sitting here thinking, like, “It’s time,” now that I’m getting off here because, you know, it is time. It is time. My luggage takes a beating anyway. So yeah, it’s time for me, too, Jennifer. Let’s make—speaking of evangelism, let’s make Away luggage [crosstalk 00:47:29].

Aaron: 00:47:29

There you go.

Karen: 00:47:29

[laugh].

Jennifer: 00:47:30

Yes, now you know someone that works at Away, so—

Karen: 00:47:34

[crosstalk 00:47:34] a little email on the sly. So, all right, speaking of emails, if people are looking for more, where can they turn for more information about both your organizations? Jennifer, we’ll let you go first.

Jennifer: 00:47:45

You can find me on LinkedIn, Jennifer Lien L-I-E-N. But my email is jennifer.s.lien@gmail.com, so that’s how you can reach me.

Karen: 00:47:56

All right, great. And Aaron, how about you?

Aaron: 00:47:58

Yeah, so you can check out the company at outset.ai. That’s the domain. And I’m aaron@outset.ai, so please do reach out. And obviously, go check me out on LinkedIn. That’s how [laugh] Away found us, and probably how—you’ll learn I post all our demos, and all sorts of interesting things, so check me out. But that’s about it. And so, thank you so much, Karen. This has been awesome.

Jennifer: 00:48:19

Thank you.

Karen: 00:48:20

You are both so welcome. Thank you for joining me. It’s been a real pleasure and a really interesting conversation, so I’m grateful for you both and for the work that you did that you decided you could share with us. So, glad you reached out. And also, this is my time to thank our producer, Natalie Pusch. Natalie, thank you for all that you do to set us up for successful conversations. So, thank you so much for that. Our editor, Big Bad Audio. I’m really glad you do what you do as well, so thank you for cleaning things up so that we sound better out there in the world for our listeners, who is the last group that I’ll thank. Thank you for tuning in to the Greenbook Podcast. We will see you again. Take care.