Episode 12: Kathy Cheng, inca

Episode Overview

Kathy Cheng, founder and CEO of inca, on why better survey experiences produce better data — and what the industry needs to change.

Episode Highlights

• From qual to quant — by accident. Kathy built inca out of frustration with traditional surveys, bringing qualitative thinking — projective techniques, conversational flow, participant engagement — into quantitative research at scale.
• The participant experience problem. Poor data quality is not the fault of respondents. It is the result of survey designs that have barely changed since the 1930s. Improving the experience improves the data.
• AI as part of the whole, not a bolt-on. inca's AI moderation capability is central to the product, but Kathy argues that conversational AI embedded in a poor overall experience will not deliver meaningful results on its own.
• Synthetic data: a useful tool, not a replacement. Kathy sees synthetic data as a short-term response to declining survey quality, and worries that adopting it at scale means giving up on the belief that people have genuine things to share.
• The blurring of qual and quant. The more significant shift in the industry over the next few years will not be technological — it will be human. Researchers will need to develop skills across both traditions to get the most from new platforms.
• Always go to a meeting with an ask. The single most useful piece of business advice Kathy has received — and one she now applies consistently as a self-described introvert running a growing technology business.

About the Guest

Kathy Cheng is the founder and CEO of Nexxt Intelligence, the company behind inca — which stands for Inquisitive Natural Conversation Agent.

She started her career as a qualitative researcher and founded the business around a decade ago with a simple idea: that surveys should work more like conversations. inca combines structured survey tools with AI moderation, projective techniques and conversational probing to improve the participant experience and the quality of the data it produces. The platform is used for both quantitative research and qualitative research at scale.

Learn more about the impact of technology and AI on research, insights & analytics at Insight Platforms.

Transcript

Mike 0:11

Hello everyone and welcome back to another episode of the Insight Platforms Founders and Leaders series. And today's episode I'm joined by Kathy Cheng, who is a longtime collaborator with Insight Platforms and a good friend of our business and is the founder and CEO of Nexxt Intelligence and inca. So Kathy, welcome to the show. Great to have you here.

Kathy Cheng 0:35

Thank you so much, Mike.

Mike 0:38

I introduced you as Nexxt Intelligence and inca, do you wanna just give a, a little bit of background to, you know, to that the business where it came from and why? I've used two different names there.

Kathy Cheng 0:51

We get that question all the time. We really probably should fix that. So we usually say we're from inca, and inca stands for Inquisitive Natural Conversation Agent, and Nexxt Intelligence is the company behind inca. I do believe inca is probably better known now'cause we, when we go to conferences, that's the brand that we use most often and it does stand for something'cause, hopefully it tells people exactly what we do just based on the name. So what we do is we try to turn surveys into conversations. So instead of like a single dimensional question answering session surveys can be interactive, can be a conversation. So that's the main purpose.

Mike 1:30

Your background was in qualitative research. Is that right? Before coming into this to, to revolutionize surveys

Kathy Cheng 1:37

That's actually that's the, that's the main reason why I started the business. Yes. Like you said, I. Do consider myself deeply qualitative. I still do believe that's the case. I started my career, first half of my career, only qualitative. So I, I do like qualitative a lot. By the time I started to do quant, I started to realize I really, really quite disliked quant. because everything the way we conducted quantitative surveys, everything seems to be opposite of how we did qualitative research. Then at the same time, the whole industry, I noticed at least the whole industry was talking about bad respondents, and we came up with all kinds of smart ways to kick out the bad respondents. To me, that was just counterintuitive because for Qual don't, we never complained. The respondents are bad. We say the moderator, you are not doing your job engaging the respondents, and if they can't answer your questions, it's not their fault. It's because your questions are too hard. You're not using, example, projective techniques to enable them to think about what they can how they can answer that question. So all these to me it was just counterintuitive. So when I started the business, the, the idea was fairly simple. I just thought, okay, maybe instead of fixing the participants, the respondents, maybe we should fix the surveys themselves. So the idea was what if we add all the. Good qualitative dimensions into a quantitative survey. Meaning what if we try to engage participants? What if we try to provide them with an experience that is slightly more interesting and possibly more meaningful to them? what if we ask questions in a way that they can answer, they can find the answers for us and they can articulate themselves better. what if instead of making. A long list of choices for them to just read it and then click and click if we can just listen to them? Because a lot of times we know that there are a lot of limitations of quant surveys, but that's the, that's the reality. If you want structure, that's the only, only way you could do that with a large sample size. So yeah, that was the beginning of the, of the, the journey. The idea was fairly simple, was just to add all the good elements of qualitative into upon surveys.

Mike 3:57

Okay, great. So how does that you know, I've seen some of your recent campaigns have been, you know, I think make your quant a bit more qual or, you know, that, that type of thing. What does it actually mean in practice then? What's the participant experience and how is it different from what they might get, you know, completing a standard survey, what do they actually do as part of their, their inca experience?

Kathy Cheng 4:21

So for anyone who have done surveys, I would think they probably agree. It's just a single dimensional thing. It's you reading a lot of questions, click the boxes. If you have other ideas, maybe there is a other option or maybe there are. Very few open-ended questions and, but, but in the middle of clicking those boxes, it's, it's, you're probably not motivated to answer those open-ended questions very well. The way inca surveys work is we turn the whole experience into a conversation, even for close-ended questions, choice questions, scale questions. We still have all of those because it's a survey platform. But it's a conversation. There is a, a moderator asking those questions, even if it is structured, even if it's a tool, even if it's a deep dive tool, a heat map, all that. It's always delivered. The questions are delivered as part of a conversation. So then when we do need, need a little bit of like a mini in-depth interview, a little dialogue, it's embedded in that format already. So we, we do see people are, it's quite. It's a natural transition between open-ended and close ended. So, yeah, so then it's quite easy for them to just continue with the conversation and open up and share their thoughts. So yeah, the whole experience is quite different a traditional service.

Mike 5:36

Okay, so you've got a you've got elements that are structured so, you know, choice questions or, or drag and drop and that type of thing, as well as the conversational AI kind of, you know, moderated probing that, that you combine with that. That's how it works.

Kathy Cheng 5:51

Yeah.

Mike 5:52

Yeah.

Kathy Cheng 5:52

conversational AI or just AI probing? Moderate what, what, what do we say now? AI moderation. Yeah. As a leader, should we say AI moderation a lot now? The way we look at it is it's just a part of what we do. It obviously is important. It's it's a core piece of technology that we have built, but it's really just a part of the whole experience. We do believe if we embed this conversational capability into. A boring experience. It isn't gonna work. It's not the super bullet. It's not like all of a sudden you have a conversation. Oh, someone else on the other side seems to understand what you have just said after you have just gone through like five batteries of statements that isn't gonna do the do the magic. So yes this is one of I think the other pieces I'm possibly more excited about, for example, projective techniques. I do believe that makes a huge difference. And depending on the demographics, sometimes we can turn it into an immersive game. So it does change the experience quite a bit. And also the tools, I mean, for qualitative moderators, we use tools. You, you are a quality as well. You, you remember the, the good old days, well just give people a piece of paper with a concept. We say, okay, underline what you like, like all these simple things, but. That's part of what we do as well. It's it's easier for us, it's also easier for the participants when they have a tool. It, it's easier for them to, to actually look at the concept in more detail and then provide more specific comments. So, yeah, so the tools. Projectives, the, the overall ui, a lot more interactive, a lot more familiar. They're like surveys. We create this very arbitrary environment as if we would be doing exams all the time, but we don't. We're humans. We chat with our our friends and all that. So the whole environment, the whole experience is a lot more familiar. So I think it's the whole combo that, creates a very different experience from so this is actually interesting because this has evolved quite a bit in the past few years, I'd say. Initially when we started to market inca, we, we, we, we had the platform first, but then we, we realized a lot of clients didn't necessarily see experience. A problem yet some time ago. I mean, even today we're catching up. I, I do feel this is not a foreign concept anymore. More and more people are talking about participating experience, but still not enough, I would say. But not too long ago, this wasn't, I would say. I remember an end kind once said to me, this is really interesting, but honestly, I have to say, I don't care. I don't see it. So this is like, I, I only received my report. So I really appreciate that, that candid feedback. I remember talking to a, to an investor they, they said, this is all very, very interesting, but who are your paying customers? Why do you focus so much on participants? They don't, they're not your paying customers. You really should be focusing on paying customers. So I'll just say the whole participant experience, it's always been there, but I. Don't believe was it was a high priority for quite a long time. the reason I want to mention that is when we started to market inca at that time, we had our platform first. But what clients seemed to be most interested in was the AI bit. They were interested in having that conversation. They didn't seem to look at the whole platform as as a whole unit like this. They, they felt like it would be easier to be it would be less disruptive for them to add the conversational capabilities into their existing surveys. So that's how, that's what, that's why we launched the smart probe, API. It's a very successful product. It's really, really wonderful. We, we like it a lot, but we always saw it as our beachhead. We then we would have a, a opportunity. demonstrate the power of that, but then we always believe it's not just that. So once you have experienced the conversation side of everything, hopefully you'll want to change the, the, the overall experience as well. That's definitely happening. I'm very, very happy to see that. I, I feel like more and more conversations are more about the overall participant experience, not just the AI capability, but overall, how can we make it more. Engaging, enabling and exploratory. That's kind of always,

Mike 10:14

Yeah.

Kathy Cheng 10:15

yeah.

Mike 10:15

Okay. You think people are starting to recognize the connection between better participant experience, more engagement, higher data quality, more meaningful now? Do you think they're making that?'cause it sounded like the client you spoke with. I didn't really appreciate that. It was a little bit like, well, I don't care about livestock standards. I'm just gonna eat the beef. You know, it doesn't matter what happens, you know, in the, in the factory, but in this case, you know, it really does have a through line to the quality of the data you're working with, doesn't it? If you're, you know, if you're not engaging, but there are people seeing that more these days.

Kathy Cheng 10:47

I think so. I think yes, more and more people are paying attention to the participant experience and also as an industry we have seen more and more research on research reports talking about how powerful part. Participant, when the participant experience is improved on how we see the data quality gets improved, how the depth of insight is improved as well. So, so all that is helpful, think yeah. So maybe in the past I don't know, this is probably me, but I, I do feel like our industry has. It's been quite negative for a while now. So I feel like for a very long time the focus was on the problems. The focus was on. If the data quality isn't there, it's because of the bad quality of respondents. It's the panel's problem. It's been a while now, but I think more and more the conversations that we've been having with our clients seem to indicate we're now seeing, no, it's not. Just that it's after you have the quality participants, what kind of experience you are giving to the participant. It's both things working together. So I'm really delighted to have more and more conversations with clients focusing on how to reinforce a more positive experience. I feel like it's. simply wrong to assume that people don't want to take surveys. I think we've been working on that premise for a very long time now. We basically assume that they are bad respondents. They don't want to take surveys. The few sense they, that's just not enough to incentivize them. I don't think so. I think we, what if we think like, I think people when they join panel. They have things to say. They want to share their opinions. what if we believe that is true? I think we have to believe that is true. then on top, if that, if that is true, if that's logical, then what? What if we can focus more energy as industry on. Providing these people with an experience that they can express themselves. They, they, they enjoy sharing their opinions. So I, I do feel that this is changing and that this kind of conversation energizes me. I.

Mike 12:59

Yeah. Okay. I think you, you'd find a lot of enthusiastic supporters in some of the panel companies as well, actually, who would say Yes, of course there are, there are quality issues and there are challenges, but stop beating our panelists over the head with these interminable survey experiences that are just awful on the eye and, you know, and difficult to follow. So I think you're you're definitely onto something there. And, you know, one of the worlds I've worked in over the years in you know, proprietary panels and communities, there are absolutely people who are very willing to participate, give feedback because they're intrinsically motivated for. A whole range of reasons. They care about the category of the brand. So I think, you know, if, if you can tap into that with the right kind of experiences, then you know, we should be able to reframe the conversation to be a bit more positive, like you say, let's hopeful that we can go forward. This is fascinating by the way, and I wonder what, what are some of the other trends? You know, you talked about the negativity in the industry. You talked about the part participant experience. And, you know, potentially people waking up to that, recognizing the value of it. What are some of the other trends that you see? I mean, you know, I would say you are one of the, inca is one of the pioneers or Nexxt Intelligence in, in, you know, AI adoption for research, the conversational AI and, you know, and, and redefining that. What are, what are some of the other trends you're seeing at the moment?

Kathy Cheng 14:19

I think, I think we adopted AI by accident, to be honest, because we started the business. That was 10 years ago. That was a long, very long time ago. Sometimes looking at the new companies, I feel like, are we too old to still be around? But but we, when, when I started think about what kinds of things that we could do to make the survey experience better, AI was a very, very small part because at that time there was no ai. We did try to train our own ai, but that was very. If I, if I think about the AI that we had like before generative ai, it was just so, so little ai, it was, it wasn't real ai. So, yeah, I, I feel like that's a, that's an interesting evolution. Now, most of the platforms tools, I feel like they are centered around ai. Like AI is the main thing. Our product. AI is a core capability, but I think it's the holistic experience that really makes the experience different. that makes me think about another trend. I feel like I'm, I'm sure a lot of people are talking about about it, synthetic data, synthetic participants. I'm sure there's a place for it. I don't know. Conceptually, I don't fully understand that. Maybe that's just me. I just don't really fully understand that. So, because to me, the conversation we just had about people really have things to share, I think I am hopelessly hopeful about humanity. I think that's, that's us human. That's we, it's not about the few cents that we offer people. It really is about them having things to share. So if that is the case now synthetic data is getting popular. I think it's because we're not seeing reliable quant survey data. We're not seeing people participating in surveys because of all that. Why don't we just rely on the synthetic data? It's probably the same, unreliable, but then it's a lot faster, it's a lot cheaper. So I can see that argument, but I feel very sad about it. I feel like we're, we're giving up on us, we're giving up on. The belief that we're, as humans, we have things to share. We have our opinions, we have, want to help people, help companies build better products. to me, that's a, that's a trend that I, I, I'm, I'm watching where it will go. I, I definitely do believe there is a place for it in a lot of the use cases, but as a whole to replace surveys. I would think it's, it would be very unfortunate if we actually would allow that to happen because it's not, yeah. You know what I mean? It's not about, yeah,

Mike 17:13

But as a, as a, as a compliment or as a different type of data that can help make a decision, you, you see that it does have a role alongside the real human organic input as well. Is that, is that right? Yeah. Yeah.

Kathy Cheng 17:27

But

Mike 17:27

Fair.

Kathy Cheng 17:28

replace the human input. That's

Mike 17:29

Yeah. Do you think w would you say that it's being overhyped? Would you say that the synthetic, you know, is that an example of a, of an overhyped trend or are there others that you think I just wish people would stop talking about, you know, this particular trend at the moment.

Kathy Cheng 17:49

Yeah. To me, I think so. I think it's because I do believe we humans have things to say. So to me it's it's interesting. I think it's, possibly a short term solution to low quality data and very expensive, very slow, like all that kind of things. But yeah, to me it's overhyped. I, I think maybe on the other side automated insights to me is also overhyped. like one click and within seconds you have all your reports and all that. It sounds amazing, but at the same time, again, I think as humans. We have our own judgment. We have we have things to say. As research professionals, we have our vision, we have our strategies, we have things to share. So to me the whole narrative about a single click that you have, everything that's, again, counterintuitive to me. I, again, I, I know there is a role it can play. It helps us. Maybe write reports faster, and then we can see things a lot faster so that we can save our time to do the real strategic piece of So that's probably just language that is maybe just for marketing. Like we, we talk about things like that. The reality is never going to be like that, but I, but I, I do feel, maybe if I could generalize technologies that are built to replace human articulation. I think they are probably overhyped.

Mike 19:15

Okay. And that you mean the, the sort of the process of the, for analysis and reporting or for the synthetic feedback, those are the kind of the things that you're, you're saying human articulation replacements, is that right? Yeah. I think it's interesting the growth in, and I'm gonna get the language wrong here, but the sort of friction maxing movement of people trying to slow things down or make things more challenging in order to you know, go through that experience and the learnings that you get. And I think there's probably something maybe in. The process of working through analysis or output of being close to it and having to do some of that sweat that maybe leads you to places that the kind of push button automated thing, you know, will never expose. And, you know, who knows? Maybe maybe the circle. You know, it, it, it, it. The wheel turns and people come to appreciate that actually, you know, you do sacrifice things with that highly frictionless you know, input output approach, but who knows?

Kathy Cheng 20:17

think that's our human nature. We saw that in history. If I remember correctly, was it General Mills? They had this like what's that called? That baking mix that you wouldn't need to do anything

Mike 20:28

Yes. Aunt, not Aunt Bessie. That's a, that's a British thing, but I do know what you mean with the and people hated it because there wasn't enough effort to, you know, to make the cake. Yeah.

Kathy Cheng 20:37

big anything. Yeah, but I think it's the same thing. I mean, it's gonna be corrected by human nature. We are not like that. We like to be

Mike 20:44

Yeah,

Kathy Cheng 20:45

We like to express ourselves. We are creative. We want to be part of the process. If it is over automated, I think we're gonna correct that.

Mike 20:54

yeah, yeah. The IKEA effect as well, isn't it? You know, having actually put that effort in to assemble something, you know, you feel a sense of, of ownership and and pride. Okay.

Kathy Cheng 21:03

Yeah.

Mike 21:05

What else is in the industry that I guess, you know, is there a sacred cow in the industry that you would like to slaughter? I hope this isn't offensive language to anybody, but you know, and you understand where I'm going with the metaphor.

Kathy Cheng 21:16

yeah. I mean, to me it's possibly very personal. I think it has to be traditional surveys because I think if traditional surveys are not gonna change. We will find surveys or surveys dying soon. It's not gonna be down the road 20 years or whatever. It's, it's. Survey. Survey will just not be relevant anymore. This has already happened. That's why we have synthetic data, just because surveys, a lot of people don't trust the, the data that we can collect from survey. People are not opting to complete the surveys. So this is already happening, but I don't believe, problem is the surveys. The problem is how we deliver the surveys. So that's why I think if we could improve traditional surveys. So if we could just even give up traditional surveys, provide people with a very different experience, do surveys, better, do surveys in a way that people want to participate, do surveys in a way that the insights users can rely on the surveys. They play a role, they play a very, very important role in decision making. So yeah, that would be. My choice,

Mike 22:29

Yeah. Okay. So that, that kind of you know, box interface grid intense experience that, that people have with surveys, which, you know, it's funny, I'm writing A guide for corporate researchers right now to survey research and going back through the history of, of surveys, and you realize so much of the, that design that you're describing actually has its roots in the 1930s and forties because of, you know, as a function of old technology. Questionnaires had to be designed in a particular way, and we replicated them when we moved online. And you're right, you know, the, the experience is definitely up for renewal and reinvigoration. So I would tend to agree with you on that as well. So if we look forward the next two or three years, I was a conference in the uk. The, the UK head of Ipsos was talking about people's. Simultaneous excitement and anxieties about ai. I think she told it. She called it the wonder and the worry of, of ai. And it seems from where I'm sitting that a lot of people have got this kind of split, you know, optimism, fear thing going on. How do you see it? So the next, next two or three years, obviously AI is a big component of that, there's lots of disruption, but where do you think the insights industry will be in a couple of years time?

Kathy Cheng 23:45

Yeah, that's a big question. I think I tend to be more on the optimistic side. In general, I find AI is very helpful. I don't know. I, I feel like I cannot live without AI already. It's just so embedded in everything I do. I think what's gonna happen next probably. The big changes probably will not be on the technology, possibly not on methodology. I think there's probably this much that we can change, and then there is a lot of technology built already using ai. be a. More polished, more automated, cheaper, like all that possibly, and better user experience for the actual users. But I can't imagine, um, fundamental changes to come in the next 10, 20 years maybe. But I think think what probably we will experience as an industry is on the human side. like we. Started our career as a qualitative researcher, quantitative researcher. Most of us have, have been operating such a way we work in one of the methodologies. I think that's gonna change. I think, um, again, talking about ikea I remember one time someone said they developed this new concept you build so that your home can be flexible because you now can. Assemble reassemble based on your needs and move things around. But it's the human adopting the concept that make it work. For people who don't like to do that, they just put a piece of desk always there. They don't want to redo anything. That's just not gonna happen. So I think what we are seeing, what's exciting about industry is with technology we are now able to kind of blur qual quant. It's very hard to really even give a name for these things. To really utilize the new technology, it's us researchers. As of now, my observation is we don't, as a, as a whole, as an industry, we don't necessarily have the mindset, I suppose, and also the the skills Both sides yet. And then if that continues, I don't see these technology that you, the, the, the power of these technology can be maximized. So I would think in the next little while, what naturally will happen is more training, more in practice as well, more just. of Qual and qu if you think about, like we started as a using a conversation in the surveys world, to really utilize inca really well, it requires researchers who can and who want to add projectives know how to use projectives, how to even turn a, like a scale into a projective, because to me. Keep a, like, scale is useless to me just as is. It's, but it's a nice projective. You use it, you kind of give people a little They select the number, but the number doesn't matter. It's what they say after. So it,

Mike 26:50

Yep.

Kathy Cheng 26:50

requires that kind of mindset. It, it, it does require you want, do you want to use pictures? Do you want to use metaphor elicitation? You want? So if we don't have that kind of desire and or knowledge. In those kind of things, we would not be able to use that platform. That's. Like, but it probably will still be used as a, as a quant platform. Then the other side for us, that's an interesting change as well. Even though we started as a conversational survey platform more and more clients are using inca Qual scale because it's really hard to say what is what. But then it's the same thing for qual at scale. Now it is scaled. for us quallies, we really focus on the questions, we don't necessarily think about the logic. That's not our. Intuitively, we don't, we don't, we don't think about that first. But then now that we can scale those conversations we can some concepts, multiple concepts with hundreds of people. logic is you need to build something. You probably, you need to start to think about the loop questions in the in quantum surveys. But again, if we don't know that, if we don't know how to even interpret the looped question data, it would be very hard for us to maximize the, the power of these platforms. So I think what going to happen next is probably less on the technology side, but as a whole industry, how we're gonna rethink researchers our roles, what we need to learn, and how we can, use different perspectives to do the same work that we've been doing.

Mike 28:25

Yep. Yeah. You know, it's really interesting because the paradigm that a lot of people talk about is this qual quant divide, which is beginning to merge. But I think what you're describing is slightly more nuanced than that, which is actually qual and quant imply. Legacy data collection methods and the skills that were designed around them. Really, it's a question of being able to blend the intuitive, empathetic inquiry, that sort of depth that drives qualitative and the more structured thinking, like you say, more of the engineering brain that goes around, you know, looping questions and data structures. And to connect those two things. Actually, the way the industry trains people will have to change quite significantly because it's gonna be much more about the tools enabling much more automation for what we've traditionally put people into buckets for, you know, you are a moderator, you are a survey data processor, but after this is more about. How do we enable people to use those tools and blend those two instincts capabilities, or, or grow them? Both. I, I, I don't wanna put words in your mouth, but I'm, I'm paraphrasing. I think how I understood what you were describing is that, is that right?

Kathy Cheng 29:39

That's precisely what I'm thinking.

Mike 29:41

Yeah. Yeah.

Kathy Cheng 29:42

yeah, that, for example, quality scale for a very long time. I resisted that term because I'm such a quality, I just don't think Qual can be scaled. I think but. It's, yeah, it's probably just me overthinking the term. it really implies is we, we can forget about the term altogether. What it really implies is now you can have consumer led conversations at scale. I think that's, that's the real change. So what that means is for if you add conversations in surveys. If you are still a only quantitative researcher, you would think, okay, I'll use all the data and I'll add, I'll add the verbatims to add colors to my report to add a little bit of context. And I go, that's, that's probably what a typical quantitative researcher would do with conversational data. But I think the real opportunity is beyond that, is if you start to think, no, the real shift. It's not just to add verbatims, it's now I can listen to these people, thousands of people actively. So it changes the dynamic. It's no longer just the adding verbatims, but to use their verbatims as consumer led insight to call them into it becomes exploratory. So, so that's a difference. So that requires a mindset change of the researchers. It's, yeah, it's beyond what the tool can offer, but it's how we want to use the tools.

Mike 31:09

Yeah. Okay. Well, I feel, you know, you've you've, you've sort of reset the pessimism in the industry for some, you know, energetic enthusiasm for where we could go with all of this. We could carry on all day, but I'd, I'd love to just wrap up with a couple of, I guess perspectives from you on building the business. You know, you've got obviously 10 years in business and you said, you know, you feel like a, a, you've been around for a long time, or you feel old in this context. A couple of weeks ago. I interviewed the new CEO for discuss the expanded business and Vox Co part of that has more than a 50 year history. You probably know, you know, it's a, it's a Canadian, very proud Canadian research technology business, so founded in the late 1970s, and I saw this week that Infotools have just revamped their. Overall platform. It's you know, data analytics and, and modeling solution with lots of generative AI and co-pilots. And originally launched their product in 1980. You know, so we're in good company if we're starting to feel like we've been around for a while, but it's good anyway. Tell me about some of the lessons. I guess maybe what, what, what do you feel like you've learned as you've built Nexxt Intelligence over the last 10 years?

Kathy Cheng 32:19

I think I learned a lot. Really. It's quite a journey. If I could just name one thing I think I. I, I would say when I started the business, it was almost by accident. I just had this little idea. I just thought it would be fun to try it to build something. And then once it was built, there was a, a real project at that time as well, once the project was delivered. And then I happened to talk to an industry friend and then she said, oh, this, this could be useful. All market research. Are you ready? Like, it just happened like that. So I didn't really plan to build a business. So then I realized it's actually a real business. Now you have to. Have a roadmap, you have to have more people, you have to do all that. So to me it's it's quite a journey. I, I suppose I wasn't fully prepared. I suppose most people are probably not, never gonna be fully prepared. So what I was trying, so one thing that I, I would say that keeps, bugging me, I suppose, is I, I, I think I consider myself, consider myself pretty introverted. I suppose. a lot of quallies are fairly introverted, even though we are supposed to be talking to a lot of people, I. So I wish that there was a, like a introvert playbook for running a business. I really, I really think that could be very helpful because I, when I look at LinkedIn for example, a lot of things that people do quite naturally, I feel like I just can't, do, blame myself for not doing a. Things, and then it is a business. You really do need to go out there and network and like all that kind of thing. So, so I, I do wish that there could be something that help people even, even if they are not built to be an entrepreneur. But one specific lesson, I don't want to be pessimistic as if that's was but one specific lesson and it's very concrete, was even for someone like myself one day someone said to me. Always go to a meeting with an ask. That was quite enlightening for me. That became very concrete. That became like, then I started to look at all these things with a very purpose. I started to realize a lot of things that if I don't think through the, the, the ask that that I have before I talk to someone or go to a meeting or something, and then I have like 10 different asks in my mind. me and then I wouldn't say any of that. And then I feel very stressed and I feel like any of them would be a huge favor that I would ask. It's terrible that I would even ask any of that. then, yeah, someone just said to me, always go to a meeting with an ask and people if you ask, people will help you. That was so true. That really changed my perspective and a lot of my actual like day to day. So I hope that's,

Mike 34:56

it's wonderful advice and I think I'm gonna take that on board myself. And but I would say the LinkedIn you know, feeling that everybody else does things so much more naturally, so much more confidently and you know in extrovert fashion, you know, it is really like looking at Instagram and thinking everybody's so much more attractive and, better dressed and better made up than than I could ever be. So you know, there is a little bit of a self-promotion wrapped around that, that we should all be a bit skeptical of. But I love that. I think that's a fantastic point on which to finish. Always go with an ask. Don't be afraid to have a clear request of people you know when you're meeting.'cause you know, you're right. Generally, and especially in this industry, people are fairly inclined to help one another. It's, you know, it's not a cutthroat environment that you might find in other spaces. So this has been great. I think we, you know, we've covered a lot of ground. We've covered the need to reinvent the participant experience with better you know, combine surveys with much more you know, exploratory, interactive, conversational components. We've talked about some of the opportunities in the industry, the big trends, some of the things that may be slightly overhyped, that how things might develop over the next few years, and I love that. Particular piece of advice. You know, the, obviously we're still looking for the introvert's handbook, but always go to a meeting with an ask to see if you can. Get that useful support from people. So, Kathy, it's been a wonderful conversation. Thank you very much for taking the time to, to speak to us and share your insights with our audience. And I hope that you've you've got something from this as well. It's been wonderful. So everybody watching or listening, we will be back. We have many more episodes scheduled with founders and leaders of both niche. Technology, perms and huge giants of this industry, they'll be coming out over the next few months. I do hope you'll be back to listen or watch, but Kathy, thanks once again for taking the time to be with us and enjoy the rest of your day.