Episode 3: Navigating the Shifting Landscape of Qualitative Research with Karen O'Neill
How has the role of qualitative research evolved from being an order taker to a strategic thought leader? Join Cynthia Harris as she sits down with Karen O'Neill, Senior Vice President at Ipsos, to explore the dynamic changes in qualitative research. Karen reflects on the journey from being an order taker to becoming a strategic thought leader in the industry. They discuss the challenges and opportunities brought by new technologies like Gen AI and how the human element remains indispensable. If you're curious about the future of research and its role in shaping business strategies, this episode is a must-listen.
Your peek behind the curtain of the insights industry starts here. Enjoy this episode of Research Revealed!
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Karin is a Senior Vice President in Ipsos’ Qualitative service line, where she is responsible for innovative techniques with a special focus on the balance of Generative AI and Human Insight. Prior to joining Ipsos, Karin worked for several years on the client side of market research in the CPG industry.
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Cynthia Harris 1:02
Awesome. Thank you so much, Vic. Well, hi, Karen. I'm super excited to have this conversation with you, so thank you for taking the time to come on Research Revealed.
Karen O'Neill 1:11
Thank you for having me. Cynthia, it is a delight to be with you. I always say that any day I have a conversation with Cynthia is a good day. So happy to be here.
Cynthia Harris 1:19
That means a lot coming from you. Well, I'm particularly excited because you're one of my favorite researchers in the world for many reasons, but one of my. We had the chance to work together at P and G years ago. It feels like just yesterday, but it was quite some time ago now, and I learned so much from you working with you there, and just feel very fortunate that we've maintained a friendship ever since. So excited for this discussion.
Karen O'Neill 1:42
As do I. Cynthia, you're one of my very favorite colleagues to work with, and I really enjoyed seeing your continued success.
Cynthia Harris 1:49
I appreciate that. Likewise.
Speaker 1 1:52
One sec, you guys. Sorry to cut you off. Cynthia, if you could speak a little bit more into the mic.
Karen O'Neill 1:56
Your.
Speaker 1 1:56
Your. Your audio is kind of low.
Cynthia Harris 1:58
Okay.
Karen O'Neill 1:59
Yeah, it's a little quiet.
Cynthia Harris 2:01
Okay, let me turn up that.
Speaker 1 2:02
Yes, that was better. Yeah. So maybe if you, like, hold it like.
Cynthia Harris 2:07
I will.
Speaker 1 2:08
Yeah.
Karen O'Neill 2:08
All right. Okay.
Cynthia Harris 2:09
Okay. Awesome. So, Karen, what I really want to talk to you about is some of what you think about what's going on in the industry today. But I wanted to hear a little bit about the evolution that you've seen in the industry. You've been in the industry for quite some time now, and you've seen a lot of changes. And if you don't mind just kind of talking us through the changes that you've seen and how you feel about where we are as an industry.
Karen O'Neill 2:33
Gosh, that's a great question. And when you say a long time, that makes me feel rather senior in multiple ways. But you're right, the industry has changed a lot. I'd say, you know, one evolution we often talk about is you and I both come from the client side and on the client side, I'd say that market research kind of transitioned from being a little bit more of an order taker. Run this test for me. To having more of a seat at the table and then of course influencing business decisions from the supplier side. I think there's been a couple of big disruptions. I think one has been the advent of DIY platforms. And so that has enabled a lot of researchers to kind of get in hands on and do their own research and then has caused an adjustment, I would say the supplier side of market research in terms of what they contribute. And then of course now Gen AI is the latest big disruption. And I think we can learn a lot from the supplier side from that previous disruption. What we learned there we can apply to Gen AI. And I always kind of go back to some advice from one of my managers at P and G, which we probably recited back then together and she would always say to me, think about what you can uniquely contribute, you know, when you're in this meeting, think about what you can uniquely contribute. So I kind of keep that in my head, you know, now that I'm on the supplier side, what can we as research suppliers uniquely contribute in the environment that we're in now? So I think it's an exciting time in the research industry now. I think there's a lot of opportunity both to change the way that we do things as well as take the things that we've always done and kind of elevate them and do them better. So, so happy to dive into any of that.
Cynthia Harris 4:12
I love that. No, I love how you said we're moving from being order takers, having a seat at the table and being strategic thought leaders is how I kind of heard that comment. And I think that is so true. We are lucky, both of us are lucky that we get to work with lots of different companies and brands and see kind of how Consumer Insights works within these different industries and within these different companies. And it is astonishing to see the ones that have a seat at the table versus the ones that are just kind of checking a box. It's, it's just Inspiring to see that so many are now strategic thought leaders. So exciting to hear you say that too. So when it comes to innovation, Karen, I would love to understand a little bit more about where do you feel like we have gaps as an industry from an innovation standpoint. Where do you feel like we've clearly come a long way from a technology standpoint, but where are the gaps that still exist?
Karen O'Neill 5:02
That's a great question too, when I think about the innovation and where we are as an industry. Let me start over on that one. Sorry, it wasn't exactly what I thought you were going to ask. So gaps that still exist in our industry, I think it's. We're all sort of actively working to fill them. A lot of it is just keeping up, right. Keeping up with this disruption in the industry, keeping up with the technology and trying to kind of lead the way. So if I think about again, on the client side, you know, clients are busier than ever. So I think what is continually a challenge is getting them the insight they need sort of in their hand when they're in the meeting and need it to influence, which is often quickly, not requiring a lot of time on their part. I think that's something that we can continue to do better as an industry. When it comes to kind of methods, innovation and thinking about things like AI Gen AI, I think we are all going very quickly in that direction, which is great, but we also can't lose sight of what we have always done as an industry and how we can continue to do that better. So that's one thing is I'm thinking about our innovation. At ipsos, we talk about hi, human intelligence or human insight as well as AI. And I have innovation streams going on, both of them because I think that's one thing we have to be important, have to think about, that we don't lose sight of is how can we continue to elevate our craft and do things that Gen AI cannot do at the same time that we're embracing it and incorporating it into our work?
Cynthia Harris 6:39
Yeah, that's. It's great. It's interesting because just in the past year and a half, I feel like we've heard people go from being scared about AI and its impact on our industry to people really starting to embrace it and to be excited about the possibilities. And from your perspective, Karen, what do you feel like the possibilities are? And even if you could talk to synthetic data and synthetic users, what are your thoughts on that as well?
Karen O'Neill 7:04
Yeah, I feel like I could talk about this topic all day. So just Stop me when you need to. So possibilities, I think, are really exciting. And the way to embrace it is to think about a human AI partnership. So again, I think back to that P and G manager who said, what do you uniquely contribute? I think we have to think about what we uniquely contribute as humans and then where AI can help us and where AI may even in some cases be able to do better than humans. And then kind of give. Give everyone the best role for their capabilities, the human and the AI, and then continue to keep up with that as the technology evolves, because it will continue to evolve. So if I think about what we as humans are good at, their social and emotional skills, that AI does not necessarily have, we continue to try to build things like that into it. But there's part of what makes us human that hopefully will always continue to make us human. So as a human researcher, I would encourage people continue to sharpen your skills in the those areas. You know, we're looking at things like culture and human motivations kind of on that. That human side of things. And then on the AI side of things, AI can give us a lot of efficiency, it can give us scale, and in some cases, I'd say it can even give us inspiration. So synthetic data. So love to talk about that. And I'll tell you kind of the latest from what we have learned in our research on research. But I'll tell you, I have another paper in my inbox that is even newer than that, so it's just changing by the minute. But I'll tell you the latest as of, like, right before I got that email, because I'm still reading it. So our research on. Research on synthetic. We did a really cool experiment. My colleagues in Japan did it. They looked at, I think it's about 150 respondents in a community and created an AI twin of each one of them. So think about, like, in the community, we would have real Cynthia and then we would have AI Cynthia and then do.
Cynthia Harris 9:04
Yeah, I'm like, let's call her Beyonce Cynthia.
Karen O'Neill 9:06
Okay. So then we do research with both of them and then compare the results. So that's kind of how they did this experiment. And that's one thing that we have been, I think, done a good job on is not just leapt into AI kind of blindly doing. We're moving very fast, but doing research and research all along the way. So we can say we are doing this because, you know, we understand kind of why we're taking the approach with each element. Hi. And AI. So what we found in this Synthetic data experiment, we looked at three different areas. The first one was foundational research, I would call it fundamental type of research. And what it found there is that synthetic respondents could come up with themes. So you know, AI Synthia could come up with some themes of what was important in this particular category or space, but may not have all the personal stories and color and richness and nuance to how real Cynthia would have articulated that. And if you think of it that way, you know, until we're in some sort of a sci fi world where you can sort of suck all the contents of your brain into an AI model, that's probably going to be kind of impossible to do. So when it comes to foundational research, that's where I feel like you really still do best with real people talking to real people in real life. So that's the first one is foundational research. The second one is ideation. And when it came to ideation, the AI twins did a pretty good job. They came up with a lot of ideas and varied ideas. And if you think of how LLMs work, you know, they're good at sort of putting different things together, right? So it makes sense that they would be able to come up with these ideas. However, where ideas coming out of the AI twins fell short was they tended to skew functional less and again, makes sense, right? They don't have the human EQ or the skills in terms of contributing the social and emotional context. So when I think about ideation, that's where I really feel like it should be a partnership with the human and the AI working together. Because the AI can get you started. It can really give you a huge breadth of ideas and maybe some that you wouldn't have put together yourself, which are great, but again, those ideas are going to skew a little more functional. So then bring in your human team to add to those ideas, build on them, create their own ideas that are coming from maybe more of a social and emotional place, put it together. And that's when I feel like you kind of have the best of both worlds. That's the second area, which is ideation. The third area that we looked at is evaluation of stimulus. And that's where I don't feel like we can rely on the synthetic respondents entirely. And so we did this experiment in qual, and there also was one in some quantitative research as well that came up with kind of the same conclusion. So if you think again about that idea that the synthetic respondent just doesn't know everything that's in your brain and all the human experiences you've had. So one example I would give is like, you and I used to work in shampoo for a long time. And so let's say we're looking at a new shampoo brand and someone's looking at the shampoo bottle and it's a particular shade of green. Well, we don't know all the associations that that individual has had in their own personal history and their life with that shade of green. Maybe the couch in their childhood living room was that shade of green. And one day they had the flu and they were laying on that couch. And there's just a subconscious negative association with that shade of green that is not going to go into how a synthetic respondent is going to evaluate that shade of green in that product, if that makes sense. So it's always important to check with real human respondents to some extent. I know our quantitative team, when they did a study on this, they actually came up with a number where they said, you need to have this many human respondents in your samples. So I think it's potentially okay to use a mixture. But I wouldn't rely just on the synthetic there. That's where I would use a human respondent. So I guess all of this sort of in summary is saying, you know, there's a lot of opportunity for both human respondents and synthetic respondents. We can also talk about the impact on moderation, too, is another. Another kind of topic there. But there's. There's a lot of room right now for both to play. And that's where I feel like it's very exciting. It is changing daily. Like I said. I just saw another paper in my inbox that I've got to read. So it's changing daily. And I think for those of us that are working in innovation, it's a really exciting time to try to kind of keep up with it and adjust our craft as we go.
Cynthia Harris 13:30
I love it. Thoughtful response, just as I would expect from you because you're always so well articulate it and just do a great job of explaining things. But when you think about what's happening from a synthetic or AI perspective, how should people go about educating themselves? What would you recommend in terms of how we can all start to stay up to speed on what's happening? I mean, at Ipsos, you guys clearly do a great job with research on research and have the resources to do that. But for other researchers out there who perhaps aren't as large as Ipsos, how can they stay abreast of what's happening?
Karen O'Neill 14:05
Yeah, so we actually Publish all the research on research that we do. So anyone is welcome to read it and it's on our, our website. So the qualitative research that we do is all entitled Conversations with AI. And I think we've published six papers now, Conversations AI 1, 2, 3, 4, 5, 6, etc. So I usually honestly Google the topic and then the ipsos, and then sometimes I say Conversations with AI just to see what comes up, just to easily find those papers. So they are all online for anyone to read. So we've got papers on analysis, like qualitative analysis, side by side ideation, knowledge curation, the digital AI twin experiment that I just told you about, AI moderation. And it sounds like there might be another one coming out too. So we do publish them all. So I would encourage folks, if there's a supplier that you trust or from academia. So we are partnering with academia, Ipsos is partnering with Stanford, my alma mater. I'm not personally involved in it, but on some of this synthetic data work and that also will be published. I know some of our clients are also publishing work. So I believe P and G actually just published a paper with, I think it was with Harvard on working with AI as a tool. So I would, you know, kind of like, I think about how kids are educated in school to kind of check their sources today, I would kind of apply that same rubric to like how you're looking at what's out there. So who did this experiment? How did they do it? Does it make sense to me? Do I understand where it came from? Is it recent? You know, I would just sort of look through all those filters and if, if someone says on the client side and someone's coming to you and say, this is what we learned, I would just ask them questions. How did they do the experiment? How did they learn? And you know, this is a time when things are changing, so you are going to have conflicting findings out there. So I have seen some of that and again, I just try to dig in and see, okay, is it really conflicting? Did they use a different model? How did they do it? What did they learn? Does it make sense with everything else I know, I mean, that was another thing I remember like when you and I worked in innovation at P and G and we used to talk about, you know, you need to look at more than just one test, you need to look at sort of the whole body of knowledge that you have on this topic. So that's another way I would think about it is if you have one study or one recommendation that Seems to differ from everything else. I would try to look at the whole body of knowledge and see is it hanging together and then if this one's different, is there a reason for that?
Cynthia Harris 16:48
So yeah, I love that advice of looking at a full body because, you know, lately I feel like I've been saying this ad nauseam, but data is just becoming very ubiquitous. It's very easy to get to a data point. Right. But the meaning behind the data is harder to come by because people just want to go by headlines, it seems sometimes and don't. We don't always want to do the work to look at the full body of evidence. So I appreciate that encouragement. So you talked a little bit about AI moderation and I'd love to talk a little bit more about your knowledge on the topic of AI moderation. But then also what skills, skills do people need to develop to continue to be the right human for the job of being a solid researcher, a solid consultant, somebody who can sit at the table credibly? What are the skills that need to be developed?
Karen O'Neill 17:37
Yes, and I think actually the way you just ended that someone who can sit at the table credibly is actually a really great place to start. And again I go back to that boss in my head years ago saying, what do you uniquely contribute? So the way I think about the world of AI and research today is. Sorry, I lost my train of thought. Okay. So when I think about like the researcher of the future and how they should equip themselves, and I think it's actually quite similar for many other occupations. You know, talking to teenagers today, this is something a lot of teenagers are thinking about or young adults who are in college, what job should I go into that is going to be future proof in the world of AI? So that's where I start to think about, you know, what can AI not do? And then how can I use AI as a tool? That's how what I would encourage a researcher to think about. So, you know, for example, one young person I was talking about, this is a little bit of a tangent, but was thinking about going into physical therapy and I was like, okay, that's something that I don't think AI is going to be able to do. The hands on, in person nature of anytime very soon, will there be aspects of it that could be taken by AI? Sure. But in person, in person, human skills are going to be probably one of the hardest things for AI to replace. So if I think, take that back to our context of market research. So if, if I were a moderator Today I would want to really hone those human skills. I would be thinking about in person research. I'd be thinking about things like ethnography, culture, empathy, the social and emotional skills that go into being a great moderator. And I would really want to beef up that side of things. At the same time, I would want to learn how to use AI as a tool. Now, the young people coming out of school have already started figuring out in academia there's some guardrails that
are put around using AI, but most of them have already sort of figured out there's still ways I can use it and I'm going to use it as a tool. I would embrace that kind of mindset for all of us. So yeah, so I think about what can AI not do and then how can I embrace it as a tool as it continues to evolve and kind of learn from it? So when it comes to AI moderation, we did do a side by side experiment, if so cited on AI moderation. And I'd say the overall conclusion, and again, this is something that's going to continue to evolve and develop, develop. And I knew I need to read the latest paper in my inbox about this as well. But I would say AI moderation kind of is like a novice moderator in a way, in the sense that it tends to follow the guide and not the gut. So if you think about those human skills that you as a moderator would use to understand what, you know, what am I getting from the person, what emotion is behind it, where might I dig for more insight? Where should I maybe back off? Because I'm realizing this isn't a fruitful conversation and I need to pivot. There's a lot of human, social and emotional skill and intuition that goes into that. So that's something that I think AI moderation is probably not quite there yet and it's going to continue to improve. That said, that doesn't mean that there's not a place for it. So if you think about adding, you know, sometimes people are doing quant research and they want to add a little bit of sort of qualitative feeling to it, a little bit of color and context, but it's really not full qualitative research. So I think one of my colleagues kind of coined the phrase conversational quant is not a qualitative conversation. That's true. But if you want a little conversational quant, I think that's a great application of AI moderation. Another application might be something like, let's say you're studying a health condition and Somebody struggles with a condition that wakes them up in the middle of the night. We had storms here last night. Maybe you were up in the middle of the night, but usually you're probably not. And you're not going to want to hop on and do an interview with them in the middle of the night. So it's always on. Kind of quality is a great application for AI moderation as well. So I'd say that's kind of where I feel like it is right now, is kind of, you know, like a novice, not necessarily going to give you the depth that a really skilled moderator, human moderator will give you. It will probably continue to improve and we'll all keep up on that. But then as a human moderator, I think that there are certain human skills that are going to be very difficult to replace. And that's what I would focus on as a human moderator as well as using AI as a tool. And AI as a tool doesn't necessarily only mean AI moderation. So think about, you know, you as a moderator, you. Let's say you're doing a project and it's in like six countries and you've got all this richness to analyze. AI can help you kind of dig through that. Let's say you're doing a project maybe even before you start the moderation and the discussion guide, and you want to understand kind of everything that's known about this topic. And you've got 64 different documents to go through. Well, as a human, that's going to take you a really long time to read 64 documents. So how might you use AI to help you sort of dig through that more quickly and get you going faster? I can give you a personal example. We have this human motivations model, Syncidium, and we've developed a prompt for that. And I wanted to create a fun quiz based on the different. Because you can kind of take this quiz or in Syncidium, you basically have like a color that you tend to identify with in this model. So I thought, wouldn't it be fun if we had a little quiz for the holidays and people could, you know, almost like a buzzfeed quiz or like in the olden days when you have a quiz in a magazine and it would say, you know, for your color, here's how you might want to celebrate the holidays or something like that. That's something. It probably would have taken me like a half day to create something like that. Two minutes. Two minutes using AI.
Cynthia Harris 24:01
Amazing.
Karen O'Neill 24:01
So I'd say, like, as a moderator, when you think about using it as A tool. There's so many different ways to use it as a tool, not just moderation.
Cynthia Harris 24:10
Beautiful. Now I want to make a quiz on something. I don't know what that sounds like so much. Yeah, I don't know what I was watching recently, but somebody was very into a crossword puzzle and it actually made me think of my dad. My dad always had a crossword puzzle in his hand as I was a kid and it just made me want to kind of get into crossword puzzles again. So I think with this affirmation of a quiz and seeing that crossword puzzle, I might have a new hobby coming up.
Karen O'Neill 24:39
You know those games applications like we're all doing the wordle? They're doing really well.
Cynthia Harris 24:45
I actually think, Karen, I think having time for downtime and hobbies has helped me be a better researcher. And I'm curious if you think that that is true for you as well. When you think about what you do outside of work, do you feel like any of those activities make you better at your job?
Karen O'Neill 25:02
Oh, goodness, that's going to be embarrassing because you're going to make me admit to my embarrassing hobbies. I'd say one thing outside of work that makes me better at my job, honestly, is probably parenting. You have to be, you know, you have to get more decisive and know when to be directive and when to kind of coach someone. There's a lot you learn from being a parent that I think has helped me be a better employee and manager and everything. El in terms of my hobbies, one thing this is embarrassing. Cynthia. I like to cross stitch. So I've been talking to some of the and it reminds me of my grandma. It's funny you said crosswords remind you of your dad. Cross stitching reminds me of my grandma. And my daughter took it up, I don't know, a couple years ago and I decided to take it up again with her. I hadn't done it since I was in high school and the Gen Z employees I work with now tell me that this is like cottage core. So it's kind of a trend O I love it. Just pretend like it's fashionable. But it does help me sort of disconnect and help my brain like incubate, you know, because when you're just sitting there looking at the details. So number one, it's probably helped me become more detail oriented because as you may recall, that was not my strength. But secondly, and by the way, I always hear my grandma's voice when I turn it over and I look at the back of the Cross stitching. Because the first time I made her something in high school and I gave it to her, she was the nicest person. But she turned it over and she said, well, I guess no one's going to look at the back. So anyway, I've tried to learn back neater. So I've become more detail oriented, I would say, through that as well as I think having a hobby like that where you can really disconnect and not think about all the millions of things going on in your personal life and work, I think does allow ideas to kind of incubate in your brain and, you know, you come up with a better idea afterwards sometimes.
Cynthia Harris 26:58
I love it. I have to tell you, Karen, I have been being more deliberate about the human moments in my life, and I think it is because we're so inundated with technology now that, you know, I've been playing tennis for the past year and I do not miss a clinic if I'm in Columbus, Ohio, I'm going to go to clinic on Sunday morning. And I think in some ways it helps me continue to remain human in a world where we're on zoom half of our lives, it feels like, you know, I think it's so important to cross stitch and to play crossword puzzles and to play tennis on the weekends.
Karen O'Neill 27:30
So, yes, anything that disconnects you from technology for a minute, I think is a good thing. You know, much as I love technology and I work in innovation, you know, you think about how we as humans evolved and it wasn't looking at a screen every time we get bored. So there's something to be said for not being on the device all the time. So.
Cynthia Harris 27:51
So true. I had a chance to go to Second City last night in Chicago, the improv. Have you ever been to the improv place, Second City?
Karen O'Neill 27:59
I've not been to Second City, but I have had some exposure to improv. Now, did they. Did you have to participate?
Cynthia Harris 28:05
Oh, no. I made sure I was on the end and kind of tucked away so that I'm like, I'm making no eye contact. I do not want to be on stage at all. And so, yeah, they were.
Karen O'Neill 28:15
We just did improv at a meeting and I'll tell you about that too. But anyway, go on.
Cynthia Harris 28:19
I love it. It made me think of pg, had a training on improv years ago, and that was such a transformative training for me. Just thinking about how to keep a conversation going and keeping everybody involved in the conversation. It was really powerful. And who knows, maybe I'll put that on my Hobby list as well. Getting back into improv, because I'll tell.
Karen O'Neill 28:40
You, it's not going on my hobby list. But we just did an improv training. It was really good. We had this meeting out in Vancouver and we went to whatever their equivalent improv business, improv training place was in. One of the exercises I liked so much, I actually used it with my daughter when she was getting ready for a job interview, was that you start talking about something you need to talk about, like a presentation or a pitch or whatever it is, and then the other person throws in an unrelated word and you have to work that word in to what you're doing and keep going. And they just keep throwing these, you know, squirrel, birdhouse. And you just have to like make it work. And I thought it was a really great exercise. So like you said, I think there's a lot to be learned from improv, but it's not my natural tendency.
Cynthia Harris 29:29
I love it and I love the idea of listening before you respond with improv. But anyways, we can talk about improv for an hour, I'm sure. All right, so I guess my last few questions as it pertains to the industry, Karen, are when you think about the future of research, what do you feel like people are underestimating? So when you think about what we need to make sure that we're vigilant of, what do you feel like people are not talking enough about these days?
Karen O'Neill 29:55
What are people not talking enough about? I think it depends on who you talk to. I mean, we are in a huge period of transformation right now with Gen AI. So we think a lot of people are talking about that in the implications. But as I talk to different people in the industry, it's to very differing extents. So I'd say I think it's something everybody should be thinking about. Again, I would come back to what can I as a human uniquely contribute? And then how can I use it as a tool and embrace it? So there's that. I think talent development for the future is probably what we're in the industry not talking enough about. And again, I think it goes back to those two things from what we know now and then we're just have to kind of stay with it as it changes. But for example, I was working with a new person and with the time that they joined, I said, you know what, this is great. We really need to train you on the human side of moderation and the AI side at the same time and make you into like the moderator of the future. So I think, yeah, Talent development would probably be the one. I think everyone is just trying to catch AI as it's coming and adapt quickly and it's in those on the client side. You have so many business demands. Right. And your business is changing so quickly. I think it's hard to step back and say, you know, what does the researcher at the future need to look like and how can I develop them?
Cynthia Harris 31:25
So, yeah, makes a lot of sense. All right, so we end every episode, Karen, with eight questions and they're rapid fire. There are no right or wrong answers. I just want to hear what first comes to mind. So the first question is,
what's the
Karen O'Neill
Insights.
Cynthia Harris
first word that comes to mind when you hear market research.
31:43
31:45
What's one
buzzword in research that you'd love to retire?
Karen O'Neill 31:49
Impactful. I probably shouldn't say that considering where we come from. I just don't like the full on it. I don't know.
Cynthia Harris 31:56
It's used a lot. I agree with that. Name a brand that gets consumer connection, right?
Karen O'Neill 32:02
Oh, gosh, that's hard because we work with everybody and I don't want to, like, play favorites. A brand that gets consumer connection, right? Oh, can I pass on that one? There's so many doing a great job. I'm trying to think of something I've seen recently and been like, you know, you know, we used to talk about in advertising, like, when you get that reaction of like, wow, they get me where I felt like they were doing that, but I'm just drawing a blank right now. There's so many good ones and I have a hard time picking one.
Cynthia Harris 32:33
What about a category? Is there a category or a space or a vertical that you feel is really good when it comes to consumer connection?
It's okay. If not, we can move on.
Karen O'Neill 32:47
Yeah, can I skip that one? I need to think about it. I'm sorry.
Cynthia Harris 32:51
That's okay. That's okay. Would you rather have more time or more budget for a project?
Karen O'Neill 32:58
More budget. Because I don't think it, you know, you're never going to have more time.
Cynthia Harris
Did I lose
Karen O'Neill
Okay. Yes.
Cynthia Harris
33:03
you? Hold on. I think I lost you for a second, but I'll ask again. Yep, now I can hear me.
33:11
Okay.
33:13
Would you rather have more time or more budget for a project?
Karen O'Neill 33:19
Well, more budget because you're never going to have time, so you're probably never going to get more of either one. But if I have to pick, I'll pick budget.
Cynthia Harris 33:27
Okay, fill in the blank. The future of marketing research is exciting. Name one book, podcast, or article that every marketing researcher should read.
Karen O'Neill 33:42
Book, podcast or article? Well, I should say Conversations with AI by Ipsos.
Cynthia Harris 33:51
That works. I'm definitely going to read it. What was your dream job when you were a kid?
Karen O'Neill 33:58
When I was a kid? Oh, gosh. Probably veterinarian. Until I discovered I was afraid of birds. So then I really had to pivot. I think astronaut was in there, too. My grandpa worked for NASA. Yeah, something like that.
Cynthia Harris 34:12
I didn't know that we had a common fear of birds. I'm actually quite afraid of birds.
Karen O'Neill 34:17
Terrifying. Yeah. Sudden movements. Terrifying.
Cynthia Harris 34:21
They're unpredictable. I don't like that. Final question. Do you prefer coffee or tea?
Karen O'Neill 34:27
Coffee. Definitely coffee. I like both, but definitely coffee. We grind our own beans every day, so love my coffee.
Cynthia Harris 34:36
Also, something I did not know about you, but that's amazing.
Karen O'Neill 34:39
Yeah, it's like everyone went to the Keurig and we went the other direction.
Cynthia Harris 34:42
It's more romantic that way. I do think it's more romantic that way. You know, it's just more fun when you grind your own coffee beans. And I use a French press when I'm feeling fancy.
Karen O'Neill 34:55
Okay. Yeah. I've not embraced the French press. We were actually just talking about that. Maybe we should try it. But. But no, I haven't embraced it. I'm still thinking about your other question.
Cynthia Harris 35:04
Oh, you're so funny. Let's see any. Let's see, category, brand. Maybe your favorite brand that you've ever worked on. You probably can't answer that either.
Karen O'Neill 35:16
Oh, it's question to answer. Yeah. So that's okay.
Cynthia Harris 35:22
Well, I'm so grateful for your time, Karen. And I feel so fortunate to have the relationship I have with you years later. And I'm just grateful that you came and imparted some wisdom on research revealed.
Karen O'Neill 35:34
Well, likewise, Cynthia. Thank you so much for having me. It's always a pleasure to talk to you and to learn from you. So thanks again.
Cynthia Harris 35:42
Likewise. Thanks so much, Karen. Okay, Vic, we're wrapped.
Episode created and produced by Cynthia Harris and Emily Byrski of 8:28 Insights.
Score provided by Swoope and Natalie Lauren Sims, friends of the 8:28 Insights Collective.
Co-sponsored by 8:28 Insights and Greenbook.