Jonathan Widawski [00:00:00]:
The big part of the product development process going to be mostly automated, meaning that your capacity to build fast not going to be a competitive advantaged organization anymore. When that happens, when your capacity to build fast no longer competitive advantage, then what you build becomes the competitive advantage. If everyone can build stuff, ultimately what you build is what matters for organization. And what you build is a massive part of the research journey, meaning that research all of a sudden becomes the center of gravity of company success in organization.

Erin May [00:00:31]:
Hey, this is Erin May.

Carol Guest [00:00:33]:
And this is Carol Guest.

Erin May [00:00:34]:
And this is awkward silences. Awkward Silences is brought to you by user interviews, the fastest way to recruit targeted, high quality participants for any kind of research. Hey, awkward listeners. It was awesome to have Joe on the CEO founder of Maze. I think this is the second time on the podcast. And these good buddies of ours, we always love chatting with them, but today we're talking about the future of research. Always fun to speculate, but to do it based on data, survey data of hundreds of respondents and kind of get a pulse on where people are and where we think things are going.

Carol Guest [00:01:15]:
So today we'll dig into some of the trends they found from that, including who is doing research, what they're doing research on impacts, using AI, all that good stuff. And loved in particular, hearing Joe's additional thoughts on what the individual insights mean for sort of the future research.

Erin May [00:01:29]:
Awesome. Please enjoy. Hello, everybody, and welcome back to awkward silences. Today we're here with Joe Wydo, the CEO and founder of Maze, one of our good friends in the UXR tech space. So excited to have you here. Today we're going to be talking about the future of research. So small topic, itty bitty, not too much to cover, but you've done a report on it, so you have lots of great data to share, and we're really excited to get into those details. So thanks for being with us.

Jonathan Widawski [00:02:03]:
Absolutely. I'm very happy to be here. It's exciting to be able to share some of our insights with you.

Erin May [00:02:08]:
Fantastic. We've got Carol here, too.

Carol Guest [00:02:10]:
Very excited to jump in.

Erin May [00:02:11]:
Excellent. So let's do it. So, Joe, tell us about why did you want to run this report, run this survey to start with.

Jonathan Widawski [00:02:17]:
You know, research has evolved so much since we started building maze. For us, it was kind of almost a selfish report that we wanted to run to better understand how we could better serve the research organization of the future. And so to do that, we need to better understand our customers, how they were, how their practice was evolving, how research was also perceived in organization, and we know that the past few years have been very tumultuous for the space, to put it lightly. So we wanted to be able to provide better answers for our researchers users and our product team users on how the space was going to evolve and what were the recommendations that we would make as one of the players in the space to better support organization. So, yeah, it's been an exciting journey. And from there, I think we've learned a lot of the key trends that we've seen happening in the market, both that on the one hand, demand for research is growing, which is exciting in itself, but the shape of research has changed how democratization has empowered stronger decision making. So democratization has been a taboo world in a space for a very long time. And for us, we're seeing democratization as a multifaceted solution almost to the research problem and the research scaling problem.

Jonathan Widawski [00:03:24]:
And finally, obviously, like the elephant in the room, how new tech can help scale research and most importantly, AI. And so I think a lot of overlap with your incredible report that you shared very recently.

Erin May [00:03:36]:
Thank you. Yes, just published today. State of user research just published today.

Jonathan Widawski [00:03:39]:
So big round of applause to your team. So, yeah, happy to dig in into most of those insights.

Erin May [00:03:44]:
Yeah, fantastic. And you mentioned that it's been kind of a tumultuous period. I guess just headline for me. We'll dig into the trends. But what's the vibe? What'd you get out of the report? Positive, negative? A little mixed? What was the vibe coming out of the report?

Jonathan Widawski [00:03:57]:
It feels like organization, a little bit schizophrenic right now in some ways. And the reason for this is that we've seen budget for research being cut, we've seen research teams being cut as well. So there's definitely a perception of the value of research in the business that needs to evolve. But on the other end, we're seeing the demand for research growing. And so we're trying to reconcile these two aspects of why organizations believe that research is not valuable and how we can make it more visible inside the. And then on the other end, why is research demand growing, and what does it mean? And so one interesting element that we identified was that with product budget and product teams being constrained, the opportunity cost of what you build becomes more important for organization. Meaning if you only have two parts that can work on something, ultimately what you focus your efforts and strategic resources on is going to be what's going to make you successful or not. And so while most companies don't really know how to frame this as we need more research, they understand that they'll need more insights to drive the right decision.

Jonathan Widawski [00:04:53]:
And so it's our role now as research practitioners and as people who do research to help educate the space on why research is the solution to the problem that they've identified inside the organization.

Erin May [00:05:04]:
All right, well, let's do it. Let's jump into the trends. So I think there were three kind of key trends that came out of your report. You want to run us through them at a high level and then we'll dig in more detail?

Jonathan Widawski [00:05:14]:
Yeah, absolutely. So the first one is that demand for research is growing. So I touched a bit on that, but happy to dig a lot more into what we've learned and the data that we've collected. The second part was we're seeing more and more democratization in organization. And we're seeing that democratization has a positive impact in both the perceived value of research and the scalability of research inside organization. And finally, we're seeing how teams are leveraging new tech to be able to drive better decision and how AI is going to be an assistant in the overall capture of user insights.

Erin May [00:05:47]:
So the demand for research is growing and we've got these trends going along with it that are going to make that possible, even as, at least in the short term, the headcount for researchers, capital researchers, is not obviously growing. So how do we make these things fit together?

Jonathan Widawski [00:06:03]:
Yeah, absolutely. So it's very related to what I mentioned at the beginning of this conversation. I think what we're seeing is that executive understand that they need to make the right bets for the market that they're trying to solve. They need to make the right bets. They need to understand their users. And so while they understand that they're trying to leverage more and more of the resources that they already have internally, the infamous people who do research to be able to power and capture more of the research inside organization. And so while the headcount for researchers is not growing, the discretionary budget for research in itself is growing inside organization. And so I think what we're seeing is that we can expect more and more non researchers to have to handle more and more of the research part of the process.

Jonathan Widawski [00:06:45]:
And on the other hand, for the researchers, what we're seeing is that they will need to do a better job at communicating the value of the research to their stakeholders. What we've seen in the report is that only 27% of execs are consuming research for strategic purposes. And so research is still relayed as a tactical operational resource versus a strategic one. At least from a perception standpoint. And so I think for the researchers, part of their job is going to be a bit of the selling the religion and the Bible, right? Explaining to the stakeholders why they need research and ultimately what their job is, because I think there's still a lot of brain damage from the last era of how research was perceived. I think what we're seeing as well is that we're seeing more and more people try to connect research data with business outcome. And so part of that conversation about how we can make research something that's more visible to justify the growing demand is by trying to make research data something that's very disconnected from the ultimate business outcome that we're going to drive into something where we can connect the doT. Part of the historical problem with research was that you could only see the ROI of research if you failed.

Jonathan Widawski [00:07:51]:
Most companies and most product team know of the IRI of research because they've run projects that didn't have research embedded into it. And so when research is run properly, what you're seeing is the opposite of that is people, it's transparent, right? It's, oh, the product works and people are satisfied with it, they don't connect it directly with research. And so we're seeing more and more people trying to connect the dot between the input of research inside the product development journey to the output of business success. So that's a trend that we're seeing. And finally, the capacity is going to evolve. Well, 75% of respondents say in our report that they plan to scale research in the next twelve months. We're not seeing that translated into a growing number of researcher running the research. We are more seeing a growing number of product people that are going to have to handle a research backlog.

Jonathan Widawski [00:08:38]:
And so it's interesting and exciting and I don't think it's unique to our space as well. I think researchers have a very self centered view of that problem, when in reality this is something that's happening across the board for every function, that's a support function in the business. And we've seen that ten years ago, if you think about the bi teams, ten years ago, companies had two options. Everyone wanted to be data driven so they could either infinitely scale the size of the bi team or they could find ways to put the means of making data decision in the hands of the people that had to make decision every day. And so we're seeing a very parallel approach to research. I think for like in the past five years, people have tried to scale infinitely the size of their research function, and they're seeing the limits of that. And so they're trying to figure out what is the right balance of the number of researchers we need and what is the evolution of that role moving forward, which is part of the second topic, which is the democratization of the practice.

Carol Guest [00:09:29]:
And will you share more with this demand for research growing? I was surprised to see in the report it seems like there's a lot of demand among the product teams. I think it's really well established in product teams to bring in user research and do research, but less so on the sales side. Like only 10% of people said that research had improved sales win rates. I'm curious about that. How is research sort of penetrating across the organization?

Jonathan Widawski [00:09:50]:
Yeah, that's a very good question. And it's a function of the reporting function as well. Right.

Erin May [00:09:54]:
I.

Jonathan Widawski [00:09:54]:
Research is not a structured function within the business, meaning that for most organizations, research will report into product, but we're seeing an evolution of that as well. Procter and Gamble, for example, have a chief insight officer where they get analytics and research and bi reporting into one function and they act as like the brain of the organization. When that happens, then research becomes fed into every department. It's much easier for research to spread outside of the historical product where they've operated. For organization, where research sits in product, research is used as a product resource. And so I think part of that evolution that we'll need to see is for the research role to escape the product organization, to be able to be seen as just like ops, as a function that supports the business and not a function that supports product.

Erin May [00:10:41]:
Right. And the trick is often two opposite things need to happen at the same time, right, being a kind of standalone central resource, but at the same time needing to really be close to product and to these people who are doing research, so that the time to insight, right. Can be sped up and can be close to the people who are going to actually act on it.

Jonathan Widawski [00:11:01]:
That's exactly right. And so I think what we're going to see as a transition is that first of all, the role of the researcher is going to move from operational to educational. I think that like many functions that are trying to democratize our practice and we're kind of jumping into the next point, but let's do it. Part of the challenge is that a lot of the people in the research field care a lot about their craft, but they need to understand that the craft now is about passing on the craft to others so that they can actually power research versus owning the craft themselves. And so it's kind of a switch in the mentality that researchers need to bring to the market. And so they need to do that first with the product, then they need to socialize the business outcome so that they can be seen as a business partner versus a product partner. So it's kind of a multi step plan to get them outside of the product and into the more broader strategic partner to the business. And just to be clear, a lot of researchers are already doing that.

Jonathan Widawski [00:11:53]:
It's just that I think the standard in the industry historically has been about research is a support function for product versus research is a support function for business decisions.

Carol Guest [00:12:02]:
Will you go through that sequence again? I think that's really interesting. It's something like you said you start with, they have been operating within the product team. They shift to educating the product team so researchers can focus more on outcomes and then as a part of that, become more of a strategic partner and then go to elsewhere in the business. Is that what you're saying?

Jonathan Widawski [00:12:18]:
That's exactly right. From operations to education first, and then from education to showcasing the business value that they've driven and then escaping the product team so that they can become strategic partner to the rest of the. I think every department will benefit from the user's voice, and I think that we need to make research a business partner versus a product partner. That's been one of the challenge that we've tried to solve at maze. Right. As well as a company, how do we make a tool that's not about just solving a research process, but how do we make it a tool that helps company drive better business decision themselves?

Erin May [00:12:52]:
Great. Yeah. And we're seeing the same in our research as well, whether it be the state of user research or talking to researchers. But everyone is definitely thinking about how do I show the impact of the work? Which is interesting because there is so much demand for research. Right. So qualitatively, people know research is valuable and they want more of it, but there's also. Okay, well, what's. Because resources are scarce, right.

Erin May [00:13:13]:
Because of the macro environment we're in, there's really this pressure on figuring out what's the best way to communicate the impact of this. What are you seeing in terms of how researchers and people who do research are working through those questions?

Jonathan Widawski [00:13:26]:
It's really hard. I don't think it's a solved question yet on how you can do a good job at connecting the doT. I think it starts with being the voice of the users for the product team at first. So making sure that the insights that you collect are seen across the entire product organization. And then at the end of this journey, it's trying to present to execs how decisions were made throughout the product development process. Because you won't be able to point out and say, the increase in the number of paying customers we have is linked to my work. But what you'll be able to drive is show how the product or the features that you've delivered have solved a customer need to the degree where they wanted to spend more with you, where they wanted to convert. So it's a tight line between showing how feeding the input in the system have led to better output outside of the research process and workflow.

Carol Guest [00:14:16]:
So we talked about who is doing research now and how that evolves. Your data has some great report on actually who is conducting research at companies today. We'd love to dig in there.

Jonathan Widawski [00:14:24]:
Yeah, absolutely. So it's the rise of the generalist, right? Like it's the rise of the people who do research. And so what we've seen is an increase in the spread of research across organizations. So, product design, 61% of product designers reported that they were running research. 38% of product managers, 17% of marketers, which is outside of the market research. It's a net new category that we're seeing actually in place research and customer success managers. So what's interesting is all the people that are both creating for users and that are the eyes of the organization are trying to connect more the data that they see to the things that they build. So it's an exciting part of the process when we're seeing the value being spread out.

Jonathan Widawski [00:15:04]:
I often use the Figma example to explain how democratization works and why democratization is important. Figma was not a successful company because they managed to make two designers move block together in a file. They became a successful company because all of a sudden you had a CEO in a design file. If you think about the sketch era and all of those, you would never have a CEO actually embedded into the software. And so when we talk about democratization, a lot of people think about the democratization of the practice, making more people do research, but really it's about the democratization of value, making more people exposed to the value of the things that you're doing. And when you're doing the former, you actually end up with the latter. When you have more designers, when you have customer success, when you have more people that are exposed to research, ultimately you get research results exposed to more people inside the, and that creates that democratization of perceived value inside the organization. And so I think for a long time, people try to gatekeep that part of we don't want the practice to be democratized.

Jonathan Widawski [00:16:00]:
And there's reasons for that. It makes sense. There's a lot of fears around the quality of the research that's going to be run and the role of the researcher moving forward. But at the same time, it's counterintuitive. But the best way to make research macro resilient is to actually make research democratized and as a practice and as a value inside the organization.

Erin May [00:16:20]:
And what kinds of research are folks doing? Marketers like me or these powder, the people who do research that are not capital r researchers, what sorts of research are they dabbling in?

Jonathan Widawski [00:16:30]:
I think what you're seeing is that a lot of people are formalizing the fact that they are doing research. I think that as a marketer, you used to talk to your users. You might not have called it user research, but it was something that you were doing. A lot of people, ultimately, part of their job is to capture the user needs, the user's voice, the user's positioning. And so right now, I think what we're seeing is that a lot of people are trying to better frame what they've been doing and get better support as well for the things that they've been doing, meaning marketer getting support for researchers on how they can run better user interviews, which is 89% of what we're seeing our users do. And then usability testing is extreme, still extremely high at 85%. So the usability of your product, and then that's followed by surveys at 85% and concept testing at 56%. So we're seeing the practice is evolving more and more usability testing being run as well, which is interesting and exciting, and then surveys across the world and concept testing becoming more and more prevalent in the space.

Erin May [00:17:25]:
So you kind of described an evolution that I've seen in my six plus years here in the industry as well, which is, you know, years ago, it was really, I don't like this democratization. I'm worried about my job, poor quality research, some valid, some more fear based responses, but we're fully in this. It's not an if it's a happening, it's there. It's growing to, we can worry about it, but so it's a how are we going to do it? Well, I'm curious what you're seeing in your data in terms of positive outcomes, some challenges, maybe that based on where we are right now with our democratization, evolution.

Jonathan Widawski [00:18:01]:
Yeah. And just like you have been in the space for a very long time, so I've seen the tide and I think you had judge very recently, I think, on the podcast who talked a lot about the reckoning of the space, right. And how the space is going to happen to us whether we want it or not. Like democracy is going to happen to us, how we deal. It's the, you can control the wind, but you can control your sales type of moment for, I think the research space, right? Like how do we react as a team? And I think the best in class researchers we're talking to right now are making that conscious transition to becoming educators in the space, right? When you have your product leaders, when you have your CEO's actually asking of the designers of the product managers to run more research, you can either be an agent of change and help that transition happen, or you can be an agent that's blocking the process and that's only going to damage the image of research for those execs even more. Right? So part of what we're seeing is researchers making sure people are asking the right question, helping them craft the right user interviews, helping them understand the data that they're collecting, and making decisions from the data. So at the highest level, it's basically removing the researcher from the tactical aspect of research, the collection of insights, and putting the researcher in a more strategic role, which is in itself exciting and the path of the future. Anyway, I think any researcher in an organization is looking to drive more strategic decision versus running user interview.

Jonathan Widawski [00:19:22]:
I think it was never about the means of what you do and always about what's the outcome you're trying to drive.

Erin May [00:19:29]:
Awkward interruption this episode of Awkward Silences, like every episode of Awkward Silences, is brought to you by user interviews.

Carol Guest [00:19:36]:
We know that finding participants for research is hard. User interviews is the fastest way to recruit targeted, high quality participants for any kind of research. We're not a testing platform. Instead, we're fully focused on making sure you can get just in time insights for your product development, business strategy, marketing and more.

Erin May [00:19:54]:
Go to userinterviews.com awkward to get your first three participants free. I think that's an interesting spot where researchers are in this process where we talked a little bit earlier about this emphasis on impact and how do you name impact and think about it? And then there's more of the doing the strategic research versus the tactical research, and then you're also talking about this role of education versus doing research. And I'm hearing a lot of researchers, well trained researchers, that are on the one hand, interested in doing more strategic projects, maybe as a center of excellence, getting those insights out to the entire company, but also some resistance in the education sometimes. Are you saying that I don't want to be a teacher? Or can someone help me with this teaching? Maybe some research ops people or. What are you saying there? Yeah.

Jonathan Widawski [00:20:42]:
Yes, we're seeing the same thing. I think there's like a rift right now between the two types of researchers that we're seeing in the space. And that's kind of the, let's call it the legacy researcher that's about running the research, that cares about the craft, and that that's an important aspect of the job in itself for those people. I think that the problem is that they will have to make that transition happen. They will have to see through the education piece. And what we're seeing is that some of the challenges that they have besides the I don't want to be an educator. Is that again ensuring the data quality and accuracy? This is a job that's very academic in itself. It's very hard to give away your legos when you have a PhD in handling the Legos.

Jonathan Widawski [00:21:21]:
I think it's accepting to have a different bar for how people and companies make decision. Because companies operate on trend line, they cannot operate on. Look at the way that we operate with data. Look at the amplitude of the world, right. I don't think product teams are making the best decision from amplitude constantly, but I think that having access to those trend lines on their own unlocks a lot of the decision making that they have. One of our customers is Google flight. And when Google is struggling to do something, it's generally a good moment to reflect on what's happening in the space. And the head of research at Google Flight struggles with the volume of decisions that product teams have to make every day.

Jonathan Widawski [00:21:57]:
And they can only staff so many researchers. And so as much as that researcher and his team care about the craft, the reality is that they're seeing that reckoning happening to them. And so I think part of the job of everyone is just accepting the evolution of your function and your practice. Right. When I started my career, I was in design and research. At the time, I was called a web designer. And then the practice evolved and you had Ux designer and Ui designer. And so practices are bound to change and we have to embrace it.

Jonathan Widawski [00:22:25]:
Otherwise we are left behind, I think.

Erin May [00:22:27]:
Yep.

Carol Guest [00:22:27]:
So you've talked about the evolution of the researcher. I wonder if you. There's a similar story in the evolution of the powder, right? Where you might come from consuming that research. Maybe you just see all the report to, maybe you observe a session or you eventually lead a session. I don't know if there's a similar story you tell in the other direction.

Jonathan Widawski [00:22:43]:
There is an entirely similar story we're telling because we're seeing the same type of resistance. Right. There are still the designers that don't want to do the research and that want to care about their craft in design and was thinking the same for product. Like, why should I be the one running the research? And so it takes a lot of education, and that's part of the educational role of the researcher. It's not just about the practice, it's about the why you need to run the research. And like, it's, again, on my analogy of selling the religion in the Bible, we're seeing a lot of that happening inside organization where researchers have to sell research to the rest of the product department so that they understand why they need to do it and then how they need to do it. Right. So it's a two step process that starts with explaining the value of it and why we believe that the people that make decision every day should have the means to make those decisions on their own as well.

Erin May [00:23:28]:
Great. So let's move in. Let's talk a little bit of technology. We all love technology. We sell technology. Everyone listening is building technology in one way or the other. And of course, AI is here and is part of the story. So again, we have more demand for research.

Erin May [00:23:42]:
We have fewer slash non growing number of capital r researchers, and we have this democratization happening. We have researchers teaching powder how to do research. They're learning how to do it better. And we have technology which is growing rapidly. So where are we right now? How is technology playing a role in making more research happen? Making better research happen?

Jonathan Widawski [00:24:03]:
Yes, I think everyone's tired of hearing about AI at this point. We'll talk about it. I actually think it's a very interesting moment in the history of research. So it's an interesting moment, the history of everything because of AI and what it means for our functions, but especially for research, I think for functions where the role was heavily skewed toward collecting data, when technology finally enabled us to collect those data at scale, what happens with our function? What does it mean for us? And so part of that trend of democratization that was happening in the background is kind of reinforced by the technology that's supporting it. But I actually think it's a very good thing for the space. And the reason for that is that, well, AI accelerates the capture of insights, like at the tactical level. If we zoom out and we think about what is going to be the impact of AI on the broader way that we build as an organization. In the past 20 years, organizations have optimized for time to market.

Jonathan Widawski [00:24:59]:
The best in class companies were the ones that could push something the fastest to learn from their users. It has shifted the center of gravity of learning to telemetry. We learn less at the beginning of the process, and we push something fast, like it's the move fast and break things that are aware of. We try to push something as fast as possible so that we can learn from users. The reason we ended there was because the space at which product was being built to the pace at which we could learn about users was at odds. And that has been happening for the past 30 years, since we started building software. On the one hand, the thing is that for the first time, technology allows us to have user insights available at the speed of product development. So it means that companies don't have to choose anymore between building fast or building right.

Jonathan Widawski [00:25:37]:
So we can move away from a process that was heavily skewed towards being fast at being wrong, versus a process that's about being fast at being right and faster than your competitors. But the second thing that's happening is that what we believe is that a big part of the product development process is going to be mostly automated, meaning that your capacity to build fast not going to be a competitive advantage organization anymore. When that happens, when your capacity to build fast no longer competitive advantage, then what you build becomes the competitive advantage. If everyone can build stuff, ultimately what you build is what matters for organization. And what you build is a massive part of the research journey, meaning that research all of a sudden becomes the center of gravity of companies success in organization. And I think that's what we're seeing with AI, is that on the one hand, it's accelerating the process of capturing those insights, and on the other hand, it unlocks what we call at maze the time to write, which is a shift in mindsets from how fast can we push something and learn from it, to how fast can we learn about our user needs to actually build something that's going to be valuable to them. And we're seeing organizations already reorganize around that concept and trying to understand their users better, versus trying to push stuff to production the fastest.

Erin May [00:26:46]:
And you wrote a great piece about this. I'm sure you can find it easily on your website recently, right the time to write idea. So we'll make sure to link that in our show notes as well. But it is interesting and AI is also making it much, much, much faster. And will, we don't even know how fast yet potentially to build to code, right. So not only can we get the insights faster, but that phenomenon and you described of move fast and break things is like, I mean, move crazy fast and break lots and lots of things because you could imagine, right, what you could do with that trend is say, well, we'll just build a thousand things and see which one sticks because we can build them so fast and so cheaply. And I'm curious to hear why you think companies aren't doing that and shouldn't do that. Instead they should get the information to build it right the first time, given that it's exponentially cheaper and faster to build.

Jonathan Widawski [00:27:36]:
Yeah, absolutely. I think people just won't have the volume right for you to be able to run 10,000 experiments on the things that you want to learn. That's not a sustainable way to build. I also think that as consumers, we'll become blind to those type of experiments we're already almost all blind to. Like your business model is showing type of growth experiments we're seeing on every product. I think we're going to get more and more blind to this. It's very similar to me to the ad apocalypse that we saw 15 years ago when people started implementing ads everywhere and then consumers became entirely blind to it and refused almost to engage with them. So I think that's a big part of why we're not going to see just a massive influx of shitty product being built and released to market versus people being more conscious about it.

Jonathan Widawski [00:28:17]:
There's a term that I think the New York Times coined for that, that they call the garbage apocalypse is coming. And it's a big part of that, right? If everyone can build, only the things that actually solve user problem are going to be visible in the market, right?

Erin May [00:28:29]:
So you could potentially do that, but you don't have enough, like the opportunity costs of your limited audience bandwidth to absorb all this crap you want to throw at them. And then of course, the brand experience, you just destroy your brand and the process.

Jonathan Widawski [00:28:41]:
Exactly. That's the reason you still want to understand your user needs. Like when we talk about the value of research, a lot of people associate the value of user research to, like, product development process, right? Oh, we're wasting our resources on building the wrong thing, which is true, but also the cost of brand damage that you get from exposing your users to the wrong product or experience the cost of lost business from implementing the wrong flows, the cost of support for having to support a broken flow or product. Like all of these things are not just the product development process and they have a massive cost in itself.

Erin May [00:29:12]:
Yeah.

Carol Guest [00:29:12]:
And I think we've all been through this sort of lean startup era of tons and tons of experiments that none of which proved out right to learn that actually maybe we need to back up and do a little more research to get that value from experiments.

Jonathan Widawski [00:29:23]:
Exactly. I think as a space we have a lot of brain damage from that move fast and break things era. I think that it was the common wisdom and it made a lot of winners. Like if we think about the history of building product, we went from in the nineties, you build product and it took years and that was fine because you released a physical CD ROM to the market. And so research could take months at the time, because if you're building something that take years, research can take months. As we moved online, as we moved to the web, we saw that, that transition to the Movfast and Brexit as the common wisdom to how fast you could learn versus how much you could invest in research to learn. And I think what's interesting with the state of the space right now is that we're moving back. It's a new era for product development.

Jonathan Widawski [00:30:02]:
Our belief is that that era is very user centric because that's going to be the only currency that companies have to be successful compared to everything else.

Erin May [00:30:11]:
Yeah, yeah.

Carol Guest [00:30:12]:
So companies are using AI to build faster. We believe it could get lots faster to build and then they're also using AI. A lot of respondents in this study to actually using AI for research. So I'd love to hear more about how our teams using AI for research.

Jonathan Widawski [00:30:25]:
Yeah. So on the tactical level, when you think about user research and the different steps in the user research journey from how to create a study that's going to yield great results to running the study itself, to then tagging, analyzing theming, everything that as a former researcher I spent countless hours doing, you can see how AI can be either a better partner in that process or entirely owning the process. And so what we're seeing is things like transcription generating research questions, synthesis and reporting are being used by 45% of our users today. We're already seeing this as like AI being a very strong partner in the process. At Maze, for example, we've implemented a lot of those features to make sure to alleviate some of the fears, for example, of democratization, making sure that people are asking the right question, how can we leverage AI to remove bias from the question that people are asking, how can we leverage AI to help people craft the right user interview, study? And then at the end of the process, once you have the data, how can we use AI to automatically tag and create seams out of the data that you've collected? And we're seeing this across the board that time that was never really valuable in itself. Is shifting toward AI. An interesting thing that we've seen as well is that the trust is shifting left. And so what I mean by that is if you're a researcher and you go to a product team and you say, this is what we've learned about the stuff that we need to build or how we need to implement it, the first question the product person will ask you is show me the data, because they will want to see the data to prove or disprove the thing that they believe.

Jonathan Widawski [00:31:55]:
So there's always been this kind of trust relationship between the product and the research team. And now what we're seeing is the researchers asking the AI to show the data. And so it's kind of we're shifting from one player of the space to asking another about the data. But so what we're seeing is that a lot of the solutions that are trying to implement those AI features to siem and aggregate the data needed to do a great job at showcasing how they came to the conclusion they came to, because the researchers will be the one now checking the proof that they need to make a decision.

Erin May [00:32:25]:
Yeah, there's a big kind of, I don't want to say QA because that might sound too downstream, but there's a big quality control aspect to research in the future, including are we asking good questions, are we training the team to be able to do good research? And then are we using AI the right way? Are we using these new technologies in a good way? And fact checking and so on.

Jonathan Widawski [00:32:45]:
Exactly. And we're still very early days in that technology as well. So I expect it to get better and better. But, yeah, there's the trust we have with this software needs to come with a lot of control still today.

Erin May [00:32:56]:
Great. Okay, so we've talked about demand for research is going up. Everyone's doing research. AI and other technology such as maze, user interviews and otherwise, is making it faster to do good quality research. Your reports, the future of research. Let's talk about the future. Let's predict the future, which is always a good idea. So what do you think is going to happen these next couple of years based on your research and just having your finger on the pulse in general?

Jonathan Widawski [00:33:20]:
Yeah, we touched on it a bit, I think. So we can try to think about it at the tactical level on how it's going to affect the resources job in life. And I think we touched on that a lot about how the software is going to help accelerate that capture of insights. I think we're going to see more and more AI moderation. We're going to see how people are going to try to solve for the collection of qualitative insight at the speed that's quantitative. And so I think we're seeing a lot of, of players trying to solve for that problem. So I think we're going to see a lot of experiment to what research means. I think it's going to push a lot of the boundaries of what we want and what.

Jonathan Widawski [00:33:55]:
So we're seeing, for example, synthetic users for the first time, which is something I don't believe in at all. But it's so we're seeing the space kind of try to bubble up with how can we leverage the technology to accelerate research. And then on the other end, we can look at how it's going to affect organizational design and how it's going to affect what companies value moving forward. And that's, again, like, for me, what we expect to see is a shift towards time to right as a key defining factor for what makes companies successful. Basically, how much does it cost you today as an organization to be wrong? And how much time do you take to be right? And I think those two questions are going to be central to the best performing organizations in the world. And I think the second thing we're going to see is a bundling. So what's interesting is if you look at the state of the market in general with tooling, what we're seeing is a bending and unbending of needs. And I think we're in the rebounding era, and that bending is going to come at the cost of creating an operating system of user insights.

Jonathan Widawski [00:34:52]:
That the research insights is just one part of the broader picture of the market research, the user research, the product analytics. We're going to see a centralization of insights to feed into how companies build products. So my prediction for the futures are faster research role of the research is going to be educational. And then on the other end of the spectrum, research insights are going to be just one part of the broader operating system of insights for organization. And that the company that will win tomorrow will be the one that will be able to capture and collect those insights at scale so that they can make better and faster decisions than their competitors because that's going to be the only differentiating factor they have to be successful.

Erin May [00:35:30]:
Great.

Carol Guest [00:35:30]:
So before we jump into our rapid fire section, any thoughts, wisdom for someone who is a researcher or maybe someone without a researcher title who's doing research as they sort of prepare for this future?

Jonathan Widawski [00:35:42]:
Yeah, I think researchers, just like Ops, we're support function in the business, right? We're here to solve a business need. Your job was never about the practice itself. Your job was about how can I help this organization be more successful. And so I think that this is the mindset that we need to bring as practitioners in the space and that we need to accept the evolution of our role. So if I were a researcher today, I would try to better understand what is the perceived value of my work in organization and how can I do a better job at actually exposing the value of that work? Connecting the dot for the stakeholders. Because in an ideal world, every stakeholder in the world would understand the value of research and we wouldn't have to do that job. The problem is that we are not there yet. Design had to go through the same thing.

Jonathan Widawski [00:36:24]:
Data had to go through the same thing. Exposing the value of what we do is part of our job. So I would focus there and then I would make myself the ultimate generalist that can switch from operation to education until companies have figured out what that means for them.

Erin May [00:36:39]:
And to your point, when you're talking about researchers and people who do research, it feels like those are applicable tips to a lot of people in a lot of roles. As AI comes, everyone saying what it's like. AI is like a dumb intern, or maybe they're a smart intern. Either way, they're an intern. But, you know, you're the one doing the whatever, the brainy work, right? And so you're outsourcing this sort of administrative stuff that you maybe don't want to be doing something along those lines anyway. Okay, so that's the future for everybody. So I think, yeah, but like, stripping down, like, what does it even mean? Like, to be a marketer or product manager? What are the essential skills I have? And to your point, how do I use those to move the organization forward?

Jonathan Widawski [00:37:16]:
Exactly. And I think, like, the identity crisis that we're going through right now is not unique to us. Every function is going to be to have to think about what they are, what they do, what are the things that are not going to be part of your job moving forward. And what does it mean for your, for your job, which we've worked for, that, I think a lot of people with AI forget that as humanity, this is why we wake up every day. It's to try to automate as much of our job as possible. And so resistance is futile. In a way, it is what we've tried to achieve. Yeah.

Jonathan Widawski [00:37:46]:
So, yeah.

Erin May [00:37:47]:
Ultimate giving away of the Legos, which you mentioned before.

Jonathan Widawski [00:37:50]:
Yeah, exactly.

Erin May [00:37:52]:
All right, rapid fire time. What is your favorite research question? You were a researcher before. What questions do you like to ask?

Jonathan Widawski [00:37:59]:
So, I'm not, I haven't done research in. Sometimes now I do. I do talk to customers all the time, but sure. So it's a question that I like to ask in general when I am interviewing both founders or customers and we're trying to build something. And the question is, who do you think should be building this? And so, as human race, we're terrible at understanding our competitive landscape and our competitors and their strengths. And so what I love about that question is that it forces the people you're talking to not talk about you defensively, but to talk about. So, for example, if you say we're building this new feature, that's going to be an interesting part of our product, who do you think should be building this? The answer they will give you will provide you with all you need to understand who is better positioned than you in the market to do that thing? Why are they better than you? How would they implement it if they were to implement it? So it's a very interesting question that works across the board from when I talk to early stage founders to understand their competitive landscape to when we are building things internally to better understand who has the most legitimacy to do these things, how would they implement it and why, and how can we be better at doing it than they would?

Erin May [00:39:02]:
Nice. That's a good one.

Carol Guest [00:39:03]:
Love it. Never heard that one. What are two or three top books that you recommend to others?

Jonathan Widawski [00:39:08]:
So the design of everyday thing is something that I recommend to everyone. I think it should be like a mandatory read for every human being that we all interact with interface every day. I think understanding how interface work is critical to our world and how we experience it. Because of this conversation today, I would highly recommend people read the business value of design by McKenzie. It's a report that was released in 2020 where they analyzed what does great product mean for business? Right. Not on a purely quantitative basis. What happens when business actually invests in design? What happens when business actually invests in research and product? And so at the highest level, it helps you as a practitioner or people, or someone who do research to express and to talk the language of the people you're reporting to, the execs that you're trying to convince. And then the last one is one that I like to recommend as well, especially for researchers.

Jonathan Widawski [00:39:55]:
It's how to win friends and influence people. It's an old book that talks about building influence, that talks about the soft skills that you need to be able to rally people around your practice and the things you do. So, yeah, often I feel like as practitioners, it's easy to get stuck in our practice and in our bubble. This is a good way to rethink how we interact as cross functional partners with the rest of the organization.

Erin May [00:40:18]:
That's right. That's right. Those people relationships also become more important as the robots don't take over. They're just there. They're around. Awesome. And, Jo, where can people find you? How can they learn more about Maze? What are you excited about at Maze? Leave us with some maze. And Joe, thoughts?

Jonathan Widawski [00:40:38]:
Yes. So LinkedIn is where most people can find me. I'm on Twitter as well. I haven't been active on Twitter since it became x.

Erin May [00:40:45]:
It's Twitter.

Jonathan Widawski [00:40:46]:
Yeah, the cesspool it became has kind of driven me away from it. So, yeah, LinkedIn is where you can find me. Feel free to ping me if you have any questions as well. Following this podcast, I'm always happy to talk with people in the space, practitioners to discuss, even if you disagree entirely with what we shared today, I'm always happy to hear the counterpoints of that. And then today we're releasing our feature, which allow people to run moderated interviews with their users. So it's a massive one for us. We've been mostly quantitative and usability, and today we finally break the barrier of moderated, thanks to AI in big parts. So, yeah, please try it out.

Jonathan Widawski [00:41:21]:
We're very, very excited. It's been a year of building for us, so let us know what you think.

Erin May [00:41:27]:
Awesome. User interviews by maze. Not to be confused with user interviews by user interviews. Amazing. But check everybody out. All right, Joe, thanks so much for being with us. This is great. Great to zoom out, talk about the future, and maybe we'll sync up in a couple of years and see what panned out.

Erin May [00:41:44]:
And the future is now, you know, we'll see how things are going. Yeah. All right.

Jonathan Widawski [00:41:49]:
Amazing. We love that. Thanks a lot for having me today.

Erin May [00:41:52]:
Yeah, thanks for coming.

Carol Guest [00:41:53]:
Thanks so much. Bye.

Erin May [00:42:00]:
Thanks for listening to awkward silences. Brought to you by user interviews. Theme music by Fragile Gang hi there. Awkward silences. Listener, thanks for listening. If you like what you heard, we always appreciate a rating or review on your podcast app of choice.

Carol Guest [00:42:25]:
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Erin May [00:42:44]:
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