Democratizing UX Research Using AI - Interview with Shrey Khokhra, Userology

0:03 Hi and welcome to AI for UX. This is a space where researchers and product leaders come to stay current with AI innovations. I'm John John Whan, the founder of Brilliant Experience and we're a psychologydriven product innovation firm. In each installment, we speak to a founder of one of the latest AI enhanced research tools and dive deep into the inspiration for it and how it might benefit you and ultimately where this is headed. So today I'm joined by um Shrey Cochra and he's the uh co-founder of Userology, a tool that really does a lot. It helps you to understand your users by generating an interview plan, recruiting participants, conducting interviews, and presenting your final report, which is quite a lot.

0:44 So um so I'm delighted to have him here. And just a quick note before we get started, um all these, um videos are not product endorsements. Brilliant always pays full price for any technologies we use and no one's getting paid. It's just for us to learn more. So with that, let's get started. So um Shay, thank you so much for agreeing to do this and um we're I'm delighted to have you here. Thank you, John, for uh for having me here. Uh excited for uh for the session today. Well, let's dive into userology because it's got a lot uh to go for it.

1:15 So maybe you can tell me a little bit about just who your target audience is for your product and kind of what the pain points it addresses. Awesome. So user logic as uh it's a AI UX research agent built for PMs and designers to conduct their own research. We saw that a lot of research teams wants to uh empower non-ressearchers conduct evaluative research and focus their energy on macro research. Uh this is where uh an AIUX research agent would come in which would work with uh the PMs, designers, essentially the larger product and the UX team and and and help them conduct uh research which would ideally uh take you know months to conduct. The AI agent essentially helps them conclude the research in in a few hours.

2:09 Cool. And um yeah, it is kind of mindbending that that's even possible, you know, for all of us who have, you know, when we're just start to try these tools. Um so can you what would be a typical scenario when folks are using tools like yours? Um when might they when might a product owner or product manager use a tool like this? Yeah. Um so right from if you are discovering new opportunities, new pain points just to understand your maybe persona uh you would ideally use user logic to conduct an open-ended research discovery research or if you are if you are someone who wants to validate the wireframes or your high fidelity prototypes you can still use the tool the AI is capable enough to uh you know look at the screen hear the participant and ask probing questions Or if you are someone who launched a product and you know you want to sort of create a group of beta users and and see how their experience was, the AI is able to uh live stream the shared screen of the participant and uh ask questions based on the screen interactions as well as uh the participant feedback. So all the use cases right from discovery to uh solution validation to post launch as well. This is something that we have seen a lot of PMs and designers uh using the platform for. Cool. Um and uh yeah, I mean that's um more than is often typical in these kind of cases. So I actually did want to ask a question about what makes um userology a little different or better than other options.

3:49 And clearly having that ability to to share a screen and so on is one piece, but h how would you describe how userology is uh unique? So uh I think on two aspects one is uh there have been a lot of pull from non-ressearchers to conduct their own research particularly evaluative research. Um the tool is primarily made to keep uh the uh the human in the loop essentially where it works with them instead of automating the entire stuff.

4:24 um that's where the setup and the whole process of you know launching the study is different. The second is the vision capabilities. Uh I think we are have uh done decent job in giving AI to see what's happening on the screen and ask questions just like uh someone with a good research background would do. And that's something I I guess I I don't feel like I see quite as much. So I I think you're going to show us that in just a sec. That'd be great. Um so just uh for some so if I'm a product owner or a um UX researcher um how would I work differently once I have this tool? So first of all I guess if I was a PM I might not have ever have done the research before but uh maybe for I'll be selfish for someone like me like a researcher. How would I work differently using userology?

5:18 So um essentially the the the turnaround time for you to get insights is significantly lesser. This is where it increases the scope scope of research and it essentially empowers people uh to conduct more research and since the turnaround time is lesser the stakeholders uh you know the business stakeholders are more open to doing like more research. uh before AI it wouldn't have been possible where you know it would take like you know tens of thousands of dollars and a few weeks before you can see the insights that's where the reluctance of doing research would come in but with an agent especially something that can conduct holistic research um opens up a sort of you know more sort of um I I would say openness to conducting uh research on the hypothesis that anyone in the organs, you know, facing. Um Yeah. Yeah. Um and you know, in when uh us at at my company started using tools like yours, um I kind of didn't realize how much like how fast we could turn things around and still have high quality. And also just there's a little bit of um uh what inclusion that I guess I might talk about like I can I can have my Swedish isn't very good. So I can include people from Sweden or people in uh New Zealand who have a time zone that's really hard for me to work with. And so suddenly I get a sort of global access that I wouldn't have got otherwise. Um so um yeah it's it's hard to understand before without trying it. Yeah. Go ahead. Yeah.

7:00 So absolutely I mean uh if you if you look at Figma right it's uh it's it's a design tool you know it's it's very simple to create designs. Uh but Figma like democratized design in a way which you know uh the other design tools could not. Uh that's where you know someone like a CEO could come in on Figma and see like what's uh the you know new product that's being designed which like know like involves a lot of people into the whole design process. That's where uh a tool like an AIUX research agent would do which is democratizing research which would involve a lot of other stakeholders uh in the ecosystem which would you know uh then increase the validity of uh conducting good research and then and and and the credibility of conducting continuous discovery uh throughout the arc.

7:53 Excellent. And um yeah um so actually have you seen um uh PMs and others actually picking up the pace of the research they do or is it that they do larger scale studies or what what's been typical in your your case? So we have seen two um sets of teams. One is um the tools serving researchers uh who are looking to democratize research internally particularly value research. We are not talking about like macro research. Strategic research is something that researchers uh I I think we are uh of the opinion that it should be still driven by researchers. Um but and and the second set of teams is PMS and designers doing it and driving it themselves. uh which is something that would uh you you would see that like they they would either uh use tools like user testing but it's like more focused on research teams uh but if you want people to do their own research you need so slight test of handholding that handholding is done by agents right so these two sets of teams have have uh we have seen like um um more adoption in terms of yeah well Um, and you know what, um, we should do is, um, uh, why don't we go ahead and, uh, if you can start to, uh, share a screen. I can, um, set it up so that we can have you and, and your screen. And I think we should show what it's like to to do this. So, you can just tell me the scenario. Is this for a participant or is this for a researcher, a product person? So, this is a participant experience for a prototype of an app called Splitwise.

9:36 It's an expense management app. Um just consider that a designer have sort of built a flow and you want to test it out with the participant. They would you know go on user logic create a study and this is the link that would be generated after the study is created. Now this link is shared with the participant. I am the participant here. Uh I'll just start the study. I'll just type type my name. Um, yeah, perfect. Thanks for confirming S's.

10:10 Let's begin. I want you to know that there are no right or wrong answers today. I'm just interested in learning about your experiences and thoughts. Could you start by telling me a bit about yourself and what you do? Sure. So, I am a product designer working at uh a fintech company. Hm. Thanks for sharing that. S's what kind of personal expenses do you typically share with others like friends, family, or roommates? I'd love to hear about your experiences with that. Um, I would uh usually share uh expenses with my friends uh when going out for a for a dinner or something like that.

10:53 Could you walk me through how you typically handle splitting those dinner expenses with your friends? What's your usual process? Um, I would um just note it down in my WhatsApp and then go home and maybe use a a Google sheet or something to track. Interesting. Could you tell me more about how you use Google Sheets to track these expenses? What kind of information do you typically include in it? It's just the name and the um the amount.

11:22 Yeah. And what happens after you record these amounts? How do you handle the actual settling up process with your friends? Um, yeah, I mean it's it's it's usually organic. Uh, we don't usually like remind or something like that, but it's Yeah. Um, it's like just a track record for us to have it crystal clear. Yes, that's clear. Have you ever faced any challenges or difficulties with this current way of tracking and settling expenses? Maybe times when it didn't work so well?

11:59 Um, yeah. I think it sometimes get uh cluttered and you know, you just lose track of uh things. It's it's nothing as such in general when it comes to challenges. Yeah. Okay. Thanks for sharing that, S's. Now, I'll be showing you a prototype shortly, and we'll work through some tasks together. Before we do that, are you comfortable with me recording this session? It'll help us capture all the valuable feedback you provide. Sure. Yeah, that works.

12:35 Let me first confirm. Can you see the prototype on your screen? Yes, I can see the prototype on the screen. Great. Let me explain your task for today. Imagine you recently went on a trip with three friends. Friends 1, 2, and three. And all of you made various expenses. You spent $500 on booking a hotel for everyone with the cost being evenly shared among all friends. Your task is to add this expense on the splitwise prototype. Does that make sense to you? Yeah, that makes sense to me. Let me just explore the prototype now.

13:11 Sure. Go ahead and explore. Please share your thoughts as you go along. Okay. So I can see I can add expense, I can settle up. Um yeah, so that's that's about the onboarding. Um let me see. Um I'll probably skip setup for now. Don't want to spend a lot of time and exploring the app. I don't know.

13:42 Since you're on the setup screen, which of the three options would you select for this task and why? Take your time to think about it. I selected skip setup because it didn't make sense for me to invest a lot of time in something that I don't know. Probably I'll go ahead and start a new group. Yeah. What are you thinking about as you look at this screen? Um I I'm just figuring out like would it be like other or trip? Probably I'll go with trip.

14:28 Okay, trying to add group members here. Uh I've added three friends and then I'll maybe go ahead. Okay, so I think I have added all the three members. Um adding expense would be the next step. Okay. Um so hotel booking is something we need to do, right? Uh is it $300 or Yeah, we need to add like $500. Yeah. Okay.

15:10 All right. Okay, I have added the expenses. Thanks for completing that task. Could you tell me about any challenges you faced while adding this expense and setting up the group? What parts were easy or difficult? I think it was pretty much uh straightforward. So, not a lot of things I can complain about.

15:40 On a scale of 1 to five, where one is hardest and five is easiest, how would you rate the difficulty of completing this task? I would say one. It was quite easy. Just to clarify, you mentioned one, but also said it was quite easy. Yeah. Since one is the hardest and five is the easiest on our scale, could you please confirm your rating? Yeah. What number would you give it between one hardest and five easiest? My bad. It Yeah, it's it was it was easy. Okay. So, I'll end the session now. Um, as you can see, it's it's it's quite wary about the the flow and the screens that that are being uh you know uh shared. Um, now as next step what I'll do is I'll uh show like exactly how we arrived at that. Um basically the setup process um I'm assuming that you can still see me, right? Yes, everything's perfect. Y awesome. So the study setup is like pretty simple. You just need to give AI.

16:43 So we are um looking at a sample study uh about discord. Um so let us say you want to test out the server creation flow uh or you know like discoverability of DMs and like how you can run games in DMs, right? So you give a very high level objective to AI and uh and then user details. So user details would be necessary in in in two sense. One is of course it would know who is it talking to and second is it would create screeners automatically when recruiting.

17:16 Uh and then once we do this it would create the first draft of the interview guide. So um like uh everything you see here is something that we have kept that we keep the uh the person doing research in the loop. Right? So the first draft is something that takes away all the rigor of planning your research. Right? um right from you know like framing the questions to like what should be the flow of questions to like what should be the uh the structure in which um uh the prototype would be presented right so this was a live product research uh as in it did not really need a prototype the user was expected to share their screen and uh uh everything on the screen was something that the AI was able to see and ask questions on you can see it started from welcoming the participant to like you know um asking the familiarity with discord and then uh you know uh explaining what the focus area of the study was. Um, so Sh, oh sorry, just a quick question there because really interesting. So the first section um, it's not necessarily the the exact wording of what uh, the AI might um, ask the questions of. It's more a highle thing for someone like me or the product owner. It's sort of that perspective. Exactly. So just imagine that you got on an onboarding call with a with someone who just joined your organization, right? You would just give them an instruction that you know we need to cover this and then this and then this. Okay, don't forget to cover this, right? If you want to sort of, you know, add some things here, let us say um cover the uh familiarity with uh Instagram communities, right? Or something which would which is something that you would want them to um cover as a topic, but not necessarily you specify the time stamp or anything. uh just say that these are the things and you need to sort of make sure that this happens.

19:17 Cool. Thank you. No, please go ahead. This is interesting. Yeah. Uh the second section is about the live product research. So now after the introduction, the user is expected to share their screen. Um as you can see the task setup was around them opening discord.com, creating an account, right? and then um like completing the signup process and the last task was for them to discover uh and play games as well. Right? So you can also see what all things would be covered in that section. What all things that the AI would be asking the user while they are playing the game or discovering the game. So uh something like hey uh if the uh let's say if the user is confused about the task or if they are struggling ask what they are looking for something as simple as that or if they complete the task ask them about their ratings and if they give rating more than four tell them ask them like what made it so easy if they have any suggestions to improve. So as um as as someone who would uh who would not who does not really have the background in research, I think some something which enables them to conduct research in a plain simple language is is quite powerful. Uh I would say so once this task is completed you uh um we we have a panel of u like u we have our own panel as well. We have integrations with user interviews uh respondent and prolific where uh they get access to millions of participants across the globe. Uh but let us say if you want to recruit the participants on your own uh you can just simply copy this link and and share it with uh your group of people. If you want to change the voice of the AI or if you want to change the speaking and listening levels and the silent levels, uh you can simply uh change it on like for example if you want to want AI to be you know more of a observer and listener you can just simply uh change this levels and and and make sure that you know it it behaves as an observer rather than asking questions by question afterwards. You can simply change the accent uh based on age, gender and and and and you know um you can also change the aftar library as well. Uh but I I'll I'll show like one of the recordings that might uh make it more clearer on like what exactly I uh meant by live screen sharing. So, okay. Yeah.

22:08 So, I'll show you what I've got at the right is the um the transcript from this that your tool has made. And then if you click on a part of the transcript, you're jumping the video to that spot. Is that right? Absolutely. Yeah. Yeah. Cool. Yeah. And and these recordings would also segregate the challenges and the positives from the entire recording of like for right. So for example, if you want to go through a theme that made uh the DM entry point undiscoverable, you can just simply click there and it would like um redirect you to there and you can just simply download all these reels and highlights as well.

22:50 I'll just quickly play this uh right the side of the of the window because I found here like a person's icon. The context here is that the user was not able to discover the chat icon as well as the uh how to start the game, right? Uh that's where um the AI understood that they are looking at like different areas of the screen but not able to figure out. Let me ask how difficult or or easy it was for them to figure this task. uh that would display uh uh member list as is still here in the in the label, right? But um I could also find here on the left side where I am moving the cursor, the mouse cursor, I thought maybe here I could find um an um a person or member list. Um, I would look rather on the right or the left. Uh, I see you're looking at different areas of the screen. On a scale of 1/5, where one is not discoverable at all and five is very easy to discover. How would you rate the discoverability of the direct messaging and games feature so far?

24:09 Uh, well, I will rate it with a three because I cannot find the option easily. So they said that it's it's uh it was not easy to find that feature. Um but they were not like descriptive about why it was not easy so it probed more. Could you tell me could you tell me more about why you gave it a three? What would have made it more discoverable for you?

24:40 Erh maybe having an an icon with a name or the label that uh for direct direct messages because I cannot find it. What kind of friction points or challenges are you experiencing while trying to find this feature? I I would also like want to um like show one more example where it was um um quite intelligent enough to understand uh where exactly it needs to help versus where it needs to dive deep more. So as you know the study was about discoverability of a particular feature.

25:22 Now signing up is you know a basic requirement. uh but what if a user is not able to sort of you know like figure out the sign up in that case the AI would like sort of help them so that they can reach to that feature which is uh something that they need to know you know explore like I'll I'll just put some whatever other email I have uh register so I'm going through the create a new account process.

26:01 Uh I see you're looking for the registration option. On the login screen, there should be a link or button specifically for new users to create an account. Can you look around and let me know if you spot something like that? So something like this would essentially um empower uh the um like someone who don't are looking to like conduct research on you know a live apps uh yeah any any questions anything so far that stood out for you John? Yeah. Um uh actually I did want to ask you about the sections down below. So is that that this this study had in this particular case like I guess five different parts?

26:43 Um yes exactly. So it it did have five different parts. Um so uh the section one was introduction the section two was on boarding the section three was about you know creating a like a new server and then you know discovering like a gaming app right. So so actually this is uh interesting. So if I've got right the center column here and this is live so I may be have it wrong but um uh it's telling me here's a summary of what happened in section 4 for this particular participant. Yes. Absolutely.

27:16 Absolutely. So it tells you the overview of uh the uh the findings like in that particular section and the usability score in that particular section. Um right uh and then you can see all the themes um and the quotes would be like mapped out to those sections. But this is you know on on a user level. What if you want to sort of like a more holistic summary on um uh on on the entire study as well. So in that case it uh would give you a sort of you know like a comparator and an overview on like how many participant felt exactly which painoint. So for example um you know post signup interface was slightly overwhelming and four users uh faced that problem and you can see the quotes and which users felt that and you can simply click here and and go onto that particular section on why they felt um it was pretty challenging for them right um um so this is the qualitative analysis overview. Uh the quantitative analysis is something that would give you like the the click through rates and and if there are any misclicks. Uh how easy it was for someone to complete the signup process versus how easy it was to someone to sort of you know create a server, right? And you would also uh have the discussion summary as well which is downloadable. You can just simply download this have it in a sheet which would give you all the quotes and the and the timestamps also the downloadable links of the um uh the reels as well. So these columns are something that the AI created itself uh based on the research objective as well as uh the particular findings that the AI came through uh during um uh during the analysis part and um just uh oh sorry that that was interesting. So I guess um what I was seeing was there might be like three bullet points and there was a play button. Um I guess I wondered if um uh that would logically Yeah. So, uh, let's just take the one on the upper left here. I guess there's about five different things. So, I'm anticipating that that, um, the play would then show me the the quotes or the items that are relevant to those. Um, absolutely. Okay.

29:37 Yes. And this is basically the clips for the onboarding flow for this user. And uh it would give you a summary on like whether uh the signup was how how the signup was like whether any confusions uh any any feedback that the user gave um and then what was the overall rating of the um of the thing. And if I I want you showed us but I just want to make sure I've got it. So um uh you I'm seeing three users right now or three test participants. Um if I wanted the sort of overarching findings from the onboarding flow, how might I get that?

30:15 Um so right now we uh have like a user level finding for the onboarding flow. The overall qualitative analysis of u the entire research objective all flows included would be something that you can find here. Got it. Um it's interesting feedback. Uh what if you want to sort of you know summarize everything but just for that flow. Uh something to think about. Yeah. Okay. Got it. So so the qualitative is the overarching um highle findings. The quantitative was the um sort of success rates at at different tasks and then um the question by question is the third of your tabs. Absolutely. Um I I would also like to share one more thing as well.

30:59 Please go ahead. Yeah. So the quantitative aspects would cover the completion rates, time on test, mis clicks, usability score and the screen level analysis as well, right? What if you want to sort of you know go through each of the screen, how much time did the user spend on each screen and the usability score and the misclicks that that happened for those screens, right? you would be able to see the quantitative aspects in that regards as well which is purely from the interaction on the prototype or the onscreen interaction uh cases. Um yeah uh yeah just want to sort of you know like uh cover the whole so so there's a lot um to do with prototyping or um having some sort of usability test that we can get a lot of information from. If it's a prototype, you can get uh quantitative um data as well. Uh which is purely interaction data, right? Um yeah, very cool. Um well, it's very comprehensive.

32:00 Um oh, you know, the last question I had is we we looked at one study. Um is userology designed primarily to like focus on sort of study by study or there in some cases um folks have something that helps to sort of bring together findings from say three studies. Um so right now the uh you're talking about the analysis right the analysis. Yeah. So like yeah for example if there were um what are all the issues to do with um signup and we had say three different um you know uh research studies that we had completed.

32:33 Yeah, that's something that is uh upcoming where uh we would be gathering all the findings from you know um like 20 different studies that the org have conducted in an year and we want specific insights from like multiple studies and gather quotes from you know like uh users from like multiple personas and you know like being being yeah yeah no this is very extensive already so I'm not asking I shouldn't ask her too much but I had I was just curious this to see if there was there was that sort of perspective. So this is this is plenty to keep us going. Great.

33:08 Is there anything else or is that sort of a the broad summary of what you want to show? And the one last thing is the reports. We have seen that uh a lot of folks uh spend enormous amount of time in you know making insights presentable which is something that's important and and but but but it it creates a lot of delay in having the insights in hand to sharing it with the stakeholder holders. Right. So we created this reports where it would create a PDF uh which would contain like an executive summary uh participant background summary key findings and the quotes right which you can simply download in PDF or XLS and and then share it via email. You don't have to spend time in you know gathering all these uh things manually and put it into like a sort of fancy presentation.

33:57 So um actually uh it's an interesting question. So um do you see more folks using you know who who are sort of the the product manager or the designer maybe the non-ressearcher um using this kind of report or are they diving into the sort of detailed view that that you were showing us earlier? So we have seen that uh the product managers who are let's say responsible for like one pod they might they might want to go deeper into uh the findings even see the recordings individually by themsel as well. uh but for let us say someone who is leading like let's say five pots at a time like products they would want a summary uh which they can consume in let us say one hour and take a call and maybe change a few things on on their quarterly road map and then yeah very cool okay well thank you for showing us this all it's it's a lot to take in so I'm I'm glad that we recorded it um cool well um you know what I wanted to take a quick step back so thank first of Well, thank you for doing that. Um, and it it shows, you know, how much you and your team are working to make this really extensive and and that takes a lot of work and um I don't know there are challenges to starting up a company and I think you've done that more than once but so I'm curious to see what inspired you to create this product and for this field. Yeah. So uh both I think for like all uh the three co-founders me uh Shivam and Harshad uh were really passionate about you know understanding deeply um like you know understanding users uh at at at the deepest level and uh you know taking the calls uh right from there. So we wanted to sort of uh like uh built the uh company with that foundation in mind.

35:48 That's where we like stumbled upon this problem statement where both me and Shivam uh who is my co-founder uh used to face a lot of challenges on conducting our own research uh and then since AI came into the picture it simplified a lot of things that's where uh we felt that hey this is the right time for us to sort of you know build uh a company around uh this problem itself where we have all been passionate about this problem uh and then I I'm sure like a lot of PMs and PMs have been passionate about this thing. I I used to be me and Shom used to be uh PMs. Uh so this is something that's like really really close to our hearts. Got it. Um well you know from where you started is there anything like a achievement or milestone that that you're particularly proud of that you made made work in userology?

36:37 So the impact that we uh created with a couple of uh customers who previously were not able to like do their own research. Now with this tool since it it became you know uh it it like removed all the friction points and and doing research and you know seeing them u like being empathetic to the user being able to understand you know like uncover insights which they were not able to do it before is is the the biggest milestone. Uh we have seen previously that teams um with like you know let us say like 30 designers right but only two designers doing research uh with something like this we have seen that like you know 25 plus people are not just report viewers but also like creators of of the study. So which is which is an exciting thing to um you know witness uh in in the driver's seat.

37:32 Absolutely. Um well you know the other thing for us UX researchers too is um there may have been situations where just no research was done. So it might not be necessarily that that you know oh they won't be asking us to do any work. It's rather that you can expand and and say all these things that were historically off the table for research could now be put on the table for research. So I think it's a can be a really positive thing. Um well I I wanted to turn to your um future focus.

38:02 So, um I guess I'd love to hear, you know, if there are things you can publicly disclose, but how how you see um userology evolving over the next while and um also just for product people and researchers and so on, how do you see this um what um just the the use of research um sort of evolving over the next while? So, who might be doing it? How would it be done? and and so I know those are big questions but maybe you can you can tell me a little bit about how you see your product evolving and how you see this enterprise of research changing.

38:38 So yeah on on the product side so there are u some interesting things we are working on um something like you know what what if you can chat with your insights and you can like create a sort of a custom report right um I I think doveetail really we since we have been like really working on this we also saw dovetail launching their magic insights feature something like that we have been like really excited about um uh we've also um been working on something which would you know um let you chat with your interview guide as well like you know so that you don't have to really spend a lot of time in thinking about the conversational flow. What if you want to sort of you know give a prompt and it would create recreate the entire uh guide uh uh themselves. For example, if you want to sort of you know conduct uh live product research but you also want to conduct prototype testing and then you also want to conduct discovery research all in one session, right? uh you can simply like type it as a prompt and it would recreate the entire guide based on what you just typed out. Uh on the reports and repositories we have been like experimenting with uh you know like aski features for um study level and also I mentioned about the the multi-study analysis as well. So that's been uh really um exciting for us in terms of product. Uh would also want to understand the second question a little better so that I can Oh sure. Yeah. I was just asking how you see the just the whole program of research changing. So like do we still need UX researchers? Um will we be asking different questions because of the capabilities of tools like this? Um how do you see us? You know historically we'd go into a room with glass on one side and watch someone work and and you know hit record and it's it's transformed to something like this. And so from here a year from now or two years from now how might we be doing research?

40:33 I don't see a place where we can work without the research team. Um as it's as plain and simple we cannot really uh no matter how smart they are becomes. Um the uh the strategic fundamental research is something that the research team will always do. The thing that I am like very and then we are like very optimistic about is the scope of research being extended and more people being able to see research and the value in research that increases our sort of you know like hunger to get the strategic and the you know macro insights. Um since since evaluative research have been you know like already I'm I'm just talking about like few years down the line and evaluative research is something that uh have been like delegated and people have been like doing their own research you have like more time to explore new markets new business opportunities and that's where uh the research teams would would come in and and and help us discover what's next for us as humanity right if you talk about a business yes it's it's it's pretty simple you discover new markets new problems statement, new personas.

41:39 But but if you collectively see the impact of all the research scope being increased, you can see that you know like the pace at which uh businesses would uncover like new problems to solve that would like increase uh the um you know u like it it would like move us forward collectively. Right. So if I'm right, what I'm hearing you say is we need to have something. We need to do this and we need to learn to move faster because someone else will be moving faster with tools like this. Yes.

42:14 Okay. Fair. Um well, you know, I'm sure that there are plenty of folks that found this intriguing. So if they wanted to give Userology a try, maybe you can tell us how they they might get started if who they reach out to or how that works. Uh it's pretty simple actually. We have uh the product uh public. So you go on userlogy.com uh you u share your email uh and uh and then you can you will be able to create your account. Uh that's where you also get like five credits as well. So you can like create one research project for free see how it's uh working with an AI UX research agent. Um yeah so it's it's uh like the first research project is free. just go on the landing page, sign up and create your project. And and meanwhile, if you are, you know, curious to know more about the product or if you need help creating, always feel free to reach out to me on the uh userlogy.co.

43:14 Very cool. Well, um well, you know what? Thank you so much for showing us Userology, for all the hard work you put into that to make it really impressive. And uh what I'll do is I'll I'll just close this off, but I I really really thank you, Shay, for everything and and showing us um userology. So So everyone, that's that's all for today. Thank you so much for tuning in and keeping up with the latest AI for UX research. And of course, subscribe if you enjoyed this and tell us what other um features you're interested in next.

43:43 And just wishing you brilliant insights with AI.