Stick the landing: experiments in breathing life into the last mile of UXR

Stick the landing experiments and breathing life into last mile of UXR. It's gonna be very very cool. I promise. And our speaker is Asha Toulmin.

 She's very cool. She's an experienced UX researcher who's worked at leading organizations like Google and CNN. Maybe you've heard of those two. Currently at Alyra Health, Asha focuses on connecting people to mental, connecting people to mental health resources through effective US re UX research.

 Super important today's day and age. With passion for storytelling and innovative research methods, Asha brings valuable insights into product development processes.

 Let's hear it for Asha Toulmin, everybody.

 Hi, guys. I know we're here.

 Thank you.

 Hi, everybody. I am so thrilled to be here. Thank you for having me. And we're gonna talk today about how to breathe life into the last mile of your process.

 And I know the title was a little different on the agenda, but I promise you we'll cover all the buzzwords like AI, groundbreaking, tactical, all those things in my talk today. So Mike kindly introduced me. Thank you. And I hope some of you will also introduce yourselves to me at the end.

 I would love to chat with with anyone here. But my name is Asha, and I'm part of the small but mighty UX research team at Lyra Health. If you're not familiar with us, Lyra is really on a mission to connect people to life changing mental health support. What does that mean?

 We work with employers to figure out what kinds of mental health resources can they offer their employees. So that could be meditations, therapy sessions, crisis support, kind of runs the gamut.

 And just to bring you into my world a little bit because, spoiler alert, you will be joining the UX research team at Lyra today.

 The kinds of questions, the things that my team is focused on are really run a gamut of different types of stakeholders. So we're answering questions for mental health seekers, like what kinds of topics do they want support with, what fears do they have about getting therapy, things like that.

 We also do work with clinicians, so therapists, coaches, folks like that, how we can make their processes better, solve their problems.

 And then we also work with employers, benefits buyers to figure out what kind of support they wanna offer employees, who do they care about helping most.

 So now that you've kind of heard a little bit of the context, I think that might be similar for some of you, some of the similar questions or types of stakeholders or setup, and very different for some of you as well. But I would be willing to bet that, you know, if you you think about a recent project that you've done, beginning, middle, and end, we actually have probably a similar process or a similar map for how we do our research work.

 And I like to think about this as a graph of knowledge over time, so we're always moving up into the right.

 But it really starts off with planning. So we think we know some stuff. Right? Or we think we know something, but we wanna learn a little bit more. It's exercise in learning. Starts off with the planning.

 Then we get to research execution where we we're doing what we said we were gonna do, and I like the little loop de loop here. Some of you may experience this where we're like, oh, actually, we don't know anything that we thought we knew, and now we learn some new stuff.

 But, eventually, you get to analysis. This is my favorite part of the process. It's kind of when things, like, click into focus, and you're like, oh, yeah. Okay. I do have an answer to this question.

 And then you get to results. So you go through this whole process. You plan. You involve your stakeholders.

 You learn things. You create findings. You create a report. You share the report. And then I'm a researcher. I could be quiet for a while, but I I will spare you.

 There's this kind of gray area.

 Right? Like, now what? This ambiguity of, like, okay. My stakeholders sat in my meeting. They heard what I had to say, so I'm done. Right?

 This is what I define as this last mile of research, and it is such a critical phase to what we do because of this ambiguity, because of this kind of murkiness.

 And I have seen tragedies play out, Talented researchers who I know who do meticulous, rigorous, business critical work just to get to the end, and then nothing happens with their work. Not it go it doesn't really go anywhere. I mean, it goes to a place where people are like, oh, yeah. That was good work, and then nothing.

 And so that's what we're gonna talk about today is just really thinking about this last mile.

 As our roles change and evolve as researchers, we need to be at the seat at the table even more. We need to prove our impact, and I think this is a really particular phase where it's important that we're doing that. So I'd like to kind of rephrase this as an opportunity.

 And my challenge to you today is this opportunity of how do you create these insights or these findings that really stick with your stakeholders, that kind of breakthrough.

 So I'm sure lots of people here love a framework. I love a little framework too.

 So here's one that I particularly enjoy. It's from this book called Made to Stick. Hands up if you've read or heard of this book.

 Okay. Well, I I just added you and myself because this book came out seventeen years ago, which makes me feel absolutely ancient.

 But I think it's an enduring kind of framework that is still true to this day.

 And so I'm gonna talk you through this.

 What do we mean by something that sticks?

 There's kind of six key principles here. The first one is simplicity. So I'm just gonna touch on each of these.

 People sometimes think simple means shorter. That's not what simplicity means. It can definitely help, but simplicity is all about have you stripped back what you're trying to say to its core?

 Is this the essential part of what you're trying to convey?

 The second thing is unexpectedness.

 So, you know, maybe don't rush out and buy a gorilla suit to deliver your research report in, But unexpectedness is really important. It basically creates this investment from your stakeholders. They they have this tension, this suspense that they wanna follow through on. And I think, you know, this can often be something that in UX research, you kinda present your findings and your stakeholders go like, yeah. Makes sense.

 I knew that. And there's pros to doing that type of research as well, but how can you convey what you've learned in a way that fosters unexpectedness?

 The third thing is concreteness.

 So, again, it can be really easy to kind of frame things as high level, to use jargon in what you're talking about. And concreteness is basically how can you make this real, give people a real example, put this in actual terms of what is happening. Because another thing that can happen, I'm sure no one here has experienced this, is that if you're not concrete, people will interpret your research findings however they want, or two different stakeholders will be like, great. This means I get to do the thing I wanna do. You're not speaking the same language. You have to be concrete.

 The next one is credibility. And what's great is that if you're a researcher, you got this in spades already.

 You know? Like, the work that we do by its nature means that the learnings, the insights that we're putting forth are credible. So this is something that, you know, it's just about how you set up your work, how you're sharing what you've learned, the methodology, the thinking is already something that we actually have when we share our ideas.

 The fifth one can sometimes be a little controversial, emotions, the touchy feely stuff, so to speak.

 I think sometimes in our work, this gets cast as, like, anecdata or, like, the fluff.

 But, actually, as human beings, we are wired to care more about people than about ideas.

 And so if you have something that's based on data that you're like, this thing, I want you to recognize this thing. Like, thinking about how to bring a relevant emotion or a relevant story in is really important.

 And then speaking of stories, the last part of their framework is stories, which is kinda funny. It's like a catchall for basically everything above. Because as you can imagine, with a story, you can give concrete examples, you can invoke emotions, you can provoke unexpectedness.

 And I personally love using stories because I think more so than anything else, it gets your stakeholders to inhabit your world. So they actually have to get in there, understand what's happening, and can can kind of fill in the blanks with their own context.

 So I think, you know, if you take nothing else away from my talk today, I encourage you to think about this quote.

 So much of our life is repetition. We make research plans. We do research. We present on the research.

 We have meetings. We get emails. We get Slack messages. We get Microsoft Teams messages. You know, like, most of the time, that consistency is a really good thing, but there's so much for our stakeholders to pay attention to.

 We have to break a pattern. We have to break the pattern in order to stand out.

 So you might be thinking so far, wow, Asha, amazing talk. But I could have just bought this book and read it.

 What's why and and how is this relevant? So what I wanna do now is invite you, like I mentioned, to join the Lyra UX research team, and I'm gonna walk you through how we actually applied this in real life to a real study.

 So, maybe don't update your LinkedIn yet, but you are now on the research team here at Lyra.

 And, here's the here's the setting. Here's what's going on. So at Lyra, we offer multiple different types of therapy. Virtual sessions, so someone can join a video call. We have people join in their car, for example, to do a session with a therapist. And we also offer in person therapy, so you can go to someone's office and talk to them there. And our chief operating officer was looking at the data and noticed that, you know, in terms of that share, people were really trending more towards in person therapy.

 And for a variety of reasons, that's something that we just kind of wanted to look into, kind of think about in terms of our goals.

 Meanwhile, our internal teams that kind of run these programs, they're like, in person therapy rules, but virtual therapy also rules. Like, people who enroll in these programs, they see great outcomes. Like, there's no problem here. We don't need to look into this.

 Right? And maybe some of you have also heard the same thing. There's no problem here. We don't need to look into this.

 But you are part of the fearsome UX research team at Lyra now. And so one of the things that we know is that if people don't ever even consider booking a virtual care appointment, they will never realize those benefits. They will never have those great clinical outcomes. Right?

 So this was something that our team was like, okay. We're gonna look into this.

 So we do the planning. We do the race research execution like I talked about, about, the loop de loop. We do a series of interviews, and we use our amazing platform user testing to do some concept testing too, to think about what could move people from being skeptical to being interested in virtual therapy.

 So let's get ready as a team to synthesize these findings and think about how to share them.

 But there is a trap. I didn't mention this. I fooled you all.

 At Lyra, we have some interesting constraints in that we deal with people's private health information. So I think a common way that people in our craft tell stories today is like the video reel. Right? You make a reel of people talking about their experiences.

 You show it to stakeholders. That's not possible for us. We can't show people's faces. That's private health information.

 So you and I, we're gonna have to get a little extra creative today in how we kind of do those emotions and stories.

 So here's some of the data that's coming in.

 These are just kind of things that we're learning as we go through.

 So a couple of things I'll spotlight here. You know, one of the things that we're learning is that people, you know, because of COVID and more experiences virtually, they're like, whenever I do a virtual care session, not with Lyra, with, like, maybe a doctor or someone else, I always feel like I just get low quality care.

 So people just have this perception. Right? Like, this is not gonna be high quality.

 We've got some fancy stats. You know? Sixteen percent of our twenty five participants ultimately at the end said that they would consider virtual care. Right? That's a pretty low percentage. Just could should be a little bit concerning to us as a business. Right?

 And there's a couple other findings there too, right, about, you know, just explaining a little bit more about people's prior experiences, another potential theme of why this is happening. And, like, hopefully, you know, something like this, something similar looks familiar to you, gets shared out in a research report, a slide like this.

 Not sticking for me. It's not meeting the stick bar.

 So how could we, you know, think about provoking emotions, con concreteness. Like, what does this actually mean when I read these words?

 So maybe we try a story.

 You, because you're a fantastic researcher, you are looking through the quotes and you find this.

 So I want you to sit with this for a moment.

 This is a quote from a participant, not about Lyra, but about another online, therapy platform. I've heard stories from people saying they could literally see in the reflection of their therapist's glasses, they were playing like Sudoku or doing a crossword during a session.

 That sucks y'all.

 Like, if you sit in this moment and think about it, that is just, like, terrible. You can imagine how someone feels rejected, that this could convince them, even though they actually weren't even the one in there, it was their friend, right, to never do this kinda thing, to not trust it.

 So already, this is kind of, like, hopefully, an example from the previous slide. It's a little bit stickier. Right? It's raising that sticky bar. But this is still a finding. It's still a quote on a slide.

 How how are we going to kind of elevate this even further? And so our challenge as a team and, hopefully, I think some of these might feel a little bit familiar to some of you, or we really have to take these learnings, the quote, the stats, things like that, and figure out how to elevate them with these challenges in mind. So the first thing that we're always trying to do as a group, how do we improve the member experience ultimately at the heart of what we're trying to do? How are we gonna make this better for people who are very scared or not interested in this because they think it's something else?

 Secondly, you know, we in this scenario, we kinda have to do more because we have a group of stakeholders who are like, there is no problem. There's nothing wrong. Yes. Other people's virtual therapy is not good, but ours is amazing.

 And everyone should already know that already. Right? So we have to do something extra to break through their perceptions to make this stick. And then the last thing, as I mentioned, you know, as in terms of our process, how are we gonna do this in a way that's privacy compliant, that's trauma informed, that's really honoring the information that our members are giving us?

 So how are we gonna do it, guys?

 I mean, come talk to me, actually. I would love everyone's individual thoughts on this, but this is how we did it at Lyra. We really looked at, experimenting.

 And so I highly encourage you to think about this, for your teams. And maybe it's not in this area of making insights stick. Maybe there's something else you can do in this last mile or some other part of your process. But the beginning of the year, our research team, did a retro. And we talked about, like, what's working, what's not working. One of the things we said was, okay. Twenty twenty four is the year that we are going to experiment with emotional storytelling.

 We are going to experiment and make a commitment to trying to shake things up. And there's two things that I think work well about this. One is by talking about it as a group, you sort of have this commitment to each other, and you create this space for failure. Right?

 We're trying this out. We're just attempting it. I think also giving yourself a long timeline. Right?

 All of twenty twenty four. Like, that gives us enough time to make changes, to try things out, and then adapt them and try them differently.

 And then I think also, you know, telling other teams about it. Right? Like, our wider design team. We were like, hey. Just so you know, this is something you're gonna see from us this year. And, like, if you have thoughts, we welcome them. You know, just setting that expectation.

 And then the last thing is that by opening this up as a topic, a commitment, we also started to think about, okay, if we're experimenting, how could we experiment with, like, the tools that we're using?

 So, you know, no one's probably heard of, like, AI at this point, but it's a great tool, turns out, and it's a really great, you'll see kind of how we used it actually to tell stories, as almost our own creative agency in this process.

 Alright. So I'm gonna show you kind of the experiments that we went through. And as part of this, you're gonna get to see some failures.

 Woo hoo. So fun. These are bad.

 So this first experiment I'm gonna talk about is, you know, we had that really great quote.

 And we were like, okay. We have this really great quote, but we can't show a video of this person saying that. And that might connect. So my first thought was, okay. What if we just, like, make this a person saying this quote?

 So this is, like, a five minute experiment. I hopped on a Zoom call. I added one of those weird, like, cartoon avatars. And I was like, I'm gonna say the quote like I'm the participant, and I'm recorded. And let's just, like, see if this resonates.

 We wanted to personify the participant and meet our privacy requirements.

 So let's see how it turned out.

 I've heard stories from people saying that they could literally see in the reflection of their therapist's glasses that they were playing like Sudoku or doing a crossword.

 So I think it's a concern that, like, both myself and the therapist wouldn't wouldn't be fully invested in the session.

 If it's virtual, it's easy to get distracted and work on other things.

 Okay. So I know what you're thinking. Amazing voice work. Thank you.

 But for me, this was a fail. This was like a test tube blew up in my face kind of fail.

 But there was, like, really valuable stuff I could learn from it. So what was important was for us to kinda go back to that stickiness framework as we were kinda going through these different examples. So what's not working for me here is, like, there's no there's no emotion here. Right?

 This is, like, taking me kind of even farther away from the person and the participant. I feel like it's it's, like, not really adding to the actually. It's almost making it, like, more vague because I am so distracted by, like, this intermediary of what's going on. So I was like, okay.

 This is this is not working, and I feel like I'm focusing so much on this fig face. And I will say for your context, for your, you know, story you're trying to tell or point you're trying to make, there is a world in which this is gonna work for somebody, but wasn't working for us.

 So the second experiment, I thought, okay. What if we just use more sophisticated generative AI?

 So this is, using the tool Midjourney.

 I worked with our, creative team just to, like, play around in there a little bit.

 This took maybe more like ten minutes to make.

 And this blows my mind, but this woman is not real. She has an AI generated face.

 So we made an AI generated face, and we just synced tried to see, like, what would it look like to sync up this face with audio?

 Maybe she could really be the one to deliver the message in a way that would stick.

 So here's just some, playing around here, our second experiment.

 Hi, Asha. Thank you for letting me try out Lyra. This is an experiment testing AI voice overs on an AI generated face. Let's see how it does.

 I'm not sure I would use that feature often.

 Okay. So a little editorializing there from our, UX UX creative partner.

 But I think, this was also something that we were like, it's not really working. It's just not really working.

 And looking back at our framework again, I think for this, it was like, almost like the unexpectedness was too high. Right? Like, everyone was like, woah. This is a fake woman and she's talking.

 We can do that now. Like, it's memorable, but not really in the way that we want. Right? We really want the story to shine.

 And, again, this could be another great method for another story out there. Right? Like, maybe it's like showing a scenario play out instead of just this woman's face, but just wasn't working.

 So at this point, we were like, hey. We've done a couple of things to try this out. Maybe it's maybe we just pivot a little bit. And I think what was really illuminating for our team at this point in the process was understanding, like, what was the core of what we were trying to share. And what we realized was what was so powerful about that quote was actually the story of what was happening, what the therapist was doing, not the person sharing the quote.

 So with that in mind, we were like, okay. So we need to just figure out a way to share this story.

 And so I led this brainstorm with some of our wider design team, and I encourage you to get them involved if you have folks who are eager or interested, where we came up with all these different options, like, you know, doing a podcast, make a brochure, do some storyboards. My personal favorite, Beanie Babies. Like, we did not have the budget for Beanie Babies. But, ultimately, we came up with this idea just through this brainstorm for tarot cards.

 And if you are not familiar with tarot cards, think of it like a deck of playing cards, and each card is unique. They have kind of an individual archetype or a principle on each one.

 So we were like, okay. This can just be our next experiment. Let's just see how it goes. And I wanna stress that, like, with some of the AI tools that we have now, these experiments, like, can actually be quite fast.

 So this was our third experiment, and this took me five minutes to make. Right? These were our tarot cards. The one in the middle is the one that is really about that core story I had shared.

 We made a couple more. We were kind of trying to trying to think through some different things.

 And I think what was so great about this for our purposes was, like I said, it only took a few minutes to make, and we could use a prompt that didn't put any of our members' private information at risk. So I think the prompt that I put in for this was, blue tarot card illustration of a woman wearing glasses doing a Sudoku that says the word distracted.

 No no PHI involved there. You know?

 And I think you can tinker with it too. Right? This wasn't, like, the first thing that I came up with, but I was able to refine it and get to a place like this.

 And so if we go back to the framework that we were looking at over time, I think there's a few things that works for us really well about this particular finding and then this format. So thinking about simplicity. Right? It's a pretty simple way to, like, focus your attention. All you have to do is sort of take in an image, and there's one focal point literally of what you're looking at.

 The second thing, unexpectedness.

 Unless you work at, like, the coolest company ever, you're probably not doing tarot cards, like, in business meetings all the time. Right? So it was something that was kind of a new way different, breaking through all those emails, those Slacks, things like that.

 Concreteness.

 It gave a very real example of what we were talking about when we talk about distracted or low quality care.

 Credibility. Like, we didn't just say, here's a tarot card. No other context needed. Right? We had sort of we said, like, we did this study. Here's a link to more details, our methodology, where it came from. Here's something you really need to pay attention to that's come out of this.

 Emotions. I do think, like, there is kind of this interesting emotional component to this artifact. Right? Like, she's sitting across from you.

 You're almost, like, put in this place where you're trying to impress her or, like, I don't know. Like, there's some kind of emotional connection there. And then stories. So you're able to kind of see and fill in the blanks potentially of what's happening here.

 So this format particularly works really well, but I I wanna stress, like, I do think that thinking about this framework for anything that you're producing, is is something that, like, can really elevate how you're delivering your message in that last mile.

 So we had come up with this third experiment.

 Amazing.

 We're done. Right?

 No. You guys are too smart. So alright. So I mentioned experimentation, and and a really key part, obviously, of experimentation is measuring results. What actually happened?

 So it is not enough for you internally to think this is a good report. These are great findings, in my opinion.

 I think, you know, we're being asked to do more and more as researchers. We wanna be partners. We wanna be able to see at the table. It's so critical to ask for feedback on if what you're doing matches what people you know, what is actually resonating with people. Right? There's this really great quote that's like, if you want money, ask or if you want advice, ask for money. If you want money, ask for advice.

 And I think it really applies here as researchers. If you want someone to invest in you, ask them for their advice. Ask for feedback.

 I know that, like, sometimes there's an interesting power dynamic where as a researcher, you're really trying to you're like, please do the thing that I want you to do. And so you don't wanna add another request on top of that. Right? You don't wanna seem like you're asking for too much.

 But I've I strongly feel like if you ask someone for feedback, they're automatically then on your team. They're invested. They're part of if what you do is successful or not. So, you know, feedback can be, also intimidating.

 Right? Like, a lot of times, it it turns into something like, so do you have any feedback for me on that report out?

 No. I would avoid that. Use your skills as researchers. Our whole job is thinking about how to get thoughtful feedback on specific things from people. So how can you do that with your stakeholders? Here's an example on the right hand side of at the end of this study, I sent a message out on you know, we use Slack, but you could think about it any medium, and said, we just did this study.

 There's two different ways that I'm thinking about sharing this out.

 So please, like, leave a comment.

 Like, leave an emoji reaction on the one you prefer, and let me know why if you have a preference.

 And, like, we had our chief operating officer leaving a little emoji reaction on one of them. Took, like, maybe ten seconds of her time, but that's such valuable feedback for us. Right? And it actually spawned this whole you can see some of the comments below. It spawned a whole conversation where some of our stakeholders were like, a third option actually would be really fantastic, like, if you could do this.

 So I really encourage you to think about how you could potentially architect that in. And so giving people a choice and asking for a reaction is one way, but using your skills as a research researcher, thinking about other questions, and I'm happy to share other thoughts I have on this. Like, how can you just, like, get the feedback you're looking for in an easy way to give it?

 And then, of course, it's not listed here, but the other way of measuring your results is, are people taking action on your findings? And so with this study, it's really exciting because Lyra is doing a few things now to make it easier to change that perception of people to get into virtual care. So also a really important way to measure what you're doing.

 Okay. So how do we stick the landing? How can you all stick the landing as you go from here? Like I said, we used a framework. I personally really like the made to stick one, but there's so many different ones out there, things that will work well for you, your context.

 We experimented. We tried things, and we failed. And we were quick about it, and we moved on.

 And the other thing that that I should note is we use real data. So talk to your legal team before you put anything in an AI tool. What I mean by real data is that we didn't say like, oh, tarot cards. Great. Let's try that and then retrofit it onto whatever project. Right? We started with, this is the thing that people don't seem to understand that we need to, like, breakthrough with them on that's really important for them to grok from this work.

 The third is evaluating your outcomes as you go. Right? So instead of me just saying, like, this AI face is creepy, I could be like, what about this is not working? Right? Like, it's putting too much focus on the speaker. This focus should be on the story, and then you can pivot kind of adjust better.

 And then lastly, like I said, soliciting feedback.

 Yeah. Can't stress enough.

 Pay attention to your stakeholders. Treat them like research participants. Another little tip that I do sometimes with my stakeholders is I just like, if I'm in meetings, I just write down, like, what questions did my head PM ask in that meeting? That's a great way of just being like, oh, Emily obviously really cares about this because she's asked this question in the same, like, meeting, like, three times this week.

 Okay. So we live in a world, endless messages. Some of you are probably responding to messages right now. You know?

 Emails. We wake up. We go to bed. We read more reports. We do more research, all this stuff.

 Break the pattern.

 I'm so excited for you to try it out. Please keep me in the loop if you would ever wanna talk through this stuff.

 Try it out and let me know how it goes. And thanks so much for having me.

 Happy to take any questions.

 So we got a just a few minutes left for some questions. If anyone's got a question, just raise your hand. I'll bring you the microphone.

 Who wants to be first? Oh, she raised her hand, but I bet it's not for a question. She doesn't even know. I'm looking at her.

 Alright. Here we go.

 Thank you.

 Yeah. So my question is, what would you recommend if you don't have all this time to like, you iterated several times trying to tell this one story. But, in my organization, like, a lot of times we need really quick results, like, before the end of the sprint, like, a week or something. So do you have any feedback on how you can try to make things resonate, and break what did you say? Break the Break the pattern. Break the pattern. Yeah.

 Yes. I have a couple of thoughts on this. One is I think that, I think that number one, like, if you can just even if well, I I should say some of these experiments, even though we did it over time on the same story, take, like, five minutes, right, like, in itself. So what I would recommend is if you're doing iterative sprints like that, like, even just saying, like, this month, we're gonna try one thing.

 And if it doesn't work for that study, that's fine. But, hopefully, maybe in the next month, something will click a little bit better. In the next month after that, you'll start learning over time. And I think the most important thing is then, like, eventually, you will get to something where you're like, hey.

 For this study, like, this seemed to really work. Like, this actually is working. So even if in the short term, you're not seeing an immediate, like, impact, I think in the longer term, it means that you'll get there faster.

 The other thing I would say too is, like, I think that is especially where, like, finding, like, quick ways to get feedback is also really valuable. Like, is it like some teams, for example, have, like, a quick, like, retro of the previous two weeks? Like, can you say, like, hey. Can we spend five minutes in the retro just being, like, post it notes, like, liked, disliked, like, would change about the research that we ran the last cycle? Like or in your research report out, leaving, like, five minutes at the end to be like, hey. So just wanna check, like, what surprised people about this study?

 Or, like, what's one thing that you're gonna do from this study? That's bold. But, like, there's no reason why you can't just have, like, five minutes and say, like, write on Post its, like, what's one thing that's changed about what you're thinking or whatever.

 So those are a couple of other ways you can kind of get in there.

 I just wanted to share that along those lines, we my PM sends out a post study survey about the information that we collect, and it has been really helping me. I'm a one person UX team, so I don't have time to constantly be, like, iterating, especially but the surveys have been really, really helping. I love that.

 Awesome. And we're gonna we're gonna take one last question. Here we go.

 Thanks, Sasha.

 I loved your concept of the tarot cards, and I'm wondering if you can speak a little bit more to the promotion and distribution of that. Like, how did it land with your stakeholders?

 Yes. So, basically, there were a few different ways that we promoted them. I think, like, embedding them in the report was just, like, the first step to be introduced to them. And then we also just, like, shared them standalone on, like, Slack, especially with executives.

 That's, like, a great way to get in front of them. I think, like, this is one of those things too where, like, we don't have all the time in the world also. I there's, like, things that we could do in the future with them that we've talked about. Like, for every study, do we just create one?

 And then when someone new joins Lyra, we send them a pack of those cards. Like, I think in the future, there's a lot of ways you could go for it. But in the short term, it was basically, like, in the report and then, like, in one off emails or messages or other things like that. And the PMs were like, woah.

 They were like, wow. That's cool. That was kinda.

 Excellent. So this brings us to the end of the breakout sessions for the Human Insight Summit twenty twenty four. Big round of applause for Asha again, everybody.