How to talk to customers

Today we're going to have a discussion with Alex and Kurt and myself about how to talk to customers. Practical Guide to Customer Interviews. In the webinar, we've got, we're going to be talking a little bit about the challenges that we see with customer interviews. We're going to have Kurt talk a little bit more about customer profile interviews specifically. And then we're also going to have Alex talking about other visual interview tech techniques. And we're just going to start by saying, why? Why are we even talking about this? Why are we talking about testing and interviews? A lot of you have seen this many times, but I'm sure you all can understand the process can feel very messy. We know that going from an idea to scalable profits looks a little bit like this, but it doesn't have to. And at Strategizer, we have sprints that you'll see in our innovation program and also in our. In our other sprints that we do where we have three phases, discovery, validation, and acceleration. And in this underpinning, all of this is really testing with our customers and understanding what their needs are and gaining more evidence and confidence around our business ideas as we go. And with that testing, also reducing our uncertainty and risk. And that's sort of our goal, is to do those things that we can progress towards a business idea. What I'd like to do is just go into some of those challenges that we see with our customers and our clients and some of the experience that we've had ourselves in innovation. The first one is not getting out of the building. That's one of the first challenges, and that can be because of bureaucracy. It might be that you don't have the leadership support. Feel free to let me know if this resonates with you in the chat or that you're unsure who should be doing the testing, unclear roles and responsibilities, or maybe you just don't have access to the customers. And I think that that's a number one thing that I hear quite a lot. Alex, you are probably the same. Access to the customers can really be a challenge, and it can be around. Oftentimes I've seen and experienced that a particular role owns the voice of the customer, for example, or the sales team are the ones who have access to your end users and they don't want to get things confused. So what we want to aim for is that we have that easy access and we're really clear on who's doing that. Another challenge that we see is limited resources and budget. And what you might see is that There's a person or a group of people who are responsible for the research and testing. And then actually there's quite a big bottleneck and we're not able to move quickly and all sorts of issues can arise from that. And so what we hope to have is that budgets approved ahead of each phase. So you know how much money you have to deal with with your research. And as Alex was saying, if you're doing this properly, it doesn't have to cost a lot of money either. We also are looking at democratizing research. So why not get everybody out there and not just leaving it to a few people or third party agencies as well, which is often the case too. And then having templates and support, and this is maybe the original kind of key. Researchers can spend their time on providing support. Third challenge of getting out of the building is overconfidence in what you know versus analysis paralysis. So I know I've seen a number of cases, bosses or product leaders who respond to who is the customer by saying, well, we've had this customer for 10, 15 years, you know who it is, without really understanding that changing times might change the customer, changing products might require a different customer. And then on the other side of things, having so much information that we have analysis paralysis and not being able to move forward. So what we're hoping to see with that is right tests at the right time, feedback loops, ensuring that you've got an opportunity to act on any testing that you do, not just testing right before you go live, which I've seen quite a lot in a number of organizations, and also visibility of insights so that the right people have access to that as well. And we've got just one thing.

Yeah, just one thing related to what you said about the first one. Right. Not having access. If we stick to that sounds sometimes really. Oh, companies are crazy. And why don't they give everybody access? There were a couple of comments in the, in the chat. It is something you don't necessarily want to just let everybody do. Right. So we're not kind of trying to be sarcastic here. Sometimes there's a legitimate reason, but I don't think the conversations are always happening. Right. So a salesperson legitimately might want to make sure that they're selling what the company already has. Because if you start to show new ideas, they might not buy and they will wait. Something you might never build. Right. So it's not just the salesperson's bonus that is preventing this, but actually legitimate reason. Right. So you really need to have good conversations around this or, and we've made this mistake. You know, we want to learn, we're eager to learn. And then the client asks, like, why the heck, you know, are so many people talking to us? Or so many people are in projects? So we had, we had to learn that you do need to sometimes channel customer conversations, but you can overdo it. Right. So these are sound really simple, but they're not simple challenges sometimes. Right. So they're just not always handled the right way.

Absolutely. Great. And I think that's. That's really important. The. The larger your organization, the more people you have, the more important it is to have those clear roles and responsibilities. Who's doing what, what kind of conversations and how. But at the end of the day, having access to customers, Innovation teams need to ensure they have that. So we've mentioned Steve Blank already, but we've got one of his key sayings that I'm sure everyone's heard a bazillion times. There are no facts in the building, so get the hell out and talk to customers. He's got another one here that I quite like around. Cheating on customer discovery interviews is like cheating in your parachute packing class. So I thought that was great. Quite a good one. Let's not set ourselves up for failure there. Great. So just in the chat, when is the last time you got out of the building and spoke to a customer? If you want to just put something in there for us. Last week. Yesterday. Oh, nice. Yesterday. No, browning. Wow. Today, Yesterday. Brilliant. Great. Two weeks ago. All right, we've got the right people in the call. Perfect. Great. Last month. Perfect. Okay, so I'm going to talk through two more challenges. Very briefly. Kurt's going to talk a little bit more around the solution on these, but the unstructured interviews is another challenge that we know teams have. And some of the questions that you might have is, who should I be talking to? How should I structure the interview, and what question should I focus on now? So that can be a real issue, especially if we've got teams who are not trained researchers. So one more question for you in the chat. How knowledgeable are your teams in designing customer interviews? If you would just want to give it a score of one to ten. One. Not very knowledgeable. Ten. Very knowledgeable. Right. Threes. Lots of threes. Twos, sevens, fives.

I like the honesty. Right. Because we kind of underestimate how. How hard it is to do good customer interviews. Right. So something that I believe automation can help with. Cool. Wow. I. That's not something I would have expected. That we have so many low scores. Wow. Interesting.

Interesting, right?

Yeah.

Great. Okay. And then the third one, the third challenge that we see is extracting insights. And for all of you who've just been out on interviews or talking to customers recently, hopefully you've already figured out how you're going to be doing that. But the questions here might be things like, how do I do this? How do I do this quickly? And then how do I communicate this effectively? And I don't know about all of you, but oftentimes teams get so excited about innovation, teams going off, talking to customers that as soon as they get back, they're bombarded with questions. What are the key insights? What do we need to do next? And there can be that real tension between getting real validated data and insights and confirming everything with actually communicating next steps to folks. So how can we do that quickly? And I think with that we have one more question regarding those. The extracting of insights. Which of the following would you say is most challenging? Is it the process? Is it extracting insights quickly or effective communication to the wider org of those three. Oops. Lots of C's, C's, A's, 1B. Okay, great, perfect. A lot of C's, I would say, from what I can see. And then just one final slide before we move over to Kurt, and that's one from Steve Jobs, which is get closer than ever to your customers. So close, in fact, that you tell them what they need well before they realize it themselves.

And I think, Alex, I'm, I'm super happy you included that because I still get these questions, you know. Yeah, but Steve Jobs never talked to customers. It's actually the contrary. You know, Steve Jobs used to, while Apple was already super successful, hang out at the Apple store in Palo Alto. I'm pretty sure he didn't need to go there, but he was watching people and trying to see how they're, you know, looking at computers and phones. And that is pretty amazing to. To see. Right? So there's these myths that are just not true.

Yeah, yeah.

And then I guess it also highlights the difference between say, and do. So always being. Keeping that in the back of your mind when you're talking to customers and how you're going to match that up with observation and of what's actually happening on the ground.

So I'm going to talk to you guys about customer profile interviews, and we have just found these to be an incredibly effective way in which to gather insights, especially early stage innovation. So let's unpack that a little bit so there are three challenges when it comes to the idea of running customer interviews. That first one, not getting out of the building. So I'm not going to spend much time there on that one. Obviously, if you're running customer profile interviews outside of the building, it's going to solve that problem. But I'm then going to look at these two. So unstructured interviews, and how do customer profile interviews address that? And then also this challenge of the difficulty of extracting insights. So if we look at that first one, the difficulty and the challenge of unstructured interviews, the principle we want to keep in mind is that customer interviews are challenging because they require a structured approach to gather enough data, detect patterns and make informed decisions. We want to be thinking about that end goal. We don't just want to be getting out of the building, talking to customers. We want to use that data to then make informed decisions. And without structures, insights become scattered, making it harder to compare results and act on them effectively. So even you see here already, like comparing results tied to that idea of detecting patterns. So if we were to compare, kind of on a spectrum, unstructured interviews to structured interviews, if you think about the data, what we have seen is when we move in the direction of a structured interview, which we'll look in detail later on to what that actually looks like, it allows that process of analysis at the end, where you can detect those patterns to be much easier. And then with the changing landscape of today, with AI, you can take something like unstructured interviews and use AI to be able to understand and pull out from that unstructured process insights. But we've seen from our experience with AI, and obviously the landscape is always changing when you have a starting point of a more structured approach, it's a force multiplier if you then layer AI on top of that as well. So what does that look like? So we had a team recently and they had an AI idea. And this was a team of five from the public sector. And their leader, his name was George, he wanted to move very fast on this idea. Again, I just mentioned how AI is moving fast, and he wanted to do it. And in many ways you could say he used with his team, a very structured approach. They created and used interview scripts based on the hypos, the hypotheses, the risk, the biggest guesses they were making on their business idea. They reached out to folks, they set up interviews, they ran those interviews. But when it came time to come together to analyze the results of their interviews, and they were looking to start to identify the patterns of the 17 folks they interviewed. That was when it became difficult for them to identify any meaningful patterns. So even with using an interview script, each team member had a very different kind of set of data from the interviews they ran that focused on kind of, they weren't able to cover every question in that script. So for example, one team member, they said, I talked to five people and all five of them had X problem, but they had kind of hyper focused on that part of the script and the others hadn't. So when they looked at it in the broad scheme of things, it was 5 out of 17 because the others hadn't touched on it. And then all of a sudden the conversation became difficult to understand if there was actually a pattern there or if it was just a one off. So we've seen if we move in the direction of structured interviews and like I said, we'll look at what that looks like. It helps us because like I mentioned earlier, customer interviews are challenging because there's all this data. You're trying to detect patterns and make those informed decisions. And without that structure, insights are going to become scattered and it makes it harder to compare results, find those patterns and act effectively make those decisions. So this ties to that second challenge of the difficulty in extracting insights. So customer profile interviews, which we'll look into in detail, they can quickly be set up. So one of the things that is often the case when we're working with teams is people have never run an interview. So being able to quickly run them, get set up and do it at a high quality level is very important. If you have bad data coming in, it's going to be bad data coming out. So once you have them running at a high quality level, then they can provide a clear process for gathering and acting on customer insights. So what? Go ahead, Alex.

Yeah, Joe, just very quickly because somebody, Brianna was asking how we do customer interviews at strategize. Very legitimate question like who gives us the right to even talk about this? So we did switch to customer profile interviews. It's been a very powerful switch and we actually also use our own tools. So we now mainly not always because like we have a couple of different people talking to customers. So but this is what, what Kurt is showing is, is something we do and it's been in particular in exploration, a key thing when we're talking about the product and design team. It might be actually be unstructured interviews.

Yep, that's great. Now it's a perfect transition to kind of even saying what are these customer profile Interviews. So I tried to set a little bit of context here. So what is a customer profiling group? So first things first, we have here our customer profile, which is just a representation of your customer. You see here customer jobs, pains and gains of the jobs. What are the things they're trying to get done? Pains, what are the things kind of holding them back that are painful, the gains, those positive kind of outcomes that you want. And the first step that you kind of see here on this slide is you're going to map out your customer understanding using jobs, pains and gains. So I'm going to, for the sake of example, just pretend I am using a, I have a business idea for a wireless medical device and I want to reach out to a customer segment of nurses. So if I'm trying to map out my understanding, I'm going to say, what do I think are the jobs, pains and gains of nurses? Well, they have this job over here. They need to take care of their patients, they have these pains, they have too much going on, busy in the hospital, et cetera, et cetera. And then to run a customer profile interview, you're actually taking that same artifact, that same customer profile you just mapped out and going to a customer. So say I'm going to a nurse named John. I'd say, john, do you have this job? And I would read off the job is this you? And it allows you to have a conversation and understand, maybe that's true, maybe that's not. And we'll actually look in a second on the Strategizer platform what that looks like. So that's what a customer profile and a customer profile interview is. And here was a very powerful example. We had a Canadian team. They were consumer packaged goods company. They realized their innovation process was based on assumptions. They reached out to us, they wanted to test, they wanted to experiment. And this team came in, they had zero experience setting up, running and analyzing customer interviews. So they didn't come in with lots of know how and how to do this already, but using the Strategizer platform, and again, we'll look at that in a second, they were able to run 20 interviews over a few weeks. And let's look at what came from that. So first they mapped out their understanding of their customer. They mapped the jobs, pains and gains, and then they got ready to go talk to actual customers. And from those 20 interviews, they had in total 34 sticky notes of jobs, but 91% of time. So from those 20 interviews, 91% of those jobs were deleted at least once. Their understanding of what was actually true for their customer. You can see and now even go back to the points I was mentioning earlier. This isn't maybe they said this, maybe they didn't. They know with certainty that even have a percentage 91%. So these patterns begin to emerge again with the pains they saw as well. The majority of their pains were not true. So 55% of the pains were not true at all. So half of the pains, half of the people who said, nope, that doesn't apply to me at all. So immediately half of that, their understanding of their pains was able to be removed. Go ahead, Alex, you had a comment?

Yeah. There's a debate going on in the chat where people say, oh, but this is our leading questions. And you know, you can't do that. And well, there's a place for different interview techniques at different moments. This is not a problem. Now there is a space where you know nothing and you want some direction and you leave it open to just kind of figure out. But the challenge we've actually seen, and I'm not sure if, if I can't remember if Carol addressed it, is when people go out with completely unstructured, they actually are all over the place. And you do need a starting point. So this is a technique that is super, super powerful. And yes, part of it is leading is not a problem. Guarantee you from, from what the results we've seen, we used to do unstructured interviews or less leading questions and the results were terrible because people were all over the place. This has been the best way to get people started. Is there, you know, are there other techniques that more advanced people can use in different contexts? You bet. But this has not been a problem for us. This actually, on the contrary, from the hundreds and hundreds of teams we coached, this led to better results. So just wanted to get into that debate and you know, like, I'm sure there's going to be an ideological conversation here. We're just looking at the results because we need to help innovation teams.

And it's an important call out there where the majority of the time we're working with folks who are new to this, so not experienced practitioners. And we're very focused on how can we get them high quality results very quickly. So just jumping back in to look at what happened for this team, an interesting thing happened. One of their gains, one specific gain. 75% of the people interviewed of the 20 had tons of comments about that specific gain. So if we look at the before picture, they had mapped their understanding of what they thought their customer was and then after you look, they have a completely different understanding of what that actually looked like. And this happened in the course of a couple weeks. And obviously we know innovation, it's critical that you're addressing the most important jobs, pains and gains of your customers. If you have a value prop that's not rooted in customer understanding, it's going to lead to issues down the road. So this allowed them to then, after doing this testing, present an evidence based presentation to their leadership team, made them look good. And then the decision for their idea. It wasn't intuition, it wasn't someone's who has the most power making decision. It was easily traceable to the evidence because those patterns were so clear. So our point here that we're trying to hit on is really that customer profile interviews can be quickly set up, are easy to run at a high quality level and they provide a clear process for gathering and acting on customer insights. And now just to get even more practical, what that looks like. So on the Strategizer platform we have the ability to run these types of interviews and let's just walk you guys through what that would look like. So step one would be mapping your customer understanding. So you would be putting down your job's pains and gains. So what are the jobs for? Nurses. Okay, again you could start doing that. But one thing we want to call out and I'll even show you guys on the actual platform, you see the little AI button up here and you can use AI to assist you. Now this is a new thing we're rolling out where it's going to know what you've already kind of inputted around your idea. And if you've already started mapping some of your jobs, pains and gains, the platform, the Strategizer platform knows those ideas and use them to feed into the AI. So the more you interact with the platform, the more the AI becomes even more helpful. So it's going to give you the option with these different suggestions, you can accept it. Maybe it's not the best idea, maybe you want to change it, but you can use AI to quickly go from a blank page to have a quick understanding of what your customer jobs, pains, gains might look like. And then two, if we're running these types of interviews on the Strategizer platform, you would then be designing, experiment and adding the customer profile. We're super excited about this new feature on our platform. So you see, you're now seeing our new feature, this new widget and there's three kind of tabs you see up here. There's this design, test and analyze tab. So we're starting. In the design tab, you would select the experiment and you would select the artifact. So say I went ahead and did that. You would then see that same customer profile that I had kind of populated earlier gets pulled in. And this allows you to then run an interview with that customer profile. And it would open up. So here, here, now we're on the test tab. And I just kind of put in a fake little instance here. But you can add people's names of who you're going to interview. And when you're ready, hit the button, get started. And it opens up this focused view. So say I'm, I got this wireless medical device, I want to talk to nurses. I go, I meet with John. And what it does, it's going to hide all the sticky notes so that you're not overwhelmed. John's not overwhelmed. When I'm talking to him, I could click on the first sticky note and it's going to review it. And I just, like I mentioned earlier, I could say John, and obviously set context for what jobs, pains and gains are. But John is this. You improve communication with patients as a nurse. And he might say, yeah, that's definitely me. That's definitely a job that I have. And he might also say, nope, that's not me. Maybe you have to add in a different sticky note. He says, like, well, it's sort of this, but actually it's this other one sort of allows you. And once you've kind of gone through and unhidden all the different sticky notes, you're then able to rank. You see the rankings here, your top three. And now this artifact centers the conversation and it centers the data. So you're able to then, if we look at the next step, analyze and adapt your customer profile. So if we look at what that looks like now we're on the analyze tab of the interview widget on the platform and you begin to see a ranking. So we have jobs, pains and gains. And here we start to see a ranking. So let me zoom in a little bit, make it easier to see what we're looking at here. So like, for jobs, we talked to three people so far and we're beginning to get a picture of the top job. So the top one you see here is feel confident in patient care. You see, it's a little hard to see here. There's a little three. Three people said, yes, I have that job. But you contrast that with something like enhanced teamwork with real time data sharing. Well, three people Said, no, I don't have that job. So you begin to see a picture you should be seeing here. Now I'm actually on the Strategizer platform and I kind of have just set it up. So say we were just to go through those four steps that I walked you guys through. I come in here, I have my wireless medical device for nurses. So I might start mapping out my customer jobs. I might say, oh, I need to take care of patients when I think about nurses. But then I might say I'm kind of running out of ideas. I can use AI, generate some, maybe a mix of different types of jobs, get them added on to here, to the board to see. You see here, this one was just a blank one. If I want to come in here, like I had mentioned earlier, I can accept that job. And then obviously I'm just, for the sake of our conversation, I'm just going to accept them all and move forward to that next step. Obviously you would actually put some critical time into thinking about this. We also have a mini coach feature where it can analyze and give you feedback on the jobs. But that next step I mentioned was designing your experiment. So here you see this new feature. Like I said, we're just rolling this out. Super excited about it. So I would quick get started. My tab opens here. Again, that design tab select an experiment. This is something that we would have worked on before. If you're going through a Strategizer innovation, Sprint and I have a bunch of these nurse ones here, I can just add this and this allows you to then pull it in and get started here. So if I then move down to that third step of running interviews, I have this one already kind of set up ready to go. And you can see I already added in a different user. So maybe I want to talk to Sarah. I can get these going. And then once I'm ready, I would then get this focus view so I can add as many people we often recommend 15 to 20 to begin to really detect those patterns. Open it up. So when I'm in that conversation with a nurse, I then see this view that I mentioned earlier and I can work through one at a time. So hi, Sarah, you're a nurse. Is this a job that you have improving communication with parents, with patients? Excuse me. She says, yeah, like that's a job. That's something I, I need to do. Maybe this one that she says it's not. Maybe this one you have to edit a little bit. And there's some side note of some aspect to it. Once you've gone through and done all of these, you can begin to start ranking the top ones, your top jobs, pains and gains. And you can finish that interview and say, go ahead, Alex.

Yeah, let me just emphasize, you don't rank. You take the rank of what they said. Right. So when you put a one on it, it's because they told you that's their top job. Just wanted to emphasize. Right.

100%. You can almost think of it as you started with a baseline customer profile and now you're trying to make a customer profile of that individual person. You're talking to it. So 100%, all of the inputs need to be coming and stemming from that conversation in that person. So if we then scroll down to analyzing and adapting our customer profile, say I talked to John, I talked to Sarah, I talked to a couple different people. I then am able to see here that these three people I already talked to are done. And now if I'm on this analyze tab, I can see that view that I mentioned earlier where I have the top ranked jobs, I have the top rate customer pains. And now that picture I showed earlier of that Canadian team, you can begin to see a picture of the before and after the best guess of who your customer is to then moving towards a validated understanding that you can then build a value prop around.

And you might actually use five different interview techniques to get good results. So many of you were right. You want to have unstructured interviews that are not leading if they make sense. And Carol did say the right experiment at the right time. What we see is a lack of variety in the interviews. And customer profile interviews are super powerful. So we use those as the starting point in particular for novice teams. But there are also other techniques. I'm going to get into this a little bit. We're almost out of time. But it's super important because there are other techniques, visual techniques, and they have really good strengths compared to the, you know, just asking questions, getting answers, much harder to analyze. And some of these were productizing just like the customer profile interviews. Some are semi productized if you want, not as a software feature, but as a visual one. The thing I want to emphasize, somebody pointed that out already. There are three areas of interviews. Customer some people like problem interviews. We like to call it customer profile interviews because it's not just about problems, it's about jobs, pains and gains. There's some techniques that are very powerful for that, like the customer profile interviews that Kurt showed you. Then you have value proposition and solution interviews. So I'm going To show you some techniques for that. And then you have interviews specifically focused on willingness to pay. So there are different techniques in these categories. And the last one is even prioritizing either jobs, pains and gains or features or willingness to pay. So we're just not good enough in the number of different techniques we use at the right moment, right interview technique at the right time. So, and I'm going to zoom in first and I'm not going to go through a lot of them, just going to take one or two is the sale. The speedboat technique from or at least Luke Coleman made very popular with his innovation games and is very simple. This one today, we haven't productized yet. Matter of time. How does this work? You talk to customers and say you are, you have a boat, you trying to get something done. Explain to us where are you aiming, where are you trying to go, which harbor are you trying to reach? So the destination, where do you want to land? Number one. Okay, now what you also want to hear from them now is what is you, what is holding you back from getting there, from getting that job done. You will ask them to put up sticky notes. These are anchors. And the way you want to frame it is put up your sticky notes. But the more it's holding you back, the lower down you put the anchor. So here's the thing. When you put visuals in front of people and they can compare these two, you start to have a much better understanding of how they perceive these different pains that are holding them back, these different anchors. If you do this in a conversation, you will not get the same granularity of how much these things are pains or holding them back. And you'll do the same things for the wins that are helping them advance. So using visual techniques get you to more powerful conversations with a deeper understanding and a first little insight around prioritization. That's why we love the speedboat technique, which we're also going to productize into our experimentation or interviewing library. Because at the end of the day, this one you still need to analyze manually or with AI. We want this to be structured data, so that will automatically help you analyze. Here's another one, this one that we use quite a bit. It's called the VA value scenes. It's putting a image of how you create value in front of customers and getting them to comment that right. So you're giving them a prototype if you want, but just, just the drawing you could do with storyboards. But we like this moment of need. So I'll give You1 from Strategizer you have ben here, who just got the new job to implement an innovation function in his small company. And Ben got this job from his CEO, but he doesn't really know how to do that. So what is he going to do today? What's the solution? Today he's going to go to the Internet, he's going to look at the latest literature, he's going to see some great books out there, like the Invincible Company, or he'd had the choice to hire, you know, consultants. As a small company, maybe not so easy. So all these things are costly and time consuming because if you bought books and tried to implement this, you probably also get it wrong the first couple of times around. It takes a ton of time. Now, with the programs that we put in place, you have as Ben, you have a turnkey solution that immediately guides you through the process. So you can experiment or you can bring people along to experiment. This is a value scene. This is our belief of how the solution creates value. Now, do we know that? No. So you put this image in front of customers and you start to have a conversation. Now what this does, and this is deliberately leading because people are talking about leading. This is deliberately leading because what you want to have is feedback around the value scenes of how people see this. Does this create value? Do we need to change this? Now, we didn't productize this with software yet, but we productized it as visual workspaces. So that is very easy for people to do this the first time and to aggregate this. So I'm going to quickly kind of jump into how a workspace like this looks like. This is one that was productized, but as you can see, much more complex than what Kurt showed. So this is our semi productized version where it's not yet software. You make this image. And we're actually working with one of our coaches, Rapid Visual. They created a tool that you can generate these images with AI. So this was AI generated image. And then we run the interview and you can see we pre populate the empty sticky notes and guide you through it. Is it as elegant as what Kurt showed you? No, but it's already guiding you to help you as an interviewer do these things. So it's what we call semi productized. Now the other thing that it does is if you go to analysis, we automatically take all of that data and put it into one place. So you have an overview. Now, in a day and age of software, does this make sense? No. So what you saw with Kurt is that automatically this is aggregated and already to a certain extent, analyzed. So before we get to full productization, these are not software features. They're productized by visual workspaces. So now, last technique here that I want to show you. Somehow this did not go back to my slides. Let me see how we can do that. Here we go. Okay, so we saw the value scenes, something that you now can generate. So the small story, one of our clients used to do this with designers. Cost him some money and took him a month to get these value scenes ready. We now generate these in like. What was that, Kurt? We did this with a. In the lightning sprint, how long did we give teams to generate a value scene? A drawing?

We put. We put them on. In the pressure cooker. We gave them, I think like 15 minutes, maybe 20 minutes. And one team was able to produce three of these kind of video you saw there.

Yeah.

So the speed of the innovation process is going to really go through the roof. And then we got people to talk to customers in the afternoon after the first kind of work session in our lightning sprint. So what you also want to have is willingness to pay conversations here. We haven't really developed yet a visual tool, but you could go through the. The buying, purchasing process and actually also not just ask where the. The last thing to ask is, would you pay for this? Or how much would you pay? We like questions more like, how much do you pay today for similar solutions? Or out of which budget will this come? Now, if there are no similar solutions, you still should ask out of which purchasing budget? You know, do you think this will come if you're in B2B and if you are in consumer? Well, you're going to figure out, you know, what are they not going to spend on? Because it's likely to kind of take away from something else they're spending on. Now the last technique, and I'm just gonna kind of scratch on top of it. Then we have like five minutes for Q A. Carol is prioritization. So again, driven by what we see from. From customers. So we see teams that will say, oh, highly validated customer profile. And then we ask them, well, how do you know which job is most important? And show me the evidence. But they can't. So while they kind of maybe said it's first or second, still relatively light. So another technique that's super powerful is card sort, where based on customer profile and the value map, you start to create a series of cards. And the cards might represent jobs, pains and gains or features. And what you then ask them is to force rank these cards. So if we take the workspace kind of goes back to something like this. So you got the pre populated stuff coming from the customer profiles. You did you create the cards. And again, this is unfortunately the semi productized version, because our product team is just not large enough yet because we're just starting to shift towards recurring revenues. But what we do is we do explain how do you start the interview and you ask the customer to pull down the cards from here and rank them from low importance to high importance. And again, is this, you know, something that gives you really strong evidence? Absolutely not. What you want to follow up afterwards on is call to action experiments. But we do like three to four different types of interview experiments. Before you start to kind of move to call to action.