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Testing your ideas against reality can be challenging. Not everything will go as planned. It’s about keeping an open mind, having a clear hypothesis and running multiple tests to see if you have enough directional evidence to keep going.
This is the How I Tested That Podcast, where David J Bland connects with entrepreneurs and innovators who had the courage to test their ideas with real people, in the market, with sometimes surprising results.
Join us as we explore the ups and downs of experimentation… together.
David J Bland (0:2.087)
Welcome to the podcast, Chris.
Chris Guest (0:4.590)
Thanks David, good to see you again.
David J Bland (0:6.567)
Yeah, I was thinking back when we first started talking about having you on, I was thinking about when we first met. And I think if I'm remembering correctly, it was probably somewhere between 2012 to 14, maybe, at Lean Startup Circle in San Francisco, where we were just going to hang out as entrepreneurs and try to help each other test things. And I just remember meeting you back then as like, oh, wow, this guy has some really cool ideas. We should stay in touch. And
I have to say, you know, pre -pandemic, like going into those meetings and just really bouncing ideas off each other, it was a lot of fun.
Chris Guest (0:44.045)
Yeah, that's right. Those were the days that was the lean startup circle unconference. And I went once I sort of discovered the book, I became quite a nerd about lean startup for a while. And so it was quite happy to, to find my people and go and jump in and got right into volunteering at the events and everything. So yeah, it was great to meet you there. And I think the last time we met was actually at your book launch, because I was thinking about this earlier.
And that would have been one of the last events before COVID, I think. Was that the end of 2019, something like that?
David J Bland (1:18.855)
Yeah, launching a book right before COVID was an interesting experience. Lots of tests I ran during that. And I have to say, the airport bookstore strategy sound amazing on paper until everything shuts down and nobody flies. So it was a very interesting ride.
Chris Guest (1:30.794)
I
Chris Guest (1:35.466)
Yeah, that's one of those things that you really can't predict or mitigate for, I guess.
David J Bland (1:40.103)
Right, but I remember, so when I was writing that book...
You were at topology at the time and I was like, wow, we need some stories about what you're testing there back in the day. And that's how we really started talking about getting you as a case study in the book. And I know in the book, we can't necessarily go into as much detail as we like and everything, but you all were testing some really cool things back there with this idea of, oh, we're going to measure your face and put glasses on your face that are perfectly measured for you. And I remember the MVP and you got doing intercepts. It was such a cool, just such a cool experience.
cool story.
Chris Guest (2:15.399)
Yeah, well, it was a really cool technology and really different and unconventional as a startup, which is, which is what I love. And so it created an interesting testing case study because it was an interesting, but also challenging topic to test. So we had a lot to learn. Um, and so I really couldn't have found myself a better case study to, to put to, to test all of the theory that we'd read about and spoken about over all those meetings.
David J Bland (2:45.991)
Yeah, I was thinking about, you said something that always stuck with me, which was, and we both wear glasses. Those of you listening, we're both wearing glasses. And I remember you saying you were intercepting people on the street and there was this idea of, well, maybe they're problem aware or maybe they're symptom aware. And I remember that difference that you were just.
explaining to me and I was like, oh, I never really thought about it because I always thought about, all right, they have the problem or they wear or the actually seeking solution. That's what I'm sticking with. But you had this nuance to that that I thought was really interesting because sometimes people's glasses don't fit properly and they don't know why.
Chris Guest (3:24.005)
Yeah, that's it. And that was a learning that I got from just talking face to face with lots of different people that were wearing glasses. And I guess that was the genesis of something I've developed over the five years since, which are called the problem perception spectrum. Maybe a little bit of a balfour there, I'll take your feedback on that as a name. But it's the idea that in problem validation, the problem isn't binary. It's not just a case of do they have a problem or don't they?
or does this problem have the person have the problem or not, there's actually a whole bunch of steps in between. And those nuances are actually really interesting and really powerful. And so I guess as it relates to topology, and I should probably just give a quick bit of context so people know what the topic is that we're talking about. So topology eyewear is a concept of custom fit eyewear made from scratch based on a scan of your face.
David J Bland (3:54.938)
you
Chris Guest (4:17.731)
And so the problem that it was addressing was the entrepreneurs vision, Eric Verratti, his idea that most glasses don't actually fit most people. And the reason for this was that everybody's face is genuinely different and unique, but all glasses are made thousands at a time for a mythical average person that doesn't really exist. And so as a result,
Most glasses don't fit most people and it's incumbent on glasses, whereas to go into a store and try on a thousand different pairs until they find something that works. Okay. And so what topology was, was a system whereby you'd actually scan your face from a video on an iPhone. So you just take a video selfie. This was before even iPhone 10 structured sensors. There was no 3d model. We actually use computer vision. We take a video, analyze it in computer vision and make a 3d model of your face.
and then present an augmented reality virtual try on your face in a 3D model on the screen. And you can then actually see the glasses on your face, change the size of them if you wanted to make them a bit taller, a bit wider, change the color, and then actually order it from your phone and we'd make it from scratch one pair at a time in downtown San Francisco. So radically different concept. Coming back to your question about the problem perception.
The very first thing that I did, because when I met them, I didn't wear glasses. And they're telling me this story about this is what people that wear glasses think. I'm like, do that. I don't know. I don't wear glasses. And so the very first thing that I did was go out and spend a whole day walking around San Francisco, just stopping everybody that wore glasses and saying like, Hey, tell me about wearing glasses. What do you hate about it? And see what people would say. Um, and over the course of that, what I found was that people were aware of the symptoms, but not the problem.
So you could say to someone, hey, do you have a problem finding glasses that fit? And they'd say no. No problem. What's that? Do you ever have a problem with glasses sliding down your nose? Oh yeah. Do they have a pinch on your nose and make red marks? Oh god, yeah. Do they have a pinch on your head and give you a headache? And then people are like, man, let me tell you how much wearing glasses sucks, right? But they didn't realize that it was because the glasses don't fit.
Chris Guest (6:34.656)
And so there is an important difference that I realized straight away between knowing that they have the symptom of a problem and actually knowing what that problem is, which is obviously pivotal for how we position and talk about the problem.
David J Bland (6:48.745)
I love that. I love that you just walked around and chatted with people and tried to understand. And that nuance between are they problem aware versus symptom aware? Because again, ideally, I keep giving advice to people to say, well, go after people that are seeking a solution to a problem. Those should be early adopters. But it's not always that straightforward. And so I love that. And I'm wondering, so you mentioned this new framework you're using. I'm just curious, how is that fed into, you know,
what's happened beyond topology and what you're doing now as sort of a traction designer, like how is that feeding into your thinking today?
Chris Guest (7:27.067)
I mean, yeah, I found it absolutely foundational because it was in that, um, in that project with topology that I realized that there's a difference between knowing the problem. And, and I guess it's that idea of perception is reality, right? So it's not whether or not they, they do or don't have the problem. It's how they feel about it. And so the perception spectrum is, is saying, again, it's not just a binary, do you have the problem or not? It's actually a spectrum.
And it ranges from, and I won't sort of read out every step, but it starts with this, okay, no, I don't have a problem and they're right, they genuinely don't have a problem. And then you have that problem unaware where they think they don't have a problem, but we can see as the testers that they actually do, they're just not aware of it. Okay. But then there's a bunch of other nuances which are really interesting. So it could be, I have this problem, but I'm not bothered enough to do anything about it. Or I have this problem.
but I just don't believe that it can be solved. And then another step could be something like, well, I want to do something about it, but I'm not when I'm not sure what that is or when. And then another step could be, well, I want to solve this, but I'm going to do it with a manual workaround, which might be a spreadsheet or a post -it note or an intern or something, which isn't a direct competitor. Right. And so there are some similarities to this idea of the, of the bio funnel.
people go from sort of, you know, being brand aware to problem aware and so forth. But it's critically about steps within their understanding of the problem. And when you understand that it's absolutely transformational for how you position and communicate the product. So for example, in topology, what we found as I mentioned is that most people felt like they didn't have the problem of glasses that fit. But in actual fact, they did, they just didn't understand.
that that was why they was having a problem. So what that tells us is that our job is to market the problem in order to market the solution. If we just come out and say, finally glasses that fit, no one's going to get it, right? We had to do the work before that that would say, if you're seeing this, this, and this, it's actually, it's not you, it's your glasses, right? And then that's when the penny drops to people. It also, on the topology example, helped us actually understand who the early adopters were.
Chris Guest (9:47.158)
because it turned out that there is one group of people that do already know that their glasses don't fit them. And that's Asian Americans. Because as it turns out, almost all I wear in the U .S. is made for an average Caucasian face. Asian Americans have a certain different bone structure, which means that they don't fit them. Okay. And so many people have learned to go and look for this category of products called Asian fit glasses.
which you can find, there's usually one shelf of them in Wabi Parker or in jeans or something like this. But that then says, to us, that says, okay, that audience is in a different section of the problem perception spectrum. They're in the alt category one, which is, I know I have the problem and I want to solve it, but I'm going to solve it with a different solution, which is in this case, Asian fit glasses. Then our job to that audience is not to market the fact that their glasses don't fit. They wouldn't know that.
It's to say you think you wanted Asian fit glasses, but you actually want custom fit glasses. And here's why. Very, very different positioning, very different communication. So that's one example for topology. I can certainly share some more recent ones if you're interested.
David J Bland (11:3.785)
Wow, that's amazing. So, because we're always talking about, okay, is there observable evidence that people are seeking a solution to the problem? And usually where our heads go are, well, where are they going online and offline? And we'd like to think they're just typing in online, oh, how do I find glasses that fit? Or, you know, which I imagine you've all done some of that too. But I think this nuance you're bringing up that, well, they could be hiring a solution.
that isn't quite...
what was intended when that solution was designed. So it's almost like they're hiring a solution in a different way or they're behaving in a different way, trying to find a solution. And I don't know if founders think about that way. I think we're saying, oh, we're just gonna Google, I'm gonna do search analysis and try to find out is anyone searching on these terms and look at the related terms and all that. But from what you're describing to me, it sounds like it's much more nuanced than that because people could be hiring solutions that maybe aren't necessarily even marketed to them, but they solve the problem.
in a way that maybe even the people that created that solution don't realize.
Chris Guest (12:8.719)
Yeah, that's right. And it's all about understanding how they contextualize and think about the problem in their mind. So I'll give you a different example. The last startup I was at CMO was called Bright. And they made a basically a very premium smart mattress. And the problem that this mattress solved is the problem of waking up during the night. Okay, not so much about falling asleep, but the
the main problem was waking up during the night and how that makes you feel in the morning like you haven't slept at all. Okay. So you go out and you ask people, again, try and find out, um, you know, do people have this problem or people aware that they, and do they care about waking up during the night is different to say falling asleep and structure research interviews to try and get an understanding of what's most important to them.
But then as we go through the spectrum with these customers, well, we found people there was, I know that I have a problem waking up during the night. I do believe it can be solved, but I never imagined that the mattress could be the solution. Okay. So people think, oh, I'm waking up during the night. The problem is I'm drinking too much water and I need to wake up and pee or the problem, or I need a solution that is a sleeping pill.
or I need a new pillow or something like this. No one imagined that a mattress could do this. So we actually went a level deeper and found that, okay, so when we presented to people, you know, here's a mattress that can actually stop you waking up during the night. And it does it because we use AI to monitor your sleep in real time and adjust pressure through the, by the inch. So if we see that there's a spot of pressure that might wake you up, we actually intervene and change pressure by the inch in order to stop you waking up.
Um, that particular unlock was took people from, I don't believe this solution can work or I believe that I need to solve the problem of waking up, but I don't think a mattress can do it to, okay, now you've told me that, but I can't believe you. And so it's understanding those, those nuances. I'll give you one more example. Um, I'm working with, uh, actually Sam Hattoon, I think you, you, you might've met back in the day.
Chris Guest (14:26.248)
Um, he's working on a concept for a software delivery platform that's potentially, and, and, you know, a replacement for agile as a whole methodology, um, and particularly managing tickets and backlogs and things like that. And, uh, it's called narrative. And just for context, instead of having a backlog of lots of different myopic stories, you have one narrative presented as a flow.
that unites the entire team. The business can see it, the technical team can see it, and they find the tests and specs all in one place. And so this solved a number of different problems we thought. And at one point we had two different hypotheses about which was the problem, right? One of them is about creating a single source of truth for the whole team. The other one was about guiding people from vague requirements to detailed specifications. And we wanted to find out which one was most compelling.
to the audience. So we went through this process and what we found was actually two very different points in the spectrum. With regards to the single source of truth, almost everybody was in the column of, I have this problem, but I just don't believe it can be solved. All right. And the general refrain was like, yeah, yeah, yeah, bullshit. You know, I...
Yes, that's a problem, but no one can solve that people have been talking about it for decades. I don't believe it can be solved Okay, and until we showed them and then they said, oh, okay All right. No, I'm with you now I'm with you now and but that would tells us our job is not to just market single source of truth because it's just gonna get Discarded, you know, the people can disregard the claim So that tells us our job is to actually prove it and what ways can we actually prove that this does work?
With the requirements to specs problem, people knew it was a problem, but they're solving it via manual workarounds. They say, yeah, yeah, that sucks. But, you know, we've learned to get everyone in the team in together in a room and we do an event storm session or we do a brainstorm and we put stickies on a whiteboard and then we do a backlog grooming, a very manual work around for the same problem. And so there our job is to say, okay, you thought that you wanted to do that process.
Chris Guest (16:49.218)
But actually, we've got this product which is going to make that much, much easier. And so you can see that understanding the nuances of how they perceive the problem makes a radical difference to how you position and how you message it.
David J Bland (17:5.225)
I'd love that. I feel as if in the past, a lot of the advice we've heard has been, well, you test with customers and we frame it as a headache versus migraine problems. That's been a really common one over the years, right? It's a headache, it's a nuisance. They might try to find a solution to it. They might not. They might just wait it out and it goes away. And then migraine being, okay, it's much more painful. They're gonna find a solution there and it's gonna be urgent. But...
To hear you speak to this, and I would frame this under kind of desirability risk, right? It's a lot of desirability risk around your value prop and the customer and their jobs, pains and gains and all that. It feels as if that's almost not giving it enough nuance. There's so many different levels of desirability testing here that you're probably not necessarily just running into situations when you're trying to test your ideas, that it's just a nuisance, migraine, or a nuisance.
that there aren't just two places here where it's headache and it's a nuisance or migraine and it's a really urgent solution. It sounds like there are so many different layers there that you need to test through that maybe us framing them as those two extremes isn't necessarily helping us in our testing.
Chris Guest (18:24.030)
Yeah, well, you're actually, I mean, you're right. It's just that that level of the extremity of the problem comes actually a step before understanding the perception at the point you choose the audience. And so what I mean by that is we start off and when I work with clients now, I start off by trying to really understand what's the problem you're trying to solve and then ask, okay, who's the customer that most experiences that problem?
And we do go for a process of saying, okay, is it going to be in that last example? Is it more about, uh, the technical product manager or is it the, um, uh, the, excuse me, the delivery manager in a product in the team that has that problem. And is this a problem that enterprises has more than startups or scale ups? Or how do we triangulate some niche that we think most acutely, most painfully feels this problem? Cause I do agree.
very strongly actually that that is the best place to find your early adopters. But then having dialed in on someone say, hey, this is our assumption of who the customer is. Yes, you want to validate that they do experience the problem to the extent that you do, but also go a step further and say, what is it? What does it feel like to them? How do they perceive it? Through their eyes and not through the entrepreneur's eyes, not just do they agree with our statement, but.
What do they say unprompted? And so the way to get to this is a qual interview, basically, but going through a sequence of steps where we start with very broad open questions like, you know, tell me about your sleep. Or if you could, favorite question, if you could wave a magic wand and change any one thing about your sleep, no matter how improbable it might seem, what would it be?
And then we're looking for what's the first thing out of their mouth. Okay. Then you had a second wish. What would the next thing be? And you ask a few open questions like that to see what comes out unprompted. And then I go into, um, Hey, have you ever had a problem with this? And then it's a prompted question and then tell, and then you use those techniques about, tell me a time when you did this, what did you do to solve that problem? When you start to go through that sequence and the real, the real trick of it is.
Chris Guest (20:49.111)
And this is the bit where it gets really hard. How do you ask one question that doesn't pollute the answer to the next question? Right? So you kind of not accidentally leading them to your to your natural conclusion. But yeah, it is still what's the problem first? Who's the customer that experiences it? And now let's take that specific customer and look at it through their eyes. And if you're doing that,
and you find out that actually a lot of the people were in the camp of I don't have the problem or I don't care about the problem. Well, maybe your customer hypothesis is wrong. And then you do go back and say, okay, well, who is our next guess? Now let's take them. Do they resonate the problem? Yes. And what's their perception? And then you match those two together.
David J Bland (21:38.029)
Yeah, I feel as if the trend that I was hearing was past experiences from you. It's not a lot of future hypothetical, would you buy this solution type, which I think people get very excited about their solution and that's where they lead. Polluting almost the answers as you framed it, because they're just excited and they want to know a future hypothetical situation where you're going to buy this thing for this price because of this.
problem you're experiencing. And what I'm hearing from you is very much having them tell stories about their past.
Chris Guest (22:13.203)
Yeah, and you know, I'm not really an expert in having research done a lot of research, sorry, a lot of study of research techniques, but I, someone gave me that advice at some point in the history and in the past, you know, don't ask someone what they would do, ask what they have done. You know, the classic example not being how often do you go to the gym, to which we all want to say three or four times a week, you say how, how, how many times did you go to the gym last week?
and then you get a better indication of the truth. So I try and apply some of that mindset as best as I can remember.
David J Bland (22:48.333)
Yeah, I like it. I like it. So I'm curious, what are some of your favorite experiments you've ran over the last few years? Like things that maybe people aren't aware of or aren't very common. Just really these amazing experiments that have generated evidence for you that you, some of your favorite ones. What are some of those?
Chris Guest (23:7.187)
You know, I think the topology example in the book is probably one of my favorite because it was, there was just so many unknowns and it was such a wildly different product and it required quite a lot of thought of how we were going to get evidence for it. So as I said, the first thing that I did was just go out and talk to a lot of people and ask them about wearing glasses and give me some idea of like, yeah, okay, people don't like this actually. This is something that, uh,
This is something we might want help with. But we had a number of big questions and big assumptions. And the first thing was kind of, does anyone understand that they have this problem of finding glasses that don't fit? Would anybody believe that custom tailored eyewear glasses made just for them would actually solve that in any way? But then there was a real key shift. This is...
a textbook discontinuous innovation in terms of requiring the customer to change their behavior in order to adopt the product. You thought that you buy glasses by going to a store and trying on a thousand pairs, actually no, you're going to do a virtual try on instead and we're going to make one for you and it's going to fit. Huge labor of faith for the customer to take to believe that that's going to happen. Would anyone do that? And I should also say as well that,
I can't remember what our starting retail price, but Framon Lens is together, we're in the region of about 500, 550 bucks, which for someone that doesn't wear glasses or only shops at Wabi Parker, that sounds a lot, but that's actually a well -established price point of what you might be paying for stock glasses with the words Tom Ford written on the side. So it's an existing price point of very different proposition. And so...
You know, when I first met Eric and the team at topology, he'd been working for years in stealth, creating this unbelievable technology, both the software and also the hardware to actually make it. But he'd never actually gone out and showed it to anyone and got their feedback. So there was a lot to learn. So we had this idea that we could start getting feedback on this. We didn't have a product that anyone could use in terms of the software, the actual, the virtual try and was very difficult to use.
Chris Guest (25:27.595)
But we did have this test rig, we called it. So the actual engineers, when they were making test pairs, they'd have a version of the app with all these ugly sliders on it. Like you couldn't decode how to use it. It just had loads of symbols all over it. But we thought, well, no one else could use this, but we could. What if we got in front of customers and we scanned them, we operated the app forum, but then we could at least talk them through it. And so we thought, okay, this is our chance to do and.
I think we'd call this a concierge MVP. You could probably, you could tell me better whether this is concierge or wizard or what, I think it was maybe a little bit of both. But what we did is we found a partner, lovely chap called Steven, an agency called Partners in Crime, who had actually opened his design studio in a storefront on Union Street in San Francisco. And so for anyone that doesn't know the area, this is a lovely,
David J Bland (26:4.736)
you
Chris Guest (26:25.833)
full of boutiques with a sort of a trendy affluent crowd that would walk up and down. And the idea was, well, we'll set up a pop -up shop in front of the store. We created a fake name at the time. We weren't called Topology. So we just made up a name and called ourselves Alchemy Eyewear. And Stephen made us some posters for the window to say, you know, new concept pop -up today. And what we did was set up a pop -up
David J Bland (26:46.880)
you
Chris Guest (26:55.175)
in the store with Eric, the CEO and Rob, the COO and remember Jason was there as one of the engineers and said, okay, you guys are operating the demos and I'll go out and grab people and bring them in to come and have a look. Cause you know, it turns out if you want to do that in San Francisco, there's two things that are helpful. One is you say, I'm a startup founder working on a new concept because then other San Francisco types want to stop and talk to you and find out what you're working on.
David J Bland (27:17.743)
you
Chris Guest (27:25.595)
And then the other benefit is if you have an English accent, it does just grab you an extra couple of seconds of intrigue when you could spurt your pitch out there and get your question out and hook someone. So I went out into the street and would grab people that were wearing glasses, ask them a couple of questions to see if they, you know, seem like they were good to talk to and they were interested. I'd give them a one or two line or explanation of what we were doing and say,
David J Bland (27:33.295)
you
David J Bland (27:41.327)
you
Chris Guest (27:53.892)
could you come into our pop -up and check it out and give us some feedback? And by the way, at that time, I'm trying different sentences all the time. Every single pitch was a bit different, and I'm learning and iterating what people are resonating with. And then I've walked them into the store and introduced them to one of the guys that are ready to do the demo. And then the guy in the store would ask them a few more questions. They'd actually do the scan for them.
and then ask them more questions while the scanner's processing, because this was before we'd built out all of the AI processing on the cloud or anything. This is, let me think, 2016, I think we did this, you know, before there was the AI infrastructure there is now. So it took 12 minutes for each scan to process. And so when we scanned a customer, the guys had to keep them entertained for 12 minutes to stop them leaving the store.
David J Bland (28:47.567)
you
Chris Guest (28:52.610)
And then we'd show them the virtual try on, uh, help them still that's the style of their glasses. Um, now what we wanted to do is to try and control this experiment in a way that we could actually get useful data for it. And I told the guys like, let's not expect that anyone's going to buy any glasses from us today. Right. We're not really looking for that as an objective, but we want to see how interested people are and where their interest drops off. Right. So the first thing is like,
Can I come up with a sentence that gets people interested enough to come into the store? The next one is then when they're in the store, what do we need to convince them of to be bothered to take a scan and let this, you know, a few strange nerdy guys like us kind of scan their face of an iPhone. They have no idea who we are. You know, this requires a little bit of trust. And then having seen their face in the store,
David J Bland (29:42.703)
you
Chris Guest (29:51.488)
on the virtual try -on, do they actually believe that something real is happening here? Do they believe that we've measured their face? How do we help them understand that? And we do things like flip to a developer mode where you could see a wire mesh and a load of measurements and stuff. And it turned out that was a big unlock for people understanding that this thing was real. And then we had to control for a lot as well. So...
David J Bland (30:11.457)
you
Chris Guest (30:18.206)
In the real world, we understood, okay, if we have an app and people can download it from the app store and buy online, well, we'd need to have loads of great photographs there. That was an assumption that people would want to see high quality product photography to know this is quality product. Well, we didn't have this yet. So we couldn't show them that, but we thought, well, this isn't really a fair test if we don't show them what the glasses are looking like. So we said, okay, we'll bring along some samples, but then we can't do that because that would pollute the experiment because...
David J Bland (30:21.552)
you
David J Bland (30:45.296)
you
Chris Guest (30:47.866)
in the real world when they're in the app, they wouldn't be able to see and touch the glasses. And so then we had the idea of, okay, let's put them behind some glass. And so I think we actually, I don't remember where we got a little display case from, but we actually put the glasses, the real ones on a shelf behind some glass so people could see it and not touch it. And then we said, okay, this is our proxy for seeing a product first glass.
And then what we did is people were going through it and say, okay, let's just take a tally. Like how many people that I stopped on the street would agree to go into the store? How many people that came into the store would let us scan them? How many people that would scan them, you know, gave us good feedback? One of the things we predicted was that people would say they loved it when they didn't, because people are polite for the most part. And so we say, okay, well, we need to find out if they really like it or not. And so what we did was say, okay,
David J Bland (31:24.112)
you
David J Bland (31:37.328)
You
Chris Guest (31:44.315)
At the end of the scam, let me email that to you. Can you give me your email address and I'll email it to you. And we said that, okay, we think that if somebody says they like it, but they don't really, they won't give us their email address. So we counted that as kind of like an expression of interest. So this was roughly how we set it up. And I went out and kind of spent three hours, you know, acting like a carnival barker in the street, roll up, roll up, come in and see our demo. And after a few hours, I went back in.
David J Bland (32:7.248)
you
Chris Guest (32:13.912)
see Eric and say, how's it gone? And he said, we've sold four pairs of glasses. And I think it was, I think it was for from memory, but yeah, they just like made a thousand or more, a couple of thousand dollars in the last few hours. And I guess the other ironic thing was that the storefront that we, we had was only two doors away from Veo Optics, which is a very, you know, high end designer eyewear store on Union Street.
David J Bland (32:16.624)
you
Amazing.
Chris Guest (32:43.832)
And we easily solved more than they did on that day. So that one was a happy outcome. I actually decided to join the company at that day. I was freelance at that point, but I went home and said to my wife, I think they're onto something here. I think I'm going to join. So that's when I joined as CMO after that. But yeah, that was just one step in a very interesting journey.
David J Bland (32:53.922)
you
I love how methodical you were though. You know, you're tracking how many people you're intercepting, how many people are greeting coming in, how many people are greeting get scanned, some kind of currency with.
You know, is there real interest trying to close the say do gap because people, yes, will kind of nod and politely say they're interested, but then are they willing to give up anything, even if it's their email. I love that progression. That's such an amazing story. And it gives such much more color to it than, you know, what we were able to include in the book. So thank you so much for sharing that. It feels as if it was a lot of desirability testing there, maybe a little bit of viability, but the viability wasn't the focus. It was more about, you know,
Do people understand our value proposition and do they experience this problem enough and will they trust it? That trust, you know, having a solution that works but people don't trust it, I imagine would be a very frustrating place to be in.
Chris Guest (33:47.118)
you
Chris Guest (33:58.205)
Yeah, absolutely. And you're right, it was about desirability at that time. That was the biggest question. And we had actually, you know, I should look, we've probably got a photo of it somewhere, but we did a David Blad assumptions mapping exercise with a piece of flip chart paper stuck to the side of a five axis CNC machine in the workshop in Bayview. So we did it old school. We were legit.
David J Bland (34:9.585)
you
Chris Guest (34:24.403)
And that was the thing that rose to the top was about, you know, do people have the problem? Would they care about the solution? So it was pure desirability. Um, after that point, it did flip into more of a mixture of feasibility and viability in parallel. Um, the biggest risk for the product and the engineering side was, can we actually make this a great fit? Cause it was hard. You know, people say hardware is hard. That was.
really hard because they had this incredible technology using laser cutting and CNC machines that most of the eyewear industry didn't think was possible that the founder had created. And so he just needed to make loads and loads of pairs to make sure he had it dialed in. And so we were very quickly into, okay, we need orders. We need orders from real paying customers.
not just friends because again you make a pair of glasses for a friend and they're going to tell you that they love it because they haven't got the heart to tell you that they don't right but if you take 500 bucks off someone they're going to tell you if they don't like it and so you know we wanted to get out and we actually um i used um ash i always get i don't know how to pronounce is ash moria uh link okay great uh so he has this um
David J Bland (35:22.001)
you
David J Bland (35:43.413)
Yes.
Chris Guest (35:48.399)
framework in one of his books where you go through different orders of magnitude. So what do you need to go from zero to one? And then what do you need to go from one to 10, 10 to 100, 100 to 1000, so forth. And so we said, okay, well, that was our experiment to see if we could go from zero to one. And we did. And so then it was like, okay, what are we going to do in order to go from one to 10? Well, exactly the same thing. There's no reason to change anything else. So we just did more pop -ups. Okay. So we make it to 10.
David J Bland (36:11.825)
You
Chris Guest (36:17.260)
What are we, are we going to go from 10 to a hundred on pop -ups? Yeah, I think we can, but I think we need to, you know, build out a little bit more of this and that, you know. So we did that and we were just always getting orders, getting orders. I'll tell you about some fails along the way. Um, and they're always surprising, but we did, uh, I think our best event was at the Maker Faire in, um, just south of San Francisco, I think like Redwood city. And so this is a meetup of, of.
David J Bland (36:41.745)
you
Chris Guest (36:45.867)
nerds and makers and inventors and tinkerers that, you know, coming to buy parts to make robots with and stuff like that. And so we did a pop up there and we took something like 30, 32 orders over the space of two days. Right. So very, very successful. Um, but I think we've got a false positive for two reasons. One was that the audience were very nerdy and it was very much like a.
I'm a nerd, you're a nerd, we're all together, one of us, one of us, let's buy from each other. But also at the time it wasn't possible to buy online. So people would like, they'd try it on and they'd say, this is really interesting, you know, I love what you're doing. Can I, so can I just go to your website and buy this? And we say, no, no, we're not live yet. We're just doing a pop -up for two days. And then, okay, well I'll buy now because it's now or never. The next event we did, we had launched,
David J Bland (37:18.353)
you
David J Bland (37:29.425)
Wow.
Chris Guest (37:43.784)
And I think this was, we did a pop -up on Valencia street and people say, can I buy this online? It's like, yeah, yeah, no problem. No orders. We went from like 32 in two days down to zero because we lost that immediacy. And people say, okay, yeah, I'll do this later. And when someone says I'll do this later, they never do. So that was one thing that we realized that actually, yeah, that immediacy was giving us a false positive.
The other thing we found, which was counter -intuitive, is that the better we got at the pitch, the worse the conversion got. How is that possible? And I think that in the early days, you know, we're all awkward. We were making it up as we went along. And I think there was a certain charm to that. And I think that people could see that we were genuine and we're trying to figure it out.
Maybe they felt a bit sorry for us, but I don't know, but people gave us a go. And then, you know, by the time I'd spoken, I'd literally spoken thousands, thousands of people face to face. Probably, I think I estimate one to 2000 people. So after all, I got pretty good at the pitch, but the slicker I got at it, the less effective it was because people didn't, it just lost some of that beginner's charm and it more like a salesman.
and less like a founder that was just trying to figure it out, you know.
David J Bland (39:12.038)
That's interesting. I've had that experience sometimes with I'll help a team and they'll say, we're going to do a really quick and dirty landing page with our value prop and everything. And they'll start getting some interest. And then they'll say, oh, we got interest. We have to make it look all better now. And they'll polish it and spend days moving pixels around. And then the polished version actually generates less demands about. So yeah, I do think there's something into that. But I just love that story of how you all.
You know, you try pop -ups and you say, okay, this is where, this is as far as we're gonna get with pop -ups. What else do we do? How do we scale beyond that? That's amazing. I just love hearing you talk about it because it's such an interesting example of it's hardware and it's software and it's consumer. They're somewhat symptom aware, but not problem aware. There's so many different dynamics in that story. And I'm just curious, like, what are you testing now? Like, what are you, what do you, like, cause this was a while ago. So what are you doing today? Like, what are you digging into now?
Chris Guest (40:9.671)
Yeah. So, um, you know, I was a startup CMO for, uh, eight years over three different startups. Um, the two I mentioned, uh, topology and then bright work with seven of those years. Um, and now I'm in advisor mode. And so I specialize in positioning for AI products and unconventional startups. Um, and by unconventional, I mean, uh, startups are offering something that is.
radically different. It requires customers to change their behavior in order to opt to adopt it. Or it requires, you know, it doesn't fit in any existing category of products. Or it's just really exceptionally difficult to explain. And I think when you're in that position, I mean, on one hand, that's where the really interesting stuff is. And at some point, that's maybe where the greatest value is created. But it just is really hard to get traction. And so,
You know, that that's kind of a common thread over a lot of what I've done. It's what I really enjoy is figuring out those, those hard challenges. And I, and I package this into a practice, which I call traction design and traction design is, you know, it's really approaching the problem that nowadays, traction is, is the number one existential threat facing startups, I believe.
And despite brilliant products, great innovators, too many startups die on the battlefield of traction. There's almost, so, you know, I was thinking that there's almost like a three different acts of the trilogy mapping to your kind of your free circles of the Venn diagram, right? There was like the age of feasibility, where the biggest challenge was, could you build it? Because we didn't have the democratized technology infrastructure that we have now.
And so it was worth someone tinkering for a year in their garage to make sure they could build the thing they wanted to. And then I think, Circus, Steve Blank, Eric Reese, 2010s, those sort of terms, what they taught everyone was, okay, it's not the feasibility, it's the desirability that kills you. You might disagree with this, and it might just be because I'm kind of stuck within the local maxima of San Francisco, but I feel like a lot of people have got that message now.
Chris Guest (42:36.135)
And I feel like there's a lot of startup literature about, you know, how do you create something that people want? And as a result, you know, we've never had more great products hitting the product, hitting the market every single day. It's like a fire hose, especially in the age of AI. And so now I think we're going beyond the desirability phase into the viability phase and particularly the marketability or traction phase.
And so what I'm working on is how can you actually validate from the outset that you've got the potential to gain traction later on down the line? Cause there's this weird thing that happens where, you know, every, every startup investor is telling founders, come back when you've got more traction, right? That's probably the most uttered sentence in all of Silicon Valley at the moment. Come back when you got more traction, but yet the
Process that everyone's following is still product first everyone still goes prototype Can we get to problem solution fit from problem solution fit? Can we get to product market fit? What's even the difference between there you find some different points of view and what the difference there is and then you worry about traction, right? Well now 90 % of your runways gone and you've not if your if our job is to validate the riskiest assumption first traction should come first
And so what I'm working on is kind of how do you turn that around? So can you from the outset, from the earliest days, validate a market opportunity, validate positioning and validate your hypothesis of how you're going to get to traction for your early adopters before you spend all of your runway just trying to get to problem solution fit. And so that's the process of traction design, which is...
kind of a work in progress. So write about it, you'll find it on Substack. Rather than being a finished text, it's kind of a thinking in public, if you like. And then I'm developing that with various clients in one -to -one consulting as well.
David J Bland (44:44.602)
Very cool. Yeah, it's almost like your risk moves around and then you're right, you know, because back when we met, I was, I think I was still at Neo, which was kind of like a, almost like a startup studio. And we were pulling together all these designers and developers to work cross -functional to build, like literally code, you know? And I would say, wow, fast forward to today, that's probably a no code, low code studio where you can just spin up stuff. Like the feasibility isn't.
isn't such a risk anymore with a lot of that stuff, or it's certainly not as expensive on the cost side. And yes, we have a lot of material around desirability and how to test with customers. And really quickly, even if somebody wants something, it's really pay enough. And then how do you get enough traction? So I do like that framing. I do think you're onto something with that format. So that's very cool. I do want to thank you. Oh, sorry, go ahead.
Chris Guest (45:42.681)
I mean
Sure, sure, yeah. Yeah, so I guess on that topic of traction first, I wonder, and I'd love to hear what you think. We have this model at the moment of kind of prototype problem solution fit, problem market fit, traction. I think it's offer traction, product traction, market traction, right? Let's just take out the phrase,
product market fit, which most people are confused by to the extent it's not really that helpful. All right. This is the most important thing in your business, but I can't tell you what it is or how to measure it. You'll know if you get it. Right. What if you were to actually formalize, okay, the first thing to do is to construct an offer that you can validate will get traction with a valuable market. You can almost think of it as the top five boxes on a lean canvas.
Okay, so you've got your customer hypothesis, the problem, value proposition solution, and Ash has it down as unfair advantage, but I think a bit more just positioning, you know, how are you going to carve out your niche and defend it. To validate those five things plus your price, that gets you to it. You should be able to take someone from a point of, I don't know if I need this to shut up and take my money without even needing to.
touch the product. Right. So I met a company and this is not one of my clients, but I met a company in the EdTech space. They had a proposition of, you know, your kids get A or A star, all your money back, okay, in their exams. This is in England. Now as a parent, you almost don't need to know how they're going to do that.
Chris Guest (47:42.361)
to know that you want that outcome. The only missing piece of information is how much. If you say to a parent, you give me 50 bucks a month and I'm going to guarantee that your child gets an A or you're going to get your money back, you already want to buy, even if you don't need to know what the solution is. So I do believe that you can create an offer and validate that a valuable market wants to buy the offer.
before you've even built the solution to fulfill that. And if you can, that really is doing what you teach, which is to identify your risky assumption and do it first, which is what most people don't do. So that's what I've kind of got to be in my bonnet about, as we say in England, and I'm working on it.
David J Bland (48:31.764)
I think you're onto something with that. And again, feasibility time and time again, the teams I'm coaching, that is the least risky part of things, whether they can build it. It's always, well, do people want it? And then if they want it, will they pay enough for it? And how do you start figuring that out before you over invest in something that then you're stuck with? And I always have a saying that you can't pivot if you're broke. So if you spend all your money on feasibility, it does cost money to pivot, right? And if you don't have any money, you can't pivot. So I do think this idea of
Chris Guest (48:53.633)
Yeah.
David J Bland (49:1.718)
you know, just pivoting your way to success, you know, when you think about in reality, as a startup, how many pivots you really get? Maybe one, two at the most before you run out of money. And so, you know, spending your time on feasibility, it just seems like that's the most expensive way to learn and you're only learning kind of in this customer -free zone. So I do think you're onto something with, can we get traction and specifically traction going, not just desirability, but also going into viability on the front side.
and use that to help inform our solution. That would help, I think, the mental model with people versus I'm going to have a solution and then I'm just going to see how much will people pay for that. I do like the way you're reviewing it. Cool. All right. So I really appreciate you spending time. I love the stories you shared about testing, especially back in topology days. I love that you added more color to that. So where would people go if they want to find out more about you?
Chris Guest (49:40.185)
Awesome, thank you.
Chris Guest (49:55.801)
Yeah, absolutely. So I'm on LinkedIn at slash Chris guest as in hotel guest. And I also have a website at traction designer dot com and the problem perception spectrum. I'll create a worksheet and a resource for your listeners there traction designer dot com slash problem. So you put that in that will take you straight to that resource. And then traction design is on sub stack. If you're on a sub stack, just search for traction design.
and you'll find it there. I'll be writing more about the perception spectrum there and plenty more testing stuff to come.
David J Bland (50:34.164)
Awesome, thank you. Looking forward to what you're learning in public on traction design. So thanks for joining us today, Chris.
Chris Guest (50:41.591)
It's a pleasure, thanks so much for having me, good to see you again.