Oct. 15, 2023
How I Missed a $10B Opportunity Because of Bad Customer Discovery
Weak customer discovery is the number one reason why most idea-stage startups fail. It usually leads to founders wasting months solving fake problems.
In my case, bad customer discovery cost me even more-- I ditched a startup idea that other founders built into several companies worth $10B+.
00:00 - My First Startup Idea
03:36 - A massive miss
06:12 - Looks for An Intense Yes
08:00 - A Researcher's Mindset
14:02 - Meet Your Customers Where They Are
17:12 - The Devil is in the Details
19:40 - Research Takes Months
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So it's 2013, right? And I have , um, one of my first, like, I would say, real tech startup ideas that I've ever had. And it was one that had been germinating for quite a long time. Actually, the reason I came up with it is because I am , so, I was born in Argentina and Buenos Aires, and so I'd go back on my family pretty often. And one of the things that's really different about, well, specific Buenos Aires, I mean, I'm sure it's in a lot of other cities, but because it's such a dense city, like a , it's like a New York City type of thing, right? And delivery for a very long time was standard, like, completely standard. I mean, if you went to my grandma's house, even she would have like 50 magnets on a fridge, right? Where you could deliver food from just about any single place. And that was just such a difference between there and where I live, which is in Ottawa, you know, city of a million people, not really all that dense at all. The only thing you get delivery for, you know, five, 10 years ago was pizza and Chinese. And so as I thought this through, it was clear to me that like the main issue was density. At the end of the day, when you have so many people packed together, there's so many restaurants, and on top of that, there's just so much more efficiency from a delivery perspective. So clearly a city like Buenos Aires, they could deliver a bunch of things, but in a city like Ottawa, it just didn't make sense for independent restaurants to offer delivery because there just wouldn't be that much demand for, for their , uh, for their food. And to be clear, like back then, everybody handled their own delivery. Like in Buenos Aires, every single restaurant had their own couriers who would deliver their own food. So this model obviously didn't make any sense in Ottawa, but when these things came together, in my mind, what I thought about is, okay, what you really need is density. You've gotta find a way to get that density, even in a city like Ottawa. And so the obvious way to do that was to effectively aggregate all these restaurants in one platform and have couriers who delivered for a bunch of different restaurants. I'm sure that this sounds pretty familiar because there are massive startups today that have completely crushed this thesis from Uber Eats to DoorDash just eat. It's full of them. But believe it or not, in like mid 2013 was when this idea clicked in my mind, and I was in the right kind of, it was, you know, right after graduating university and I was ready to start something. It was, it was me and , and a co-founder friend of mine. Uh, and so we decided, you know what? This could be a really good idea, by the way, like from a timing perspective, I couldn't have been more, right? I mean, DoorDash started early 2013. Uber Eats didn't start till 2014. Things really should have worked. There was a company actually in Canada called Skip the Dishes. They all , they started like six months before they've been acquired for like $200 million. And so one of the first things we do, right, we're supposed to talk to customers. So one of the first things we do is think, okay, well there's a courier side of this, so let's at least like see if there's demand from like, from supply . Like is there supply of couriers out there that are willing to do delivery? And we kind of modeled it out and we said, okay, maybe we can offer, I think it was like $5 a delivery. I don't , I don't remember exactly how we, how we priced it out, but we put out these ads on, on Kei , which is like a Craigslist just Said, like, do you want be a driver for, I think we called it like start delivering.ca , right? Because it , it's a Canadian company. And , uh, so we put out start delivering.ca like, do you want to deliver? Like here's how much we charge. And we got a flood of emails, like just a flood of emails right away. We're like, okay, there is definitely a supply of people who would be more than happy to deliver food for a fee. And the fee is like reasonable, perfect. And so the second step, right? If you wanna talk to customers, well the , the real customers here , of course , uh, well, it's got a three-sided marketplace, but we figured, okay, people are gonna want to have food delivered. So really the missing piece is restaurants or restaurants willing to partner up with a third party delivery company. And at the time, I must admit, like I was pretty, I'm not saying I'm, I was shy, but I , I had a total fear of rejection. That's the reality of it. I just wasn't maybe mature enough or like, you know, deep enough in like the startup world where I just, I just wasn't ready to go out, knock on a door and have somebody slam a door in my face. So I did the, I , I basically did the cop out , right? I said, I said to my co-founder, his name was Lee, I was like, Lee , why don't you go out and, you know, talk to some restaurants and , and see what happens. And so Lee goes out, he does his thing and he comes back and he's like, it's not gonna happen. It's not gonna happen. Like I , I went, I talked to like maybe 10 restaurants, like half of them shut a door in my face , shut the door in my face. You know, a few of them were excited about it. And, and a few of them, you know , I couldn't even get, you know, talk to the owner 'cause you know, they were in the back or whatever it was. And believe it or not, because of that feedback, we never went forward with this idea. We missed out on an opportunity that was worth, I mean, like to the company that was in Canada that did this exact same playbook, $200 million, again, first time founders, like nothing necessarily special about it. And they told a story, like this was a story where when you launched it, the domain was through the roof. So I'm not saying it's easy, nothing's easy, but like the opportunity was there. Of course in the US I mean you got DoorDash, tens of billions just eat tens of billions. It's a huge opportunity that we missed out on. Why did we miss out on it? How come we went out, did the right thing, we spoke with customers and we got the wrong signal, we took home the wrong message. There's two reasons and it's so critical. This is the thing, like it's easy to understand the high level stuff. It's easy to say, okay, you have to talk to customers. It's a totally different thing to go from there to what it really means to talk to customers the right way. The devil's in the details. So two things that we messed up on . The first one, frankly, we just didn't talk to nearly enough restaurants. 10, 10 is a joke. Like if you go out and you talk to 10 customers and you think you know what's going on, you have no idea the number. And now I've done so many interviews, I've talked to so many founders who did research correctly, the number is closer to 500. That's how many interviews you want to have before you go and say, you know what? This is the thing or this is not the thing. Of course, like some of them, you know, in between you start to maybe chuck and jive as , and you change things up as you hear feedback. You don't just kind of do 500 blindly, but that's the number it takes. 10 is nowhere near enough. Like there's just no doubt about it. It you have to, I think we would've done at least 50 of these before we even came back and said, okay, what do we think like 50 of these conversations before we start to analyze the responses. So that's the first thing. Dataset was tiny. The second thing, this is more nuanced and even more important, it's not about the number of yeses. It is really not about going out and saying, Hey, do you want delivery? People say no. People say yes, you tabulate how many people said no and how many people said yes. And that's like the signal of how much people want it, forget it. It's about, I would argue the intensity of the yeses. Because at the end of the day, when you start off with a startup, you're going to serve only a small part, only a niche part of whatever tam . It's true that today you look at it and just about every restaurant is on Uber Eats, but Uber Eats didn't start that way. DoorDash didn't start that way. They got a handful of restaurants in a specific geography and they expanded from there. So what you need is not, you know, out of a hundred restaurants, you need 30%. What you need is a subset, let's say 10 restaurants for the sake of argument, you need 10 restaurants that are extremely excited about this idea that really, really want to do delivery. And they're gonna go and do leaps of bounds of stuff that they probably shouldn't do. That's not really all that rational because they wanna see this into fruition. That's what you're looking for 10 like idea stage partners, right? That's what your early customers are like. And so really, first of all, we should have done 50 interviews. And second of all, instead of coming and saying, well, you know, half of 'em said no, blah, blah , blah. We should have said, did any of them say yes enthusiastically? Where any of them like, wow, this is a hundred percent what I need. I've been thinking about this. 'cause if so, that's what you gotta zoom in on. And I think had we done that well, I might not be talking to you here today, , or I don't know , my net worth would be a lot higher. Let's just say that. And on, on that kind of on that line, right of, of how to do research, right? I thought that the way that Ron, the c e o of Hi MoMA spoke about that research days, what's exactly the sort of wording that I like to use. So I'll quote it directly. He said that when he was doing research, right, in the early days of Hi MoMA , I approached it from the mindset of I'm a scientist, I'm a researcher, not like I'm starting a company and I'm an entrepreneur, but more like I'm doing research objectively in the space. I want to know if this is something that's worth spending the next 10 years of my life on or not. If the answer is no, that's cool, but you'd rather know it at that stage versus after you , you've invested three years of your life into it. Like that is exactly it, that's the reality. And I think when, especially first time founder, you've just like, and I've spoken about this before, but I just think it's worth repeating the desire to be a founder when you're in that early stage, the desire to build, the desire to sell, the desire to actually have a startup is so emotionally intense that every single inch of your body wants to just push through research mode. It wants people to say, yeah, that's a great idea. You want it so desperately, so badly because A, you believe in the idea, and b, you wanna be a founder. And so staying with research mode and taking this perspective of I'm a scientist is very powerful because it lets you take your time. It lets you take your time in that research mode and you just have to do it. That's the only way that you are going to be sure. He spent like six months into this, right? It was six months of research. That's the amount of time it takes. I can tell you I was a , I was an entrepreneur resident at , at this um , like accelerator and I worked with probably, I don't know , let's call it a hundred of these ideas stage startups. Like, you know, here at Mistral we're investing in pre-seed seed, but these are like startups that already have something going. We're talking about a person with an idea. I've seen hundreds of these and I can tell you that for a first time founder, the most common mistake, the number one reason for failure by far and away like overshadows, every single other thing, is speeding through customer discovery. It's not doing true research, it's not being a scientist, it's being a founder who desperately wants people to say yes. And so every single question gets crafted so that whoever you're asking tells you yes. Like you just, you put your customers into place where they're like, yeah, okay, I think that could be a good idea. And you're like, you take that to the bank , and the reality, it it does you complete disservice because if you end up going after a startup, that's not a real opportunity. You're going to waste so much time at the end of the day, the market's gonna end up telling you it, but it's gonna take years instead of months. So thinking like a scientist, like that's really the framework. That's the best mental model that, that I've , that I've ever heard and that could ever come up with sort of thing is when you're in that initial phase, you are a scientist. You don't really know if the thing you're going after is real and you're trying to find the real truth that is your goal. If you can come outta that being like, yes, you know what, this problem I , I've identified is a real problem, or you know, I've twisted the problem this in that way and now I've landed on something that I can say with high confidence because I've done like hundreds of interviews is a real problem. Then you've gotten through that phase, like that's really what it's about in the early days. It's not about revenue, it's not about fundraising, it's not about any of the other stuff. It's about figuring out if the thing you're going after is a real problem. I told you earlier about a company, the the delivery company that I ended up not starting because I did customer discovery wrong. There's another company that I didn't start because I did customer discovery, right? Or at least that's what I think. So after I, I did Gym Track , one of the things I noticed doing Gym Track is, is just the pain of hiring. Everything around hiring I think is still super messy. And specifically like I'd done maybe 500 candidate interviews, you know, we'd hired probably 50 people or so and throughout Gym Track's Lifetime, and I was responsible for a lot of that piece. And so I wanted to figure out, you know, different things that, that we could do to, to streamline different parts of it. One of the things that I landed on that made sense to me at least was if you think about like, we'd hired quite a few junior positions and the , the thinking at least like the thesis was, look, the difference between a great junior hire and a bad junior hire is , is huge. Like the r o i you can get from a very strong junior hire is very high because the reality is unlike as an experience, like somebody 10 years into their profession, you know, there's a lot of experience you can look, there's a whole track record and , and usually the markets price those people, right? So if you're paying for someone exceptional, you're probably gonna be paying a lot more than for someone that's mediocre. At the junior level, it's not the case. Like whatever the salary is for your role , it says 50 K, that's just what most people are gonna earn. But somebody who's truly an A player will do , do so much more than a, B or C player, and yet you're paying them about the same. And so the idea was like, what can we do with that? And, and so I started exploring that space of , um, of, of hiring junior talent. And that was kind of my, my thesis. So what did I do? I , I went out and I spoke in this case with like 30 or 40 , uh, HR managers, founders , um, you know, recruiters, all these different people around in the space. And , and I think this time I really did structure it properly. I think the old me, the old me would've said, Hey, here's my idea. What do you think? Like, I would've gone in exactly this pitch that I gave you. I would've given it to them. And I would've been like, what do you think? And I think many people, because there's, there's rationality, like most of these startup pitches have been thought through. They make some sense. And I think most people on the other end will be like, wow, yeah, that's, that's compelling. Like , that's a pretty neat idea. That's something that's interesting. But I didn't do that instead of what I, what I went at and especially like founders or hiring managers, people who could be my customers. And I asked them, Hey, like, you know, tell me about your hiring. How do you do hiring, whatever, like very top level. And then I said, okay, what's your biggest pain points when it comes to hiring? And you know, typically they would be like, oh, I can't get enough. Like, you know, great candidates, okay, what types of candidates are you looking for? Junior intermediates here , senior. And almost always they were like intermediate or senior. And so, you know, we go through that and know , at some point I would be like, what about junior talent? Like, is that a problem? And almost all of them were like, nah , no, it's not really a problem. And at some point, yeah, you know, deeper in the kind of interview I would tell 'em about , about my idea, but at that point I already collected what I really wanted, which was the objective truth, right? You want to, as a startup founder, meet your customers where they are. Now, if a customer's telling you, this is not really something I think about, this is not really a problem, then they're very clearly outlining this is not a top priority, top priority for me. This is not a top of mind thing. If you were to go into that anyways and say like, whatever, I don't care. Like I'm gonna, you know, this thesis makes so much sense. You're, you're, you're kind of pushing a boulder up a hill, like that's just classic. You're, you're going against the wing because all of a sudden you're gonna have to convince your customers constantly that this is even something they should think about. This is not something you're gonna be looking for on Google. This is not something that's already top of mind that they're trying to solve. And so that's gonna be an uphill battle through and through. I did probably 30 or 40 those and uh , frankly, I shut it down like I just said. Okay, cool. It's like I wait , I spent what maybe a month, maybe a month doing that research and I decided, okay, look , I don't think this idea has legs and there's not like something I think fantastic about , about that story. It's much more exciting when you, when the idea does have legs and then, you know, you end up on a podcast talking about , how amazing the exit was or whatever. But, but this is the reality of it. Like this is the reality of founder life is like you're gonna have some ideas that are great and you're gonna have way more ideas that are not so great. I mean, most ideas are just not so great, almost like by definition. And it's your job to kind of figure out, is this idea actually solid as quickly as possible? Because I've said this before, and I'll say it again, the idea that it's all about execution is bss, it's just not real. Some ideas are solid and some ideas are bad. That's the reality of it. If you look at any $10 billion plus company, billion dollar plus company, they were solid ideas that were also really well executed. You just need both. And so in the early days, you want to as fast as possible, figure out if this idea or some version of this idea actually has legs before you start billing a deck, before you start fundraising, before you start polishing your website and all the other things you gotta do around it. The core is, is this idea solving a top priority problem for my customers? And if not, let me figure it out as quickly as humanly possible, especially before there's sunk cost . Because when you start building all the other stuff, all you're doing is convincing yourself that the idea is good. And the more you've built out, the more time you've spent on the idea, the more money you've spent on the idea, the less you want to do hard pivots, the less you wanna abandon everything you've sunk into it. And so when you start off, if right away you have that mindset of I'm a scientist, I'm just trying to figure out what the truth is, I'm not investing anything other than my time into this research and I'm coming out of here either saying, this idea is not gonna work, or I'm gonna change this, and maybe that'll work, whatever it is, I'm coming out of this with clarity of what problems my customers really have and a very deep understanding and feeling that this idea is actually solving a number one problem. The other thing that Ron said that I've heard time and time again, he said it was , it was so important, he did interviews in person and he said that seeing their , the environment that the customers worked in and that they live in day-to-day is game changing. We were able to take a lot away from that in terms of our product design. It was critical information, and I think I've heard that time and time again. You just can't underestimate how much you get from seeing or living as your customers in their day-to-day environment. The best story of this that I've ever heard is on season one, episode 21 with Mike, the founder of ada. So Mike starts like this other company is like, I don't remember, like a social search doesn't really matter, it's called volley and you know, they get some traction, whatever, but it's not, it's not crushing. At one point he discovered some problem in like the customer service space kind of feels like customer service. As he's scaling and getting more users, he's not getting a lot of like true revenue, but he's having a lot of users and just like delivering high quality customer service becomes harder and harder. Him and his co-founder decide to kind of go all in and explore this. So what do they do? This is insane because they were actually a funded startup at this point. So they're funded startup, and what they decide to do is they decide to get employed like Mike and his co-founder decide to get employed as full-time customer service agents for a bunch of companies. And they start working full-time as customer service agents to understand what these people go through and what that job is like day to day . I mean, they literally, they, and they did this for a year and Mike said to me, he said, I lived and breathed customer service for over a year. That's just insanity. , like that level of focus is truly insane. But what happens, what happens is they understand, and they did it for multiple companies, so they start to get a clear picture of what it's like to do customer service. They start to see that, in fact, a lot of the things that customer service agents do is repeatable and automatable. And so they start to literally automate themselves out of the job. And when you do that, like you clearly know that you're solving impactful problems because you're doing the work. And so you literally are like, that feedback loop couldn't be any tighter. You're seeing that every single thing you automate is helping you not have to, you know, like it's helping you do more with less. And you can clearly see the benefit of that for the, you know, the business for the organization that's employing you. And out of that came Ada, like that became a chat bot . This is many years ago. This is like, I don't know , 2017 or so. Out of that came ada , which is a chat bot , which is now worth over a billion dollars doing like 50 to a hundred million dollars in revenue. That's the power of understanding your customers at the deepest level you possibly can. The other thing I'll mention is, and I kind of touched on this earlier, but when we talk about research and we talk about, you know, doing it the right way, spending the right amount of time, how much time are we really talking about? Well, when I asked Rod , I said, you know, how long did this kind of research process? He said it took three to four months of like just the interviewing, and then another two months actually said two to three months to build just version one of the M V P . So in total of those , it was about six months from when they like had the original idea to having M V P one. That's the amount of time that we're talking about is months. And usually, like from what I've seen, we're talking six months is pretty common, four months, six months, seven, eight months. That's the amount of time it takes to do research properly because you have to literally like figure out who you gotta get in front of, get in front of hundreds of people, go back multiple times, refine kind of your, at first your interview, like literally refine your interview, think through your interviews, and then start to pitch ideas and refine in different ways. You've gotta tweak kind of the wire frames and all that stuff's just, and then of course you gotta hire people and like, well , at least bring co-founders or whatever it does . You need to like get the first M v P done. This stuff takes time. This is not a matter of weeks. Like the idea that you could have an idea and , and this is where like the, I think the expectations versus reality comes in. If you read something like Four Hour Work Week or Lean Startup , I think it's easy to fig to think that, and I , I certainly fell into this like, read this thing , you're like, wow, like everything is testable. Like I could just have an idea, put up a website , put up a landing page, and like boom, I'll know if it works. Like that is just from what I've seen. I mean, that's almost never the case. It takes so much longer to figure out if something that you have, 'cause whatever idea you originally have, that's probably not gonna be what, what is truly real, but you're going to , you know, tweak that along the way and just all those, it's a process with a lot of iterations. You constantly are coming back and fine tuning , fine tuning , fine tuning. It's just not as easy as putting up a , a website and like some, you know, words and like ab testing words and hoping that like, that's gonna translate to sales. You've gotta get in front of people, you've gotta talk to them, you've gotta have these interviews. It's many, many months of work. So like my point is just be ready, be prepared that that's how long it takes to find problems worth solving. If you listened to this episode and the show and you like it, I have a huge favor to ask for you. Well, it's actually a really small favor , but it has huge impact. But whichever app you're listening to this episode on, take It Out, go to Product Market Fit Show and leave a review, please. It's going to help. It's not just gonna help me to be clear. It's going to help other founders discover this show because the algorithms, whether it's Spotify, whether it's Apple, whether it's any other podcast player, one of the big things they look at is frequency of reviews. Even if you're just writing like great podcast or I love this podcast, whatever it is, just write a few words. Obviously the longer the better, the more detailed the better. But write anything, leave five stars and you'll be helping me. But most importantly, many other founders just like you, discover the show. Thank you.
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