Michael Margolis: observation

Transcript context

…Let me just give you an example. I think a lot of this stuff we're talking about, it starts to get a little abstract. So I was working with a company that was developing a new delivery service for people who have specialty prescriptions, medications. So these are the kinds of medications that are expensive and for very specialized chronic diseases. This is not the kind of thing you're getting at Rite Aid. And there's something very special about this company, and then I can mention that afterwards. But the fundamental thing for them to figure out was, before they can build out the logistics of this, they're trying to figure out, "Do we need to target something that is for delivery like ASAP?" These are really important medications for very serious diseases. Is it like, "Oh, my gosh, I need the next pill. Get it to me as fast as you can"? Or is it like, "Well, I can wait till a day or two, but I need it between 2:00 and 2:15 PM," like if I knew that? And then who exactly is this bullseye customer? We want to know, what's really the fundamental issue or problem that we're solving here? And so they wanted to answer those questions. And so we go through this process, and so those are the key questions. And then the customers that they're after, I know, okay, well, it's not going to be everybody with specialty medications. And so as we start teasing through that and thinking about it, I want to think about, what are examples of other products that somebody has used that would make them more likely? So a good example there is, have you had other things delivered? Food? Have you gone through this kind of process before where you've used like Uber Eats? Because if you have never had anything delivered like that before, that's going to be too many humps to get over to get the person to accept their medications coming by delivery. So they've probably used Uber Eats or something like that, and they've been on the medication for a certain amount of time. So it's somebody who, this is kind of a chronic thing. It's not like a one-off acute situation. They needed to find people who had a certain kind of density, so how rural were they living, how urban was it, because of the way they were going to do the deliveries, somebody who was responsible for their own medications. So we don't want somebody who's in some kind of a healthcare setting where somebody else is taking care of it, or maybe their spouse or partner is managing their prescriptions. These are the kinds of things that we're starting to look for. And another typical exclusion criteria is I don't want somebody who knows too much. Your core bullseye customer, I want somebody who's pretty typical. So in this case, if I were to find out that somebody was a pharmacist or worked in healthcare, they're like, "Oh, yeah, that's probably not a typical customer. If I just have these five precious interview slots, I probably don't want that, so I'm going to exclude those people." d in healthcare, they're like, "Oh, yeah, that's probably not a typical customer. If I just have these five precious interview slots, I probably don't want that, so I'm going to exclude those people." So we went through and did this and then generated these different prototypes to express a range of different recipes of value props and what this might be. So the range is things from, it can be delivered in an hour or it can be delivered over a four-hour window, or it can be delivered, "We'll get it there as soon as we can get it there, but we're not quite sure when it'll be coming. You just have to be home and available," these kinds of things. So went through this exercise, and what rose to the surface as we were doing these is that there were certain customers for whom this was a much, much bigger issue, for whom they needed to be there and know when this thing was showing up. It turned out having that distinct window, a predictable, narrow window of when this was going to arrive was much, much important than ASAP. These are important medications. They're not waiting until the last pill is gone. That's not what's happening here. But knowing when it was arriving... And it turned out that the scenarios where that was critical was things like, it's a refrigerated medication. This can't be sitting out on my stoop, right? It's cold chain. Or there's for some reason an issue where I'm especially worried about theft or something because of what the medication is or where I'm living or weather. So there are these very particular scenarios. So then going back to this idea of the bulls-eye customer, you realize, "Oh, wait, so it's a subset of customers who have refrigerated meds. That seems like a much higher value problem that we're solving here." And so we ended up running this again. So I re-recruited with people who had that subset of kinds of medications and issues and also were dissatisfied with the status quo of their existing service and were not available to just kind of be around. So they were busy and whatever, and they needed this window. So we ran it again. We were like, "Oh, yeah, there it is." So that second group of people, you just start building this confidence in the match between what you're building, what the problem is you're solving, and who exactly you're building it for. And in that case, you could see, "Oh, yeah, that is the right bullseye. That's why there's this very narrow, specific group who's much more likely to adopt this than everybody who has specialty medications, because the need is just much more acute." I love this example. Intuitively, it all just makes sense as you describe what you landed on. And this is what people call product-market fit, what you're describing, where somebody has a pain that you are solving and they need it badly. What does it look like when you find that group of... What do you notice qualitatively, just like this tells you this is it, this is the pole that people talk about when you say product-market fit?…

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