A Product Market Fit Show | Startup Podcast for Founders
00:48:23 · Sean McCarthy
[00:48:23] S0: We intentionally insert two wow moments in the demo. Essentially, we have a couple of different demos, but the first is around the intake from, we can show voice or email. Voice tends to get a better wow factor where it can be in a warehouse. You know, for a lot of our customers that are at a loading bay, and calling in with a problem. And then very clearly, they're able to articulate what's happening, but then the AI will start to go chase the information. So send a Slack to Pablo, call Sean, log into FedEx, like all at the same time, to pull this route to result. And that is happening before their eyes, so that's been powerful for them to start to see. And then the second and kind of ending part is the resolution. So now we've got all this aggregate information, we have enough to solve, but it shouldn't still go to a human for then a human to input into a system. The way that this should work is that we should be able to update QuickBooks or the ERP with the financial outcome and then update the warehouse management system with maybe the relevant stock or whatever happened there. And so, actually showing the systems being updated and the ticket being resolved across the board. And so, we try to always have at least two wow factors in the demos and even the custom demos that we do. So that they can understand not only what this looks like in practice, how their customers are going to utilize us, but internally what it's going to look like as well for them. Because I think those are two different experiences. They're worried about the customer experience, but they're also worried about the employee experience and so I think if we can make each wow factor around both of those elements, it usually sits really well.
00:49:59 · Pablo Srugo
[00:49:59] S2: And then from there at that point you have interest. You're trying to go to something, probably like some kind of a pilot and the biggest thing I found is just the challenge, like the failure mode is you just get stuck somewhere or it just starts taking too long. And, you know, time kills all deals, priorities change, whatever. Because you're already in at that point. Clearly, they like what you have. What have you found works in order to shorten the time between interest and some closing of some sort, even if it's a pilot?
00:50:27 · Sean McCarthy
[00:50:27] S0: I think the pilot thing for AI startups can be very dangerous and we've learned with lessons too. I think, you know, when we look at those pilots, and what I say by learn by lesson. You don't want to after the pilot be in this purgatory of, where is this going to go? Yes, we're going to go to commercial contract, but that's got to go right back through legal and you know, you might be still having your solution deployed. And so I think it's a dangerous area. The way that we do, we always try to push for a one year contract. But if we have to do a pilot with many of these large enterprises, they require some sort of observation phase. We'll build the pilot into the one year contract. So it's a one year contract, but it will include a thirty day pilot, sixty day max, but thirty day hopefully pilot that will auto convert to a one year. And that way, all of the legal documentation and infrastructure and all of that is pre-approved, it's all part of the normal agreement, and everybody's on the same page. Obviously, you need to make sure that you deliver in that thirty or sixty day window so that you can get that auto conversion. But that's hands down the best way and to answer your question, when you talk about like, how do you get it, that's a really good way. Because it still is a light enough ask to the customer, their feet aren't necessarily held to the fire if they don't like it. But on our side, we've got some insurance that as long as we do what we said, we have that commercial agreement.
00:51:45 · Pablo Srugo
[00:51:45] S2: So I love that idea. But between them saying, yeah, okay, this is interesting and then them signing that one year contract with let's say with a pilot out.
00:51:53 · Sean McCarthy
[00:51:53] S0: So number one, making sure that the use case that you're talking to them about. I do this whole analogy with our customers. So I'll say, all right, so one to ten. One, it doesn't matter at all to the business. Ten, business goes down tomorrow. Where is this use case for you, right? And you're hoping for the seven, eights, nines, tens, right? Being realistic, they're probably going to give you a seven or an eight, hopefully as kind of like a max starting point. They might not give you the most important critical thing. But if they say, oh, this is like a two, right? Or a three, you shouldn't take that use case. Especially as the first one, because it doesn't mean that much to them. It's not going to make that much of a difference and your pilot is probably not going to go very well. And so what I'll couple that with is, let's say they give me a seven. Okay, great and then I'll ask, how many times a day does this happen? That's the other thing. You don't want it to happen once a month or four times a month. That's also bad. So hopefully it's happening every day. It's a seven, great. Where does this fall for you guys on a prioritization scale? I mean, is this painful for you right now? And if so, you can kind of quantify and back in and on the ELT side, they'll say like, yeah, we're losing money on this. So this is high priority and often they'll say, yeah, this is high priority. We do need to get this fixed. Great, well, let's get it fixed. We can actually do time to value here in probably three or four weeks to get the initial use case handed over to you guys. You can measure it. You can measure down to the second how our AI works. If it's monetary, you're going to see what that is on our dashboard. And you'll hopefully be able to fill the gap here. And this is the best way for you guys to just measure fast. And that's usually where we're pushing it again, especially if we have to get them into a pilot. But if you ask them, how big of a priority. Especially if they're giving you those six, seven, eight, nines, they're going to tell you it's a priority and so you can play off of that. Like, hey, you just told me this is a really high priority. So let's get this in flight for you.
00:53:40 · Pablo Srugo, Sean McCarthy
[00:53:40] S2: Perfect, let's stop it there. I'll ask the last question, which is what would be a top piece of advice? Maybe a piece of advice you wish you knew when you were starting, you know, two years ago. [00:53:50] S0: I think the biggest piece of advice is to be honest with yourself as a founder as well. It's very easy to convince ourselves that either the problem that we're solving is really, really mission critical. Even though it might not be, or that you get one customer telling you that it is like super important to your business. You just take that and run as a blanket statement for like that entire vertical. Because one customer told you that. I think you need to make sure you do enough diligence and be honest with yourself on a retro the feedback that you're getting. And I tell you that is like an important lesson because I've made those mistakes in blitzing our entire team based on one or two customers telling me some product feedback and going off the rails. And quickly learning like it was just those one or two customers. It was nobody else that needed that and so I think that that principle from the very earliest stages, like you're trying to raise a pre-seed round and just figure out what you're going to do. All the way through, even past where we are from an organization, you have to make sure you have a decent sample size and that you operate off data, and not gut checks. And that's been, for me, probably one of the most powerful lessons. And frankly, one that, you know, I still make the mistakes on today.