A Product Market Fit Show | Startup Podcast for Founders
00:10:59 · Dane Atkinson
[00:10:59] S0: It’s hard now to actually say ego plays an even bigger part of that, because one of the nice thing – one of the challenges in building capitalized businesses is that you really want to live into the promise you had with your investors and your team, and getting usage on freemium feels like you’re winning. Now, I’ve got actions. People are looking in analytics. They’re printing reports. You’re doing things and everyone gets excited. Your board writes your bigger checks, like everybody’s leaning in, but you’re lying to yourself because you haven’t closed that loop. A lesson that I learned from Squarespace, and I probably shouldn’t get much closer to my heart, was we originally had, or during the cycle time, a 30-day trial. You build your site and everything else, and we quickly discovered that the length the trial actually was inverse effective. The shorter we made the trial, the more customers converted. The corollary to it, successful conversion was actually number of modules. In this case, at the time I was there, how many different components to the site? What was your investment as a buyer that I made into the product would be a better threshold for conversion than anything else. We started engineer. How do we get people to upload content? How do you get people to really feel attached to it? When you get, which my next chapter, my ego or just a successive hat through life got in the way, I’m like, people are fully engaged. It’s going to be a obvious conversion. I think that something to keep in mind is when you’re building these things, you really need to pressure test what is the future you will pay for. I think that that rope is almost always better, tighter. People do give way too much. Very quickly, when folks to the platform, and they get their thesis or the vision behind the company, they’ll decide, okay, I want to go in or I want to go out. Making them have a year and a half free and then the third mail button costs money. It’s incredibly hard. Because also the psychology is now this platform’s free. Slack was brilliant because their strategy was less about the threshold was not good in market muscle. They really found a way to get infection inside of corporate buyers through consumers.
00:12:51 · Pablo Srugo
[00:12:51] S1: Tell me more, actually, just on that Squarespace one, because I found that interesting. Why would letting somebody have a 30-day trial versus a 15-day trial actually lower conversions?
00:13:00 · Dane Atkinson
[00:13:00] S0: It’s interesting because we had the same thing in Shopify. Not we, but as part of that environment. They had found that much like we had five modules, when you had a customer make $25 off their website or something like that, then they would really feel fine paying the fee and going forward. Same thing for SumAll, we found out [unclear], five different businesses that we hit a critical value that they would even pay for it because it just hit that space. I think it’s very, very hard if you’re trying to make a trial based off time to know where that psychological point is. In 30 days, in a lot of ways, someone would get all excited. I’m going to sell scarves online. They would work on it for three or four days, and then life would get in the way. Then a month later, they get an email being like, hey, your website’s up for payment. They’re like, oh, I’m going to go back to it in three months when I get a better break. But that first seven days, you’re like, oh, is it working? I can see it. I can visualize it. Actually, your mental attitude was the investment I’m making versus the time I’ve spent is high. Vastly, I can pay now because I can extrapolate a future. Customers who did pay obviously would end up feeling the commitment and that payment as a reinforcement of their energy, and usually more energy in a gift to be more successful. It became 14 days, and 20 days, and 30 days. There’s definitely customers who would continue to invest in that period. But a lot of people just got and they’re like, this is going to always be here mentality and wouldn’t convert. Statistically, and again, this is a while ago and a lot of things have changed in the world, but a couple companies that I help advise now set a similar pattern. You actually will see a spike in decline. It’s a long tail, too. A lot of those customers that wouldn’t buy in 30 days would buy in three months because they come back and be like, oh, I want to do it. Exactly what that threshold is, it’s difficult. Even as an operator, as a business, one of the things that makes a shorter trial really helpful is when you’re trying to test what is driving conversion. If you think your cycle time is 30 days, your iterations are also in 30 days. Let’s promote -- in myday, we launched a WordPress importer. Sounds insane now, but you would move your WordPress content into Squarespace. Did that work?
00:14:58 · Dane Atkinson, Pablo Srugo
Because you couldn’t tell for 30 days because people would just wait out the trial. You’re like, oh, we have to wait to see if that one would work before we introduce a new feature. Having a short trial window and you could just try things and try [unclear]. [00:15:12] S1: It’s a tighter feedback loop, and it makes sense. You’re almost like leveraging momentum. When somebody signs up, that’s when their peak interest. Make it frictionless for them to get some value. Once they get some value, then get them to pay. Then like you said, now they’ve committed so they’re going to deploy more time into it and you get the positive flywheel spinning. [00:15:31] S0: That’s gyms, right? It’s the whole thing. Building habits takes energy, and you have to think about where you want to catch in that cycle. Different businesses obviously have different cycle times, but I would say most of those folks out there in the early stage, especially as you want that iterations to be tight, don’t get long trials If you can avoid it. Try to make that as quickly as you can, because also you’ll also see if you actually have something you’ll pay for it. [00:15:54] S1: Let’s jump now to Odeko, your current startup. In a sense, you stayed in this SMB world. I get that existing theme. You’re going from data analytics to coffee shops. Bridge that gap for me. How do you end up there?
00:16:10 · Dane Atkinson
[00:16:10] S0: Actually, I took back. We sold SumAll, and then we took part of the tech stack team. We had this great partnership with Square and Toast, and those folks, and we started out as geeks. Could we use that data that had usually been invisible inside the industry of brick and mortar because they have less technology, surprisingly, than a lot of other sellers or categories and do something productive with it? We built this, and here’s a great idea. Failed product market fit. We built a predictive model. It used to be called machine learning loops. Now, it’s called AI because it’s sexier. But it was very effective at understanding the future sales that we go to a coffee shop, [unclear] being the early customers of ours, and say like, we know what you’ll sell in a week. We can reshape your ordering behavior, and your staffing, and everything else to utilize that forecast. They loved the idea. They used it. It saved them waste. It made their business better, but it was a fraction of the problem. As we sat there with our customers, the vendors wouldn’t deliver after we put the order in for them to deliver. Or they would come in the middle of business, or they would have reconciliation problems and tons of invoices, or they would steal money. We were shocked because we were tracking the data, how systematic a lot of the industry had to be like, oh, these property bags are $18, and then two months, they’re $23. Who’s checking the invoice? It went to $23 and it was obviously intentional because it happened to all of our customers. It seemed that would be useful in of itself, but the real problem was that they needed infrastructure. Having had the experience of getting excited about software was able to break the VC pressure loop. It wasn’t easy. It was super duper hard, because again as a founder, you come to this thing often with either an idea that you’re fascinated by and you think the idea is it, or you’ve made a promise to your investors that you’re going to deliver on the solution. We had sold some of our most amazing investors on the idea that we were going to bring AI to an ancient industry and make them more efficient. Those would be a pure SaaS, gross margins in the 80 percentile. Everyone loves it.
00:18:19 · Pablo Srugo
[00:18:19] S1: Just for background here, you raised a $6 million pre-seed, I assume, at idea stage, just giving your background, and that was kind of the pitch you delivered.