Mark Roberge breaks down when a company is actually ready to scale. Use cohort data like customers sending 2,000 team messages monthly to prove product-market fit, then validate that go-to-market fit means scalable unit economics, not just profitability. Model your LTV:CAC ratio by decomposing it into contract value, margin, churn, and sales costs.
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I guess the other thing that I see here too is like, don't fall into like analysis paralysis in choosing this. Don't take like 2 months to pick this. Like literally sit in a 3-hour meeting and debate it and pick one. Setup rate, weekly active usage, contact lift, like transaction levels, whatever. Pick something. It's better. 90% of your peers are choosing revenue, and it's way better than that. So just pick something, and I'll show you why it's okay. You're not going to be— it's not going to be a problem if you're wrong on exactly what it was. Okay, so here's how I like to measure it in sort of customer cohort by when they were acquired. So let's just— this isn't Slack's data, but let's pretend it's Slack, right? So 24 customers were acquired In January of last year. A month later, 3% had sent 2,000 team messages. 2 months later, 27%. 6 months later, 39%. That's not good. Like, if you're Slack, a collaboration software, and 6 months in, your customers are only 39% are sending 2,000 team messages, you don't really have a company. But like, yeah, by September they made a bunch of changes. 50 customers signed up, and by month 2, 68% had hit that target. So they hit product-market fit somewhere in the October timeframe. This analysis allows you to see how you're improving in your pursuit as a company. The aggregate number is going to be hard to move over time, but this number you can move month to month, and that's very motivating to the team. Now, in terms of checking it, so now it's a year later, did you get it right? Remember, don't over-obsess over Choose something related to customer value, success, usage, etc. And a year later, we can see how strong the correlation is. So a year later, this example, they had acquired 68 customers a year ago, and 82% are still around. Now, of those 68, 55 hit the leading indicator of retention, sent the 2,000 team messages in the example we're working on in the first month. And for those that did, like 93% are still around. 13 of them had not, and 39% of those are still around. So that's a pretty big difference. We learned something huge about our business. If they send 2,000 team messages every month, there's a 93% chance they're going to be around for the long term. And if they don't, there's a 61% chance they're going to get out of here. That's powerful. Now, at the bottom example, it's the same data set. 68 customers signed up a year ago. 82% are still around. 55 hit the lead indicator. Of attention and 13 had not. The only difference is the retention rates of those 2 cohorts is very diff— is not that different. So it's not the lead indicator of attention, it's not the 2,000 team messages. But now we're sitting here a year later, we have a bunch of other data to analyze. Maybe it's more about the number of users that use Slack. Maybe it's like they need to have 10 or more users on it as opposed to the number of messages sent. So we can do that analysis in a day and figure that out, right? So, so that's how we can understand and validate Later on whether we have the right one. So that's how I think about what is product market fit. I don't think it's a revenue line. I don't think it's a feeling of like a pull in a market. I don't think it's a survey. I think it's based on your leading indicator retention. So that was one of the key questions we're tackling is, are we ready to scale now? And I would say no, because notice during the product market fit story, like, I didn't really say anything about profitability or scalability. In fact, I subscribe to Paul Graham, the founder of Y Combinator's guidance, which is do unscalable things early. Beautiful. During product market fit. I mean, you know how many entrepreneurs come up with an idea and never get customers to see the value they envision? Do you know how hard it is to come up with an idea and get the majority of your customers to see that vision? To realize that value. If you do that, you have experienced something that so many people wanted to experience and never did. So you have to throw everything in the kitchen sink to make that happen. David Cancel, the founder of Drift, who I helped out during that stage, and he's been a good buddy for a while, he was literally flying to onboard customers that were paying him $50 a month in the early days. months of drift. That's beautiful during the product-market fit phase. It doesn't scale, but it's beautiful. So if we check that off and now we have proven, okay, if I put 20 customers into this this month, 70% or more are going to be successful, beautiful. Now we have to prove that we can do it scalably, and we call that go-to-market fit. And we usually measure that as unit economics, not GAAP accounting profitability, because GAAP accounting profitability includes all the costs in your business, whereas unit economics isolates the costs that are necessary for scale. I think you've all heard the term unit economics. You probably all measure it. So now we just have to prove that we can do what we did in the product-market fit phase in a scalable way with good unit economics. Just like the retention, we need to understand what the leading indicators of unit economics are. Now, that's more of an algebraic process, which I'll kind of walk through here. But essentially, when a 25-year-old account executive joins your company and they're like, what's my job? You basically— it's like to have an LTV to CAC greater than 3. That's the job. But no 25-year-old account executive could understand what to do. So we have to algebraically extract that target back to meaningful activities like leads and cost per lead and close rates and average sales prices. That's what we do here is you take LTV, which is usually represented as average contract value, the annual contract value times the gross margin divided by churn. You take the CAC, the customer acquisition cost, and extract that back to the CAC to generate the demand and the CAC to sell the demand. The CAC to generate the demand is the cost per lead divided by the close rate and the CAC to sell the demand is the cost per salesperson divided by how many customers they acquire per month. And the customers acquired per month is how many leads they get times the close rate, or how many leads they create for themselves times the close rate. So now I've been able to extract this, you know, number that we understand, but we don't understand the ingredients of it back to a true business model that we can pump in. It's like, listen, if we, if we can get these sales for $20,000 each, a 70% growth margin with a 5% close rate on leads and a cost per lead of $1,000, that spits out a good business. Now I can just dashboard it and see, like, I just need to keep the blue line above the red. As long as it does, I'm going to have good unit economics in a quarter or 2, as long as those activities do. Now, it's not going to come out perfect. Your sale price might be a little higher. Your close rate might be a little lower. Your average lead cost might be a little higher. You know, and you can start playing with the model and understand if you have good unit economics, i.e., go-to-market fit. But once you do, you know, going into the next month, like if you're going to sign up 30 customers, not only are those 30 customers, most of them are going to realize the value of your business, of your, of your product and retain. But you also know that you can do that with strong unit economics, profitability, and scalability. So that is my answer to when are we ready to scale, is when you have product-market fit and go-to-market fit, and those need to be optimized in sequence. You can't work on go-to-market fit before you have product-market fit because you will likely optimize your go-to-market strategy on the wrong market with the wrong product with the wrong message. You have to do them in sequence, but once you have them, you are ready to scale.
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