Why Startups Fail: A Look Into Product-Market Fit

Rob Kaminski: Hey, everybody welcome. Uh, super thrilled today, Ryan and I have Craig Zingerline of growth university, joining us on exploring product. Uh, this is going to be a fun one. Greg. I got a good feeling about it. We're going to dive right in today. Craig, I think the best way to introduce yourself to our listeners, uh, is to tell, uh, kind of your story around startup journeys.

And I know we're going to get into some good stuff around growth metrics. So, welcome. 

Craig Zingerline: Thankyou so much. It's been great to meet you all kind of and doing all the stuff that you talk about before you go live. Um, and, uh, I'm really thrilled to be here today. Yeah. And I'm, I'm really here to talk us through a couple of stories that I have around startup success and failure and give you my perspective on it.

Uh, my really quick overview for today is that we'll talk a little bit about my story. Some failure metrics and analysis and product market fit questions. We may look at case studies acquisition, and then it's the end. So if you're with us by more than I thank you in advance for that, uh, well, here's, here's my story.

So it's 2004 and Facebook has just been founded. And flicker launches and Firefox 1.0 comes out and flash happens to be all the rage. So going back in time here, web standards are just forming. There's not a lot out there, like it's kind of the wild west. And so myself and a few others, we take the plunge into a hot new market.

We, we said, you know what? We're software engineers, we're developers. We're going to get into content management system development, and we have this amazing. Okay. This was a revolutionary idea in, in a way, an innovative way to create and publish content and get it out on the web. In fact, this product you could actually right click rate in the content well in a browser start typing way, right.

Click and save it. I mean, it was kind of magical from a product experience standpoint. This was before no JS and all the amazing server side JavaScript stuff that's available nowadays. So we were really innovative and thought, Hey. This is really gonna take off. So we, uh, do what all great founders do. And we convinced some of the best people we know to join forces with our vision.

We start a startup, right? Let me see where this is going. So what is our value? Well, we make the creation, editing and publication of content easier and more fun than ever before. And our model was of course, an enterprise level model, because there was nothing at the time that would let you easily put out content on.

So we thought, okay, well, we'll charge about $10,000 per instance of this thing. So what do you do? This is actually a screenshot of our, uh, office space in Kendall square in, uh, in Cambridge mass, really kind of before it became like the trendy really cool place that is now. We spent 18 months building an absolutely phenomenal, amazing product, and we actually get some customers.

So you see ICA Boston there, the museum of art, Athena health was one of our early customers. Uh, Boston sailing center, I think is that third local there. So, so we were successful. We got a few customers using this thing. Not as amazing as we thought it was. Okay. People love the interface. So the innovative things that they, they actually liked it.

But what we realize is that we're now spending a hundred percent of our time building those core features. To just support the product and the needs of our customers. And it's never enough. We keep building, we keep building, we keep building to support those needs. And what we realize is the license cost that $10,000 fee plus a monthly, it was just too much money for the value that we provided in a year later, we're out there, we're scrambling and hustling for consulting gigs, and we pivot the company to do service work, and then we shut it down.

Now we shut it down. So. The hell happened. So we had our heads in the sand, in this race to build this really cool thing. In the 18 months, we were heads down. We built a bunch of features to support a handful of early customers, but we missed what was happening in the market. And it turns out that there was something huge brewing called the open source.

And not only that, we also had Squarespace start, I believe in 2004, 2005, Drupal, Mambo, WordPress, and, you know, Eat our lunch. So what happened? Why did we fail? The market was forcing the prices down. All of a sudden $10,000 was competing with free or cheap. And the open source content management system was, was basically just eating the world.

We couldn't react fast enough to feature requests, to compete with those open source products. And by the time we did catch up with our team of, I don't know, eight or 10. Barely banned ourselves by the way. And we still couldn't figure it out. Our features didn't matter. Uh, we couldn't monetize them fast enough and we did not test pricing early features, customer segments.

We basically just did not get a signal fast enough and adjust to the needs of the market. So I like to say hindsight's 2020, right? Like you make one mistake and you don't do it again, but this is the world of. I guess what I did it again.

Ryan Hatch: It sounds familiar, man. We've been there. 

Craig Zingerline: So I just want to queue this up, right? Because I've been in this industry for a very long time. I've run a couple of agencies. Now I'm on the other side where I'm embedded in startups all day long. And I set out on a personal mission after basically failing. Horrifically twice and actually having a bumpy ride a number of times along the way, as long as some, uh, nice little exits and some wins, but what, how do we quantify why this keeps happening? Why do startups fail? It became a personal research project of mine. And, uh, that's why we're here today. 

Rob Kaminski: Awesome. I love the intro, Craig, the level of humility and honesty in this there's lessons in there alone. That's right. I'm curious when, when that self-awareness really came about for you, I know we're going to get into the weeds and kind of how you got into that, the research of all this stuff, but even in those that failed. Were you calling him failures when they happen or were they, you know, delayed successes or we'll get there next..., 

Craig Zingerline: oh, such a good question, man. We're getting really vulnerable here, aren't we.

Ryan Hatch: If we can just do some services work, we can keep this alive. 

Craig Zingerline: That was the game night. That was the, that was the game. So I think with the content management system, you know, Interestingly enough because we were paying ourselves so little. I actually, so I was living in, uh, outside of Boston.

I play the drums. I started a cover band to make money nights and weekends to supplement income. Uh, I had just met my future wife at that time. We're trying to figure out like what we're doing with our lives. And I think when, uh, it became apparent when we fully ran out of money and then I closed like a ginormous. Consulting gig for the product company. And I had to go work out of some office in like the Fort channel area of Boston. And at some point I was like, what the hell am I doing? What am I doing in my life? Why am I doing it through this product company? That basically felt not to say it wasn't fun. I met great people along the way, but I think it hit relatively hard, but I don't know.

I think I justified it at the time if I'm being really kind of, you know, if I, if I'm. Remembering back correctly, which, you know, a memory sometimes, uh, does us a disservice, but, but I think I had some, some level of self-awareness at the time, but it didn't feel like a total, an epic failure because we were able to transition into this consulting model.

So we, we opportunistically had that. And then I, then I moved into like building my own agency. So it was, it was tangentially related to the thing that I did. From the outside. I mean, when I look at it now, it was a total flop and, um, it, in the sad thing is it probably had more potential than, than we than we gave it credit for because we built some cool stuff.

But the problem was, we just didn't get in front of the market. The second time was a whole different story and that's kind of an ongoing thing. So.

Well, yeah, so it's 2015 and I had this, um, I had been nights and weekends w been working on a, um, kind of on like a marketing platform meets like campaign engagement platform. Um, it was originally called BRCA tiers and then we re re re re. Devotion potion.com and it's actually still alive companies, still alive.

They're still, customers are still clients. They're still happy people using it, but we never reached any level of escape velocity. And the quick story there was, um, I had gotten all this experience. So I started out as a, as a software engineer and then moved into product management and then had done a bunch of stuff with agencies, uh, had spun up to one agency on my own.

When I moved to DC, came into a bigger agency and help that scale and grow. So I had all this experience kind of on the build side, on the product side. Um, but then I really wanted to understand kind of the fundamentals of, of growth and, and growing companies. So I joined a startup early and then I had the entrepreneurial bug.

I had this thing going nights and weekends that was starting to get some traction with these bracket based voting campaigns. We actually got written up in sports illustrated, believe it or not like back in 2012 or 2013 when it was purely a side hustle. So I took down, I said, you know what? I think I can build a business out of this.

So what does one do in that situation? You go raise money. Ooh. So we, we entered, uh, an accelerator and we raised around capital, but, but we raised the capital on the promise that we could basically grow additional product lines within. This ecosystem that we're trying to build, but we had product market fit.

We had lots of traction with a single product, but between the pressure that I was feeling on the investor side, and also trying to convince myself that we had to build something big, that was venture scale. As a business, we started trying to go really, really, really wide. And we built more and more products kind of adjacent to that core product that we had built thinking that if we build all these things, The enterprise customers that we're going after are going to say, oh, of course, I'm going use this in, in in fact, some of our early adopter customers on just the, the product was actually a bracket product.

That's the one that we killed everything else off right. In the last few years. And now it's back to the basics we thought, okay, well, if we have these additional products, um, we can scale this business up and we're going to have all these different, you know, solutions that different problems that marketing teams have.

The problem is, is we went too wide and we didn't go deep enough in. I got very aggressive with pricing. And again, this is a big lesson learned. I had some signal from our customers that were paying us monthly on the, on the single product. And I said, Hey, if we build these things and by the way, they're telling us some of this stuff, they, they want us to build.

If we build these things, will you use it? And they say, yeah, of course we do that. And we heard this over and over and over again, but I didn't get that. So we didn't, we didn't ask for money up front. We didn't understand how to price it. So basically what I did is I, I doubled or tripled our pricing overnight.

And not only could we not get new clients, we lost the clients that we had because they were like, well, this is kind of sketchy that they're trying to really upsell us. It just was a really bad scenario. And that. Really felt like a total failure. Uh, and again, we resurrected it and it's still in a state of generating revenue now, but it's back to that original hypothesis. We, if we just simply would've stayed focused, this thing probably would have taken off. 

Ryan Hatch: Can I ask you a question about that? There's two things that are really interesting to me about that one is that you felt pressure to get to venture scale. And the other, and then that influenced a whole bunch of decisions.

And then the other one was like, how you talk to those customers about if we build it, will you buy it? Right. But I'm interested in the venture scale piece. I know we want to talk about failure a little bit more here, but just on this, can you just describe a little bit about. Where do you feel that pressure came from you had a successful single product, past product market fit.

You had customers. Where did you feel? What caused this pressure to feel like I need to blow this thing up and go wide and go multi-product and go enterprise. What, what would you, what drove that? 

Craig Zingerline: A number of things. So, first of all, I was living in the bay. And I was just fully immersed in the startup culture ecosystem. And while I had a background like in bootstrapping companies, actually, uh, I had an opportunity to raise capital and, and do it relatively quickly. And when we did that, a lot of the feedback from the folks putting in money were that, look, we want to see a bigger vision here. We think this can be bigger.

We think you think this can be bigger. And I actually thought it could be bigger. So a lot of that pressure to scale, I call it the venture scale was that. Our total addressable market off of that, a regional product was relatively small. It was a very niche product. Uh, it's the type of product that you see a lot of, like if you're following a micro acquire and kind of what's happening in that ecosystem, uh, you know, which growth you, my company, actually, we just bought a tiny startup off of micro acquire and we're going to grow it in public.

So if anybody's interested in that, we're going to kind of share the journey of how to grow one of these startups, but. The, the company at the time would have been a great fit for something like that. It would have been a great lifestyle business, but again, when we made that decision to just go deeper, like we had the desire to grow it into build a big company.

I'm like, I've built companies that have gotten big. Right? Why can't we do that again with this one? So there was that external pressure and there was a little bit of that, uh, internal pressure in any kind of came from all angles. I think my co-founders actually knew more intrinsically than. As like the product lead on it, that, that we probably should slow roll this thing, but I was really aggressive with trying to move it in scale it, frankly way before we had any sense of product market fit on, on the rest of the products side of things, it, it was, it was soul crushing.

Rob Kaminski: Hmm. Yeah. 

Craig Zingerline: The question I think was around talking to customers.

Ryan Hatch: Robert anything on that before we switch to that topic? 

Rob Kaminski: Uh, no, I think Craig when we connected. I think my favorite thing about your approach and the stuff we're going to get into today is that those experiences and your awareness to that really brings a, I think, a unique angle into, into the why and why that happens.

And so I, I appreciate the intro to be candid, uh, around this. Cause some folks, this is not easy stuff to talk about. And I think it launched for you a little bit of a love into, into the why and like figuring out what the heck happened. Um-

Craig Zingerline: that was, that was the start of it. Yeah. I mean, I guess on the, on the point, um, before we jump into some of those metrics and stuff, I got a bunch of share there.

We also have, we have there's. So when you're building companies, there's false positives and there's false negatives. And I would say that. Had a false positive signal in that we had highly engaged paying customers on our legacy platform. And they did say that they wanted more stuff, but we didn't do enough of a deep dive.

Like we did. I didn't really show them wire frames of what we were building. We didn't vet how much they be willing to pay. We didn't do that needs analysis. So like, we're really good at about getting them to kind of nod their heads. Yes. Like, yes, we're interested in this, but in talking to those customers, I mean, fast forward now, I would never build a product off. of that early signal without validating whether it's getting payment upfront or talking through a subscription model or doing real price analysis and price sensitivity, uh, the cost to value ratio, like all of those things that we didn't do or things that we would do now, I would have done a lot more experimentation.

We probably would have launched one small MVP at a time and an incrementally increased price. So, you know, the false positive there was that like, we had a lot of customers saying yes, but it didn't amount to actual paying revenue focused metrics. Right. And that's a really, really hard lesson to learn because even as a product manager and somebody who built, I mean, with my agency is like, we won, we won like 60 plus awards.

We won two or three Webby awards for building products and building like, I was really good at that stuff. And yet there was this giant blind spot when building my own company in that I didn't, I didn't really know how to assess what was true and what wasn't as it related to that customer input. It's tricky stuff.

Rob Kaminski: Craig, when you were adding those features, it was, it, was it almost where you were shifting from product into platform? Or do you have like a perspective on that? 

Craig Zingerline: Yeah, so we, we thought that if we could be the solution for a lot of these marketing campaign, specific ideas within a brand, for example, then we would win.

But the irony was that we thought we were going to sell into brands. Like that was really, if you asked me in 2015, who are you going to sell to? I mean, I'm going to tell you we're selling into brands because this was an engagement based platform. And I don't know if we sold a single. Because the feature set while robust was not a platform.

And we thought we were building a platform, but we weren't really building a platform. We didn't go deep enough in the products. And we didn't do enough strategy on the platform side to build enough value into the product. That was something that they had spent five or $10,000 a month on, eh, which really shows just how difficult it is to build a platform.

Rob Kaminski: Yeah, I hear you have the sensitivity to that. It makes me think of something we come across a lot, working with clients is it seems like almost everyone wants a platform, right? In the sense of think of all the cool features it could have. And I look at it as almost one year when you're adding those features, you may accidentally be stepping into different needs and different jobs to be done. So to speak where market's just changed subtly, even though they're sort of interrelated. That's super interesting to hear your story around that 

Craig Zingerline: And the market can shift extraordinarily fast, right? Like the market can shift pretty quickly or a competitor can pop up, but like if a competitor pops up or the market shifts a little bit and you've got a product that's solving a real need and it's a must have need, then you're safe.

Yeah. You may lose a little business. It may. I mean, a good example is. Marketers who were currently a hundred or three months ago? A hundred percent dependent on Facebook or Instagram for acquisition. Yes. Some stuff changed with ILS 14 five. And it's going to change again with iOS 15, then it's going to change with Google and yeah, by the way, it's no surprise.

The apple app store is going gangbusters, right? Three X, their revenue, I think in the last quarter or two quarters. So yeah, those are shifts, but if you're a founder who was using Facebook primary, And you're solving a real need for a real customer. And Facebook gets a little more challenging. You should be fine.

It's going to, you'll take a little bit of a hit, but you should be fine because you're solving that, that pain point, you you've got a solution to a real problem. And I think that's, what's often missed is that it's either, um, what is it? A vitamin or a painkiller, right. And a lot of times, like you don't really know, or you're not honest about yourself, whether or not what you're putting out there. Absolutely critical. It's the thing that they will not unsubscribe from. Right. It's the thing that they can't really live without. And most of us aren't building those types of products, but we think that we are so finding that early and being truthful about that and being honest with your team about that and trying to iterate until you find that core pain point is what a lot of this is all about, especially if you're in that zero to one stage.

Rob Kaminski: Yeah, 

Ryan Hatch: totally. 

Rob Kaminski: I want to eventually circle back to what Ryan asked around customers, but Craig, why don't you pull us into the, your kind of approach with failure? Because I think it's it really tees up that conversation into tactics. So good. I want to make sure we cover some of that 

Craig Zingerline: Got some stats. So like I said before, I'm going, I went into this kind of, uh, personal exploration mode to, to truly understand like, well, why are.

Why do startups failing? And I came across some research, uh, probably the best was this 2018 CB insights. Post-mortem and these are the reasons where they had, they had talked to a couple of hundred startups, and these are the reasons why, ah, those startups failed, you know, no market need running out of cash, not the right team.

There's not a ton about product. Here even like number seven product without a business model, isn't a product problem, you know, and I'll share my thoughts on this. It's like Paul Graham startup mistakes from 2006, it's still highly relevant. These are the reasons why Paul Graham and the early Y Combinator crew saw failure.

And this is, this is a lot more up-to-date. This is, these are stats from startup genome who basically at a global level studies, startup success and value. And they, they talk about. Um, in consistent and consistent startups, consistent startups are the ones that basically make it long term, like pass that five-year mark and inconsistent ones are the ones that fail.

It's a really nice way of saying fail. And what's interesting here. So customer acquisition, so 45% of startups that scale prematurely spend more than 15 K per month on acquisition before even optimizing their funnel. Uh, and, and. 80% of the, uh, you know, 80% of the startups that make it simply don't spend that much money earlier.

I mean, just think about that for a second. So this is highly valuable, even for companies that have raised a seed round or these pre-seed rounds now that are just giant, like you think you're going to just go throw a bunch of. At the, at the acquisition problem, but it doesn't, it's not quite that simple.

If it were that simple, then there'd be a lot more companies that scale. Another thing is perfection. And I think this has rung true early in my career. Although now I've almost swung the pendulum all the way to the other side, where I will launch embarrassing stuff all day long. Sometimes it breaks and we're constantly kind of testing and iterating to not be perfectionists, but the companies that are willing to kind of embrace.

Critical feedback along the way and are not perfectionists tend to do a lot better. One of my pet peeves is that I think I've only seen two or three companies in my entire career who should have, who were stealth mode, who should have been stealth mode or pre-launch, you should have been pretty much it's like launch the darn thing.

Get that feedback even comes down a lines of code run. The companies that made it longterm wrote less code early on, and the companies that make it long-term don't hire us. They slow roll it. They're more patient with some of those aspects of growth. And when you think about it, we took quantify it. Uh, again, this is my math, so just take it with a grain of salt, but basically one in 12 startups makes it to that seven to 10 year mark.

And when I looked at this data, roughly 75% of that failure actually came from market or product market. Or customer adoption themes, right? Simply they just didn't get customers fast enough or they didn't build an, a value to get the customers that they had to stick around for, for a longterm. Right. And so that's, I guess that's kind of the takeaway here is like that speed to market.

And that feedback loop that you build is, is just critically important. So I'll pause there. 

Rob Kaminski: These go back to the hidden gem stats on the code lines of code. Uh, I think these are not well-known and these fascinated me for a couple of reasons. Um, and, and you hit on pretty much all of them as you were going through all this, my mind kept coming to you, brought up product markets. That's sort of this nebulous term, right? Like everyone has a different feel for what that is. And I, I don't know. I see it through the lens in here. I was, I forget, I just came across an article or it was a video with Jason Siebel brought up Y Combinator. And he was telling his story about Twitch, where they were five years in six years in making million a million dollars a year in profit. And even he's like, we didn't have product market fit. Super interesting. Right. And he talked about it in sort of what you said in your definition. Speed to market. 

Craig Zingerline: Yeah. 

Rob Kaminski: And it was around because his definitions of product market fit and I'm going to butcher it, I'm sure is around people like stumbling over getting to your product.

And I think there's speed built into like staying there and being sticky and then also coming in or all of this sort of aligns to me. Uh, but do you have a hard and fast definition of product market fit in your mind? Or did this help shape this a little bit to you on how you -

Craig Zingerline: yeah. I do have some, I did put together a couple of things on this. Let me see if I can pull them up. 

Um, so look, I think when I think about product market fit, there's, there's just a lot of noise out there. There's some really great resources. I mean, the superhuman team has come up with a way to measure product market fit. Uh, Sean Ellis from growth hackers has put together a way to measure product market fit using kind of NPS.

A lot of it's NPS. How dissatisfied would you be if the product left, there's other ways to measure it, there's calculators and all sorts of things, but here's the way I think about product market fit. Okay. The reason why you should be considering product market fit is that it basically gives you a sense of when you're ready to start scaling.

But the challenge is that. Usually, you're going to look at scaling through the lens of some kind of retention metric, right? Because it's not enough just to get customers into your mix, right. You need to like, you need to sell them and they need to stick around. I mean, with very, very few exceptions, that's almost how it always works.

But the, but the challenge is that retention takes a long time to report on. It might take you three months, six months a year. Right. And so the way I. Product market fit is through what I call proxy metrics. And these are things that will help you gauge what that future retention is. And then you can understand product market fit.

So what the heck are proxy metrics, right? So proxy metrics are product-based actions that, that you can use that tell you whether or not the thing that's happening in the product is going to lead to sales or. Right. Which is, which is a challenging way to think about it because you need to really understand like what those metrics might be.

So I've got a few examples here, right? So Netflix, the famous example is if they can get somebody to consume roughly 19 hours of content per month, they do not go away. That customer will not churn. Now, what does Netflix do to try to hit that 19 hours? What did they not. You get on the app, you scroll through it.

It starts playing content. They have amazing original content. They have a production facility in what? In Spain, they've got an international strategy there. They're buying studios. I mean, they they're spending something like $20 billion a year on a new content. Why it's to get the consumer to spend 19 hours a month because they know if the consumer spends 19 hours a month, then they're going to stay.

Right. For my own example, with, with growth, you, I know that if I get more than four engagement points with somebody, either in our funnel, if I get four plus engagements before their member there'll become a member, chances are they'll become a member. And if I get four of those types of engagements in a month, they're going to stick around zoom.

Right. I don't know what their metric is. I think my guess is that if they can get free users to set up calls, With a certain level of frequency over a period of time, I would look at it from a six week standpoint. If I get somebody to set up a call one time per week for six weeks, they're probably going to become a member or they're going to stick around and then consumer companies.

So sandbox that, for example, I was inside the company. So I knew if we can get somebody to write more than two letters in their first week, they're going to stick around for as long as the, as long as they can. Right now, when it, when it comes to product market fit, what, the way that I think about this.

You need to plot those proxy metrics on a retention curve and you see where that curve flattens. And so if in general you can flatten the curve, meaning like users come in. If let's use Netflix, if users come in in a hundred percent of them at the end of three months are not consuming. 19 hours of content, their turn is incredibly high.

And they, they eventually they go away. What this chart here is showing is a cohort view based on a month that says, okay, well, after six months I still have 40 to 45% of my original user base. The ones that in this case came in in March six months later, I still have 40 or 45% of them sticking around in that kind of the curve kind of flattens over time.

Yes, we will hit zero at some point, but it might be two or three years down the road. If we kept that line going off to the right, that's an indicator that you've got product market fit. Now, if you're below that 25% threshold, this is going to be determined on market and model and pricing and other things.

But these are the types of things that I would look at. Right. So what do you want to have happen is you want to see, for example, you know, I've got, I've got better. Core and proxy metrics leading to stronger retention over time. And that's a signal that if these lines are flattening faster, you've got product market fit, which is relatively complex to do so.

So a lot of people like to simplify the model in there. Therefore I think like those early MPS surveys and like talking to customers is a great way to S you know, if you talk to 50 customers and you say, well, would you, how disappointed would you be? If I went to. And 48 of them say, you know what, I'd be, I'd be pretty disappointed.

Ryan Hatch: This is Sean Ellis' approach, yea. 

Craig Zingerline: Right. So, so I don't think that's a one size fits. All right. But I think so use all of them use this model, use the Shawn Alice model, use the superhuman model and try to understand most what are those things that a user needs to do in your. To keep them, uh, to, to have them stick around.

And if you know what that is, that becomes your product strategy and those become the things that you market towards. Yeah. You've got product market fit. If you showed me a chart that looked like this, and April may are looking a lot better. And I'm evaluating it either from an investor perspective or an advisor perspective, or like what I want to work with this company.

I'm feeling pretty good about it because it tells me that the founder knows what they're looking for. They've got some metrics that they're measuring and they can plot this. Yeah. 

Rob Kaminski: Craig, I want to, I want to not challenge this as much, but I have a thought on this as you've shown this, even from what we talked about in prepping for this session.

So one thing that comes to mind and the question I asked you before we jumped. How do you even start with picking a metric? And we talked about the importance of having the hypothesis. I think that's a combination of art and science of the entrepreneur with the behavior of the customers that they're serving.

That makes perfect sense to me. What you, it's something you should, the way you shared it this time, what kind of hit me and I could be way off. So call me out is if you find. Where people are sticking around. Are you almost highlighting early adopters and ideal users where it generates, where I would go for research?

Why are they sticking around? Like, is this the right metric to go and talk to them and then pull back? That is my thinking right around behavior. What do you find fills up that almost that area that you say when it flattens out, are those, is that early adopters or is that?

Craig Zingerline: Early on it's going to be, but you gotta look at this stuff in cohorts. That's why the cohort view anything that you're doing within an early stage startup. I didn't get this for like the first half of my career. I didn't understand the true importance of looking at things on a cohort basis are because if you took your. Your first 100 customers and you plotted their retention.

It's going to look, you know, maybe it's a little chunky and then it falls off. But, but what you're missing is what's happening on a, on a month to month basis and how that's changed. Over time. I've got I've this it's way down at the end. I've got a slide down here that shows like how to look at this stuff.

Um, if I can find it, I'll scroll to it while I'm talking, but basically what you want to do, I think is you want to see that it's a cohort view, right? It's like what is happening to sorry about that. What is happening to that group of users when they came in. Grouped together over time. So your early adopters in this example here, like month zero is going to be for January month, zero, that's your first month that you're tracking this.

Those are probably, you know, January, February, March in this model, those are your early adopters as you're out in market, you don't have that same problem. Right. So what's interesting is, um, I'm not going to share the financial number, but I can tell you that 100%. Of our early adopters that came in the first time we started tracking revenue on a subscription for growth.

You was last, it was November of 2020. So almost a year ago, a hundred percent of them are still around. We have not turned a single. Okay. But what the price point was different, the value for it. And they were the early adopters. Yeah. So if I use them in average them against everybody else, everything looks better than it is.

Well, guess what happened? We jerked the pricing around, we're changing the value prop, like we're testing things. And the next couple of months, like that month, zero to month, one churn, like, so when we're looking at this chart month, zero to month one, that's what percentage of people that next month are still around.

It's how you read these things. So if you look at just January, you know, January is month. In month one, there's 70% of them around. That means you've got a 30% churn rate between January and February. Right. So if you take the law of averages, you miss the details. 

Ryan Hatch: Yeah. I think it really pivotal to this whole conversation really is the question of when's it. Time to add more fuel to the fire, when's it. Time to scale and when's it. Time to hold back. Right. When's it. Time to resist that urge to like, well, they're, my investors are telling me, Hey, you need to have a larger vision. You just need to grow this thing. Right. Or I have this internal desire. I know this can be bigger.

Right. When when's the right time to hold back and when's the right time to double down. And that's really the ultimate question that we're kind of getting to here is how do I know? Right. How do I know when I'm at product market fit and what are the early indicators? I think one of the flaws you talked about earlier is really interesting because it's like this, this. It's totally a, it goes against what you'd think. You'd think, you know, there's the mythical man month, right? Hey, look, we just need to throw more bodies at this problem and we can solve it faster. Our backlog is so big. We just, we just need to throw more people at it. Right. And in this case, we see this, we see if we throw more money at this thing, like this thing can take off.

And it's. Yeah. It's so flawed that you it's such it's so counter-intuitive, I think Craig, from what you're saying is like you have to spend less, you have to keep your team smaller. You have to write less code. . Am I hearing that right? 

Craig Zingerline: You're a hundred percent look, here's the deal. Right? This thing that I'm showing you is like a, it's an LTV view and this is fake data. Um, but LTV is lifetime. I know again, when you're just getting started, you have no idea what your lifetime value is with growth. You, we started tracking revenue really for like our investors. We started tracking it in January. Like the half-baked idea became an idea that we were executing on really in January.

And before that we were, I mean, we, by the way, speaking about product market fit, I had sold honey, you know, over a hundred seats into a non-membership model. Talk about a strong signal. That's an entirely different business model than selling a subscription and a membership, which is what we said now. So that's why we were honest with ourselves or like what, what do we want to do as a company?

I, I didn't want to keep going after people for money. Every time we created a new course or did a program or whatever. So we built this membership, but it's entirely different unit economics. So that's the first thing, like early on, there's a ton of chaos. If you don't really know what your model is yet, then don't scale.

Now, that's not to say you shouldn't be experimenting, right? We, we experiment on almost everything, right. To the point where it's almost ridiculous. You know, some of the stuff is, is pretty embarrassing. Um, we will just kind of hack and hustle our way to try to figure out what that signal is and whether it's testing pricing or something else.

But a lot of companies where I see it go wrong is they raise. And they've got some sense of directional PM fit, but they really don't. And then they go and spin up a ton of Facebook and they burn a bunch of money and they don't, and they're completely underwater for an indefinite period of time. Here's the, here's the general rule.

I think if you can spend money on acquisition or even spend your team's time on organic strategy, right. Because it's the classic trade off of time versus. So your team, when you're early on, even though you might be bootstrapping and feeling great about the organic growth, it's probably in your best interest to do some stuff on the paid side, because you want to test the waters a little bit.

And, and conversely, like if you've raised money and you're like, I just do paid acquisition, uh, and. It's probably time to look at your organic content strategy, because again, you want to find that signal, but where we're starting to go wrong is when their metrics are underwater. So if. Salary that equates to like the amount of time you have to spend on your organic bootstrap salary or bootstrap strategy, doesn't get you customers fast enough or you raise money and you can acquire customers fast enough, where you're basically at break, even on the return on that investment of time or money within six ish months or whatever your runway is, you're going to be in trouble.

Right. And so. We, so I grow with you. We actually, um, so we raised, uh, an angel round in, uh, in March and we started applying capital to paid acquisition channels. We knew we were pre product market fit, but what I wanted to do is I wanted to stress test. What is our cost per acquisition in Facebook and Instagram and Google.

And then how hard is it on the organic content strategy side to go and get customers? What does cold outreach look like? So we've tried all these things. What we're starting to do is map what looks like this thing in front of you, which is now six months in. We know what our churn rate is. We know how much money we're going to get from every customer.

And it's starting to inform how much we can spend back up channel on acquiring the customer. And, and I think like if you're at a point where you understand that and you've got some data and you're starting to see that, like there is a payback window that isn't five years. And you have conviction around what you're doing is working.

Then you're probably in a good spot, but if you're looking at a thousand dollar customer acquisition costs and you make a hundred dollars a month off of a customer, it's going to take you 10 months to pay back. And that might be okay if your churn is only five or 6% a month, but if your churn is 40% a month or 30% a month, you never make money.

And that's a problem. And this is the thing that a lot of. Us who are starting. Don't really understand. We raise capital and we're like, oh, we're just going to go spend it on whatever channel. And I would also argue though, it's not just, it's not just money. It's also time.

Rob Kaminski: Right craig, I might be opening up a can of worms here. Uh, but you brought up raising money and this whole conversation around product market fit. I think there's this baked in assumption of when you raise money that shows yeah. I product market fit. I was able to raise money. That's not true. I think anyone who's been closed knows that's not true. I'm curious if maybe you can give us a quick perspective on like, or a story that you've had in raising money in your experience, where did you raising off of, you talked about that pre signup for demand.

Was that enough? Or do you need to have some of this stuff worked out? Like w what's that story look like to you? And I know for everyone it's different to industry and model, everything's going to drive that, but 

Craig Zingerline: do you want to see my, um, do you want to see my pitch deck? 

Rob Kaminski: Absolutely. 

Craig Zingerline: I can pull it up. So hold on. Let me see if I have it available. Hold on. I don't know what state this thing's in and I'm given, but, but look, when we were pitching, uh, what we were pitching on was a lot of the themes we're actually talking about today. And now when we go to raise more money, we will update this with the latest narrative.

But, uh, every year over a million startups are founded, like that's from a multi, multiple different sources in most fail. And we talked about. Early stage growth stage and scale stage startups, having different challenges. And so what is our solution? So that's the problem, right? The problem is most companies fail.

What is our solution? Well, we help them build their frameworks for growth and we help them increase the odds of success. That's an aspirational thing. It's our narrative, but early stage growth stage scale stage, guess what? There's different themes. So finding initial customers in the early stage, learning about experimentation.

Failing fast and pivoting and the growth stage it's holistic growth marketing, it's deeper stuff, channel strategies. And at the scale stage, it's like, how do you really scale this stuff out? How do you increase retention? How do you, how do you double down triple down 10 X down? Now, what was interesting is because we had run private beta.

Uh, and we had run even on a different model. I had these amazing testimonials. I mean, there's one on the left from that taskable the hour I spent every weekend growth. You saved me 10 to 20 hours trying to figure out things on my own. I can't recommend this course enough. Okay. That's like speaking our language.

Right. And we had all of these logos and stuff like that. And we had a big vision for where we wanted to go on the revenue forecast. And again, it's a leap of faith. I mean, look at our revenue forecast early on. Cause I knew in November, December, it was really small, but we were going to grow. So I pitched it on that potential, but I also shared, this was again, we raised in March.

So I had February metrics by February. We were at about 3000 in monthly recurring. Um, and we had been fairly dramatically increasing again, at that point we realized now there were a lot of early adopters there. Like we had a slightly slower summer, but their seasonality I play with with kind of learning platforms.

What we do is we kind of teach them a lot of this stuff. We've moved into a lot more hands-on work actually, but we had enough. Data, I guess. And we could pitch that bigger vision. I mean, great team, right? I mean, I handpicked like this like amazing team. We've got amazing advisors. I've got a track record as a founder as like, here's what we were doing and we oversubscribed this.

Right. So that's kind of like what we were looking at in terms of how do we, how do we pitch this? It's really, it really, for us was a story about traction and team and potential in the market. Because again, when you talk about failure and we're pitching investors, investors invest in companies and most of those companies fail. Most of those companies fail. 

Rob Kaminski: You brought up kind of the angel route. How important was the audience here? Like, I look at your problem and solution and I, I, my, my gut says what an institutional VC look at this and like, do they care? Or even get it around what you just said of like, prove to me it's going to work. It's all around traction. Did it help being in front of angels with my guesses that they've been around some semblance of these activities.

Craig Zingerline: It's a good point. I don't yet know. Right. So we're going to, we're going to do, uh, we're going to do, um, we will raise more capital relatively soon. Actually. We're probably, probably gonna announce something soon on that side, but, um, but the, I think the wants and needs of, and really what those angel investors are buying into is a lot of that potential.

And, and at the later stage rounds, it's all about traction. And what are you doing? And I can say we've learned a lot. We also have very strong traction. So I feel good about, I feel good about that, but there's still a lot more to learn. So I think it just depends, like we're not going to go for some monster round, you know, that that is just, you know, pitching this, you know, $50 billion idea because we don't, I'm much more realistic and I don't, that's not the type of company I want to run.

Uh, you know, and we actually, because of our model, Uh, like for example, we could get to profitability relatively quickly. Uh, if we wanted to, because we can offer more hands-on support that we can charge more for as a membership model and stuff like that. So this is an area where it's not one size fits all.

You really have to have conviction around where you want to go with it. And so, yeah, I mean, you know, Rob, to your point, like there's probably some investors that this type of model is not going to appeal to and, and that's perfectly okay. Uh, in fact, I, I weren't that. We're looking for a specific type of person to come along the journey with us.

Ryan Hatch: I'm curious, you know, you did, you know, I just saw your, your raise was like 505 million pre, like that's pretty great. Um, and I'm just curious how you, how did you justify to investors like the, the valuation of 5 million pre, like how how'd you, how'd you frame that 

Craig Zingerline: this is a little, a bit of a secret, you know, secret, secret sauce here in and I'll give away the reality is that, uh, I built the original curriculum.

So, you know, I went on this personal discovery mission to understand why startups fail. But the first thing that I did was I started recording content and I built the first program. Well, I ran it with Jason Calacanis and the launch accelerator. And so it solved a real need for a very credible investor who came on.

As a non-operating co-founder and actually put the first money into the company. So there was instant credibility there. Now had we not gone that route, we would have been, um, you know, it just would have been a much slower. Build slower rollout. And I think that part of that social proof enabled us to have a, you know, a, a cap that we thought was what was, was realistic for the company based on some of those revenue projections that we were showing and stuff like that.

But I am seeing just crazy valuations in the market right now. Uh, and some of it I think is justified and, and I think a lot of it probably isn't. To your point earlier? Uh, I don't really care what a company's valuation. Like, I want to see revenue. I want to see user growth. Those are the things that I want to see if I'm going to spend a lot of time with a startup, you know, whether it's on the advisor side again, or like spending time with our member community or doing investing or whatever it might be.

I want to see that traction. And I will always steer somebody towards doubling down on traction and focusing even. So I talked a lot of founders that still have a full-time job. Keep that job. If you can, while you're building this thing out to bootstrap it for allow. So you get that 10 to 20% month over month fund the growth of that.

If you need to, you know, while you're doing something else, because once you take the plunge and you're responsible for your livelihood, uh, and I've definitely been in this boat and if it doesn't work out the way you. You get yourself into trouble. And so I think just, again, a lot of it comes down to your, your personal situation, but we felt good about the 5 million because we had the traction in the, you know, the social proof and all that stuff.

Rob Kaminski: This is awesome. I think maybe to converge, I love it. We went down this rabbit hole. I think this conversation was extremely valuable. Craig, maybe to wrap up today at Ryan had a question earlier on around talking to first customers pre-product market fit. I know you have an interesting kind of model and thought to that.

So maybe we wrap up there.Close out today's session. 

Craig Zingerline: Yeah, let me pull this thing. Uh, and I just updated it this morning, but I didn't have time to put it in, but, but basically look, I think finding first customers is, uh, is really, really interesting. Uh, and even the way one thinks about how to acquire customers in general, even if you've got some customers, the way that I like to do this is I like to put it through this kind of flow.

Okay. So basically you have, you've got a solution that you've put out there. You've got a product, you've got a solution. The number one thing you need to understand. Is does your ideal customer profile or your batch of ideal customer profiles? Do they know that they have a problem that they need a solution?

And are they going and looking for that solution? Yes or no. Now there's a lot of blurred lines here, but that, but, but it is almost binary. If you think about it from that standpoint, it's like, they either know that they've got a problem and they're going to go seek it out. They're going to seek out a solution or they don't.

And in the answer to that question is where you start with some of that early exploration. Right? So user is aware of. Uh, they, they may know a brand and they go and search right on this. So like, Airbnb is a good example. If you're looking for where to, you know, if I'm going on vacation and I'm going to, uh, I don't know, Dublin.

Okay. Places to stay in Dublin. I'm not going to put that in Google. I'm just going to go to Airbnb and I'm just going to look it up. So that's a, that's a branded search. Well, what works there? What channels work there? And SEO. If you've got a high intent buyer who is searching for a solution to their problem, then you're going to probably want to start with search engine marketing, buying some ads on Google, maybe Bing and search engine optimization, because you've got intentionality.

If the user does not know that they've got. Uh, you start probably with paid social content, marketing influencers. Now your overarching content strategy of a, if I had to like draw a circle around this whole thing outside of that circle, kind of driving the strategy is your content strategy. It's why you guys have this podcast.

It's why we're always talking about startup stuff on Twitter and on LinkedIn and everywhere else, because we become thought leaders. And when we become thought leaders, we build our audience and then our audience. Again, they may not have known about a problem around growth, but we pointed out and then they become customers.

So, but at the starting point, it's kind of this like binary view. If you're a founder and you don't have a ton of time or money, look at it through this lens and like give you some ideas on where to hang out. And then of course you need to do all of the things about activation and all the drip campaigns and sequences and email marketing and following up and.

It's shocking how bad that process is, which is a whole different conversation in and of itself. Like that activation loop is often just an afterthought, but, um, this is how 

Rob Kaminski: Craig, for those just starting in this model here of this awareness and are they searching for a problem? So almost your second run.

Craig Zingerline: Yeah. 

Rob Kaminski: Do you, I, I, my question is, do you, would you do both or would you put all your effort into only focusing on people that are actually have that intent that are looking for a solution? 

Craig Zingerline: I think it's 80 20. If you know that there's, there's an audience. If you know your audience is looking for that solution, then you spend 80% of your time there, but you still need to kind of be in other places.

The challenge is a lot of us may not even know. So what happens before you click this start button? If you're like, I don't know if a user has a problem, the fastest way to learn there is you can use respondent IO or a there's other user research platforms you can use. Cold outreach is amazing. Uh, bothering everybody that, you know, for intros to people who might give a crap about what you're building is a good way to go.

So like before you click that start button, there might be three months or six months of research, right? Again, like when I started growth university, before it was growth university back in 2017, I was sitting in traffic, recording myself on my phone, literally sitting in my car, sitting in traffic and asking myself a growth question and then answering the question, like how embarrassing is that?

And then I would transcribe that content because I was busy transcribe that content and put it up on my blog. And then eventually I was like, I'm getting enough themes here. I'm talking to enough people that I'm starting to find these themes. And then I was like, in a year, I finally had like some form of a curriculum now that we know, right.

Three years later that, okay, well, there are. No, that they've got a problem with growth and they're seeking out solutions and then we're there. And we also know that we need to point out the fact that maybe you've got a problem and we're there. Right. But sometimes it takes a while to figure that out. So early, early, early, early on, you need to just do a bunch of stuff.

Rob Kaminski: I could just, I'm picturing you, sitting in your car, recording on your content. Now my mind goes, I think that's such a bad-ass story. To be honest, I know probably hard to do. 

Craig Zingerline: Uh, it's mostly sitting in traffic. I, and I remember when I actually started the first time I clicked record, I was actually like, uh, next to the DCA airport on my commute from where I live up into DC. And I was running growth at a startup and I was just literally sitting there in traffic and I'm like, let me just try it. Let's get over the fear of doing this. Like just the record. And it was using like the voice recorder on my. Sometimes you just got to do stuff like that though. We get rolling. 

Ryan Hatch: I have so many great, like follow-up questions. I just want to ask you right now, but I know we're, we're almost at a time I'll, I'll tease you with what they are though. Okay. It's here. It's easy with, like you said, that we experiment in almost everything I'm really interested in. Hey, how you manage that experimentation loops, right?

Like how you and your team manage that and cycle through those. I think. Uh, wheelie experiment, you know, sprints, or I'm just really interested in, in some of that. That'd be fun to talk about some time. Um, and then one thing you touched on, which I don't know if everyone quite understood, but I wanted to, to touch on them when you talked about cohorts and some of the audience might not know, well, what does that, or how do I make that work?

And really what. Well, I understand it to that you're coming from is that every week you're actually running those experiments every week. Your products changing your experience end to end is changing every month it's changing. So what you're seeing is like, how has the experience that exchanging experience, um, impacting retention over time? Right? Cause they're all going through different experiences. 

Craig Zingerline: That's what a product manager really should be doing. All day long, a lot of product managers get caught in the weeds of just like tasking stuff out. But it's like, if you truly understand what the impact of the product change is having on. On your audience, you're going to learn that you need to kill some features that you rolled out.

And you're hopefully talking to customers early on, you know, Ryan, to your question on, um, experimentation. And we're not as organized as I want us to be word it's like still, we're still so early stage that it's fairly chaotic in terms of like, somebody will have an idea and we go and execute on it. But that's the beauty of being small is we can have an idea and go execute on it.

Um, and, uh, but at, at a level of scale, like at my last company, for example, And we still do this, a growth here. We've got weekly meetings where we review, review the metrics, but we did more of a regular cadence of growth experiments. And we would actually, um, I have my own framework that I built, uh, for like experiment prioritization.

And there's, there's a model from Intercom called the rice framework. So there's a couple of ways to kind of quantify the time. In return on experiments and that, yeah, that is a totally like separate discussion. Right? 

Rob Kaminski: That's our way of inviting you back. Craig, thank you so much. So much stuff here. Where can people reach you and growth university? 

I'm just craig@growthuniversity.io, I'm @craigzingerline on Twitter. You can find me on LinkedIn. I'm the only Craig zinger line out there. So I'm easy, uh, and go to growth university.io. We have now 11 training programs for marketers that are available on demand.

A lot of founders, specific stuff doing, including how to raise money, uh, fundraising for startups. We also do a weekly live mentor sessions where we get a group of entrepreneurs together and we just talk, uh, it's combination. Channel and marketing strategy and growth strategy and founder therapy. And we do live cohorts where we run, you know, once a quarter, we run a live program and we also do a, what I call working sessions, which is, uh, you pair up with myself or a member of my team and, and kind of get some real insights into what's happening in your business, kind of in a hands-on matter. So we kind of do all those things. That's all at growthuniversity.io. 

Awesome. Love what you do, everyone - check him out. Uh, we'll catch everyone next time on exploring product, 

Craig, thanks again. 

Craig Zingerline: Thank you so much. Bye-bye.