Not All Revenue Growth Is Created Equal — A Harvard Fellow's Framework for Spotting the Real Thing

0:01There's a founder in Europe I know who has the worst sales calls you've ever seen. He basically reads the GDPR regulation on the sales call for no reason. And customers are desperate to buy regardless. So that's what you're looking for. You're looking for people who are trying to buy despite, not because of.

0:25That was Rob Snyder, Harvard Innovation Labs fellow and author of The Power of Pull, on what real demand actually looks like and why it has nothing to do with a great sales pitch. I'm Motley Fool analyst Rachel Warren. Rob has spent years building startups and analyzing hundreds of others to understand why some products take off and others don't, even when the value proposition looks identical on paper. He joined me to talk about how investors can use his demand framework to spot the differences between genuine product market fit and growth that's being manufactured by an ever-expanding sales and marketing budget, and what the AI boom is revealing about which companies actually have it.

1:03We hope you enjoy. Welcome back to Motley Fool Conversations. I'm Motley Fool analyst Rachel Warren. As investors, we're constantly looking for companies with durable, long-term demand. And when a business experiences explosive growth, Wall Street often assumes that they've cracked the market code. Well, our guest today argues that traditional economic models are somewhat broken when it comes to understanding why customers actually buy things, and in fact, that relying on the wrong growth signals can lead investors into dangerous traps. Our guest is Rob Snyder, a serial startup founder, a former McKinsey consultant, an entrepreneur in residence and venture partner for early-stage venture capital funds, and a fellow at the Harvard Innovation Labs.

1:44He has synthesized his years of building and analyzing hundreds of startups into his new book, The Power of Pull. Rob, welcome to the show. Thanks so much for having me. The financial world has spent many years treating consumer demand like a mathematical formula on a spreadsheet, but your book, really interesting, completely flips that assumption on its head. And so I'd love it if maybe to start off today, you could take us inside the core themes of The Power of Pull and explain what inspired you to write it. So the theme is that I thought consumer demand worked just like you mentioned. when I went and started my first company.

2:17I thought it was, you know, you provide clear value, clear ROI, you solve a problem, and then you convince them to buy and they'll buy it. And that's how I started my first company. And we just got punched in the face for a couple of years when nobody would buy our product. And then I got a phone call from a restaurant owner who said, hey, I have no idea what you were trying to sell me, but here's where I need help. This is specifically where I'm focused right now. And if you can help, you're a tech guy. Maybe you can figure something out. I will pay you to help me out there. And so that's when I realized that buyers don't behave like I want them to behave.

2:55They don't behave in a way that kind of like made sense in my economic textbooks. They behave in a very different way. And that's when my startup started to take off. We went zero to 4 million in revenue in two years. And I've since helped a bunch of other startups try to uncover why do customers actually buy things? What's really behind demand? And it turns out it's not quite as simple as saying, oh, they pick what gives them the most ROI or the most value or what solves their problem. It works a bit different from that. Maybe dig a bit more into this theory or model of demand and also maybe help our listeners understand the difference between pull versus push in this context.

3:33I think that that would be a great way to kind of better understand how this model works in real life. What I found when I tried to go out and sell something that I thought the market should want was that it felt like I was pushing people to buy. It felt like I was trying to convince them. I was initiating all of the force in the transaction, you could think of it as. And so when I would be on sales calls, for example, I'd be saying, don't you have this problem? Don't you want this value? Then I would have to do all the following up. So think of that as push. seller convincing. When it worked, it worked very differently than that.

4:12It was almost none of me pushing. I would get phone calls from people saying, hey, I heard about your product and I need to buy it. That is all pull. That is the buyer basically pulling the product out of my hands. And so that's where the idea behind pull comes from. It's the buyer is initiating the purchase action and the post-purchase action. After they bought, they would get set up. They would set themselves up. They would do all the work to implement the product where beforehand I had to push them to use it, beg them to use it. And so what I found is that there are common principles behind pull, behind demand, which is the model that I came up with is called the pull framework.

4:56And it just states that buyers will pull a product out of your hands if they have some sort of a project or a priority they're trying to get done right now, but their existing options for getting that priority done are not good enough. They won't get that priority done. If that's the case, they will pull a product out of your hands. But if that's not the case, it would be weird if they bought it. They would have to drop whatever they're prioritizing, or they would have to say, you know what, my existing options are good enough, but I'll buy your product anyway. And that's not how the world works.

5:30And so that's where the model of pull has come in. It's really interesting to think about because I think a lot of times as investors, you know, on our side here at The Motley Fool evaluating public companies, but of course, this also applies in the private space as well. Demand is often treated like, you know, a line on a chart that moves predictably. And it seems you have found that model actually breaks down when it comes to explaining the actual act of purchasing. What are some of the reasons for that in practice? In practice, what happens is if you think that demand is just a kind of line, you don't realize that it's each individual person making a purchase decision.

6:07And we have to understand what's behind their purchase decision. It's not that they want to buy it. It's that something is happening in their life that is kind of causing them to buy this product. Sometimes you can actually watch sales interactions and sales conversations, and you can see how buyers are behaving in those interactions. You can see, are they being convinced? Are they being persuaded? If so, the company is pushing, and that's just really hard to scale. And it's really hard to retain people after, especially for a recurring revenue business, which we all love, right? It's hard to convince someone to buy than convince someone to use and repeat that forever and ever.

6:54What you're actually looking for is somebody who pulls the product into their lives and uses it as if they can't not use it, as if they're addicted.

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8:27Vanguard Marketing Corporation Distributor. Why do most new products fail despite a clear value proposition? And I wonder what that reveals about how markets actually form. The value proposition, so much of what we've learned, or at least what I feel like I have learned in business school and all the business books, sounds so right that if you provide a compelling value proposition, then people will buy. But there's so many cases where there are so many value propositions that are available to you and I right now that we're not buying. There's 600 million SKUs on Amazon, right? All of them have some sort of a compelling value proposition.

9:08just not to us right now. So the value proposition alone is kind of irrelevant. It's about, again, back to poll, it's about what is this person prioritizing? And is the value proposition relevant to that? That's what really matters. And so what tends to happen, what I see all the time, what we see at Harvard Innovation Labs is there are these brilliant ideas for brilliant products that offer interesting value props that customers see and they say, wow, that is phenomenal. That's exactly what the industry needs. And then they don't buy it because they're not prioritizing anything related to that.

9:50They don't have pull for it. And so entrepreneurs will always go down this path of a product that makes total sense that nobody buys. I think the classic narrative we've heard is that, you know, a startup scales because of a genius founder's vision or an aggressive sales script. Obviously, one would hope that that's part of the equation. But I want to talk about your work as a serial founder, obviously, your work with Harvard Innovation Labs. What have you seen when a company takes off and how that contradicts, you know, conventional theory? What are some of the steps or hallmarks that tend to accompany a business or an idea or a product that's actually going to succeed once it enters the market.

10:28What's been interesting is I always thought it was, oh, it has to be a good product that is sold well by an aggressive founder who has a very big vision. Okay, those things sound right. Every time I've seen it work, and I've seen a bunch of companies go zero to a million, zero to 10 million, zero to 50 million. I've seen companies on this trajectory. It almost never works like that at the very beginning. In my case, when our startup actually took off, it was kind of despite the state of our product. We had a three or four slide sales deck. The product, for the first$100 ,000,$200 ,000 in revenue, was me in a spreadsheet that they couldn't log into.

11:12So nothing in that should have worked. When it works in the early stage, it is always the person who's trying to do something and blocked. They are buying despite the state of the product. They are buying despite the fact that the founder is not great at sales. There's a founder in Europe I know who he has the worst sales calls you've ever seen. He basically reads the GDPR regulation on the sales call for no reason. And customers are desperate to buy regardless. So that's what you're looking for. You're looking for people who are trying to buy despite, not because of. And then as that starts to work, as you get to a million, 5 million, 10 million.

11:57You hire really talented people who fix those things that were wrong, that people bought despite. You get the right pricing, you get a better sales process, you get a product that actually does the thing. That's what very often happens in startups. And it works totally differently than how I thought it worked. I'm curious, if investors were to use your demand framework to say, evaluate whether a publicly traded company has genuinely cracked the market or maybe papering over a weak pull with heavy sales and marketing spend, what would be some elements of that framework that one could apply? And let's just put all the caveats out here of I am not an investor.

12:37What I would say is that not all revenue growth is created equal. And revenue growth that is funded by aggressive sales and marketing, where it is a lot of push, is very hard to sustain over the long term. And you can tell if they are just spending a ton of money on sales and marketing. And that is just going up and up and up. And instead, what I found you are looking for is people buying, people pulling the product out of the company, which is often accompanied by a lot of sales and marketing spend. But I'd say like that sales and marketing spend is dedicated to converting people who already have demand rather than trying to convince people they should have demand.

13:24Are there any specific financial signals that you think tend to indicate whether a demand curve is structural or manufactured? If I'm looking in the software B2B space, I look at retention, customer retention, and specifically net revenue retention is one of the big things that we look at. That's a signal of product market fit that we're not just convincing people to buy who will churn, that we are actually converting people who, because they have so much demand, they use more and more, they pay more and more, and they get increasing value out of it. And that continues. And so that's the kind of main metric that I care about.

14:08And the things that I focus less on necessarily are like NPS, customer satisfaction type things. Those are fine, but those are stated preferences. Revealed preferences are in the post-sale usage.

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16:04For problems worth solving, get started with Claude at Claude.ai slash fool. That's Claude.ai slash fool. and check out Cloud Pro, which includes access to all of the features mentioned in today's episode. Cloud.ai slash fool. So you're currently the co-founder of an AI cloud infrastructure company, restack.dev. You evaluate early stage B2B AI startups every day. I would love if you could talk about what are some of the trends or themes you're seeing in this space, what excites you the most right now, just hear your thoughts generally. The trend right now is AI, clearly. And for any startup that is not one of the AI labs, the trend is how do we not get run over by one of the AI labs?

16:47And so the thing that every company who is buying software today is thinking about is can't I just do this myself with Claude or Codex? And so that actually fits into the pull framework. The list of options they have now include do it yourself with Claude or Codex or whatever. And those options are often good enough for a variety of things. And so the question for us entrepreneurs and for anybody in this space is, when is quad code, codex, your AI products, when are those not good enough? And in what ways are they not good enough that the next model release will also not be good enough for? That's what we're all trying to find.

17:30And so one thing that I've seen is very common in startups is you focus on the point at which they have tried to do it themselves. The customer has tried to do it themselves in Claude or Codex, and they've gotten pretty far, but they haven't gotten all the way and they can't get the last mile to whatever it is they're trying to do. When you hear and evaluate all of these applications, where do you get most excited when you look at how AI is changing different industries? And where do you think some of the use cases are perhaps a bit overhyped? the things that I'm actually most excited about are way more kind of like simple and mundane than you might expect it's like the kind of thing where hey we had a market research firm give us a report every quarter about some niche of the pharmaceutical industry and we spent a ton of money on it it was kind of good but it wasn't actually what we needed and now a startup that exclusively focuses on AI for this specific space can get us that specific report every week or every hour or whatever.

18:33It unblocks us to be able to get this kind of market research report that we in pharmaceuticals have needed. Or, you know, there's an insurance, right? In commercial insurance, we used to spend a week whenever we get quotes back from the insurers to put together a comparison chart for potential customers so that they can see what's in the different quotes that we get. Okay, now a very specialized AI that understands all the different kinds of quotes in insurance can do that for us in minutes instead of it taking a person weeks. And so it's just little things like this that are often little artifacts, little parts of the business where I've seen startups take off.

19:16Another example is a company called Jump that I helped take off where They're just an AI meeting note taker for financial advisors that specifically works with their CRM and is compliant with kind of like the regulation needs of financial advisors. It started as this really, really simple thing. Financial advisors had always manually taken notes and put them into their CRMs and that took them hours every single day. This just eliminates that thing they were already doing. So these are kind of some examples of places where I'm excited. Obviously, the big AI labs, those things are super exciting too.

19:50I'm more on the small guy entrepreneur type thing of what's the little thing that's going to take off. Well, and that's the thing when you're talking with founders, when you're looking at these AI startups and you have a founder that's talking about the explosive organic growth they've seen. What are the kinds of questions that you ask to determine that there's actually a durable tailwind there and it's not just short term demand? I will focus on their metrics all throughout their funnel with the biggest emphasis on what happens after these customers sign up or buy. Because what I want to make sure is that it's not just hype.

20:27It's not just we went viral on X or we were featured by Y Combinator or whatever and we got a ton of inbound that we converted but also isn't durable long term. The question about long-term durability, though, is honestly, like, what we've found is that it's just a race right now for every single startup in every single category. The second jump takes off, there are a bunch of other AI meeting note-takers for financial advisors. And so there's never a kind of standstill. It doesn't feel, at least in startups, like there is the opportunity to kind of say, this is durable. The AI labs are coming for you.

21:01All the other startups are coming for you. Once we see these metrics that actually look good, then it's a, okay, cool. We also now need to stay ahead of everybody else. And what I've found is that it's just staying close to customers, figuring out other ways we can unblock them and extending the product suite so that people want to stay with us longer. Fantastic. Well, it's been great to chat with you, Robin, to hear about your book and all that's happening in the startup space right now in the world of AI startups. Really appreciate you coming on to talk with me today. Thanks, Rachel.

22:01disclosure, please check out our show notes. For The Motley Fool Hidden Gems Investing Team, I'm Rachel Boren. Thanks for listening. We'll see you next time.