Motley Fool Hidden Gems Investing - Not All Revenue Growth Is Created Equal — A Harvard Fellow's Framework for Spotting the Real Thing
Episode Date: August 30, 2026Wall Street treats demand like a line on a chart. Rob Snyder says that's exactly why investors keep getting burned. Motley Fool analyst Rachel Warren talks with Rob Snyder — Harvard Innovation Lab...s fellow, serial startup founder, and author of The Power of Pull — about why customers almost never buy things because they were convinced to, what that means for how you evaluate a publicly traded company's growth story, and how the AI boom is exposing which software businesses have genuine demand and which ones are papering it over with an ever-growing sales and marketing budget. He also shares the one financial metric he trusts above all others — and the surprisingly mundane AI use cases he's most excited about. Host: Rachel Warren Guest: Rob Snyder Producers: Kristi Waterworth, Lauren Budabin Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We’re committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices
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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 that 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. We 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. He 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 Poll 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, I 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 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. They 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 four 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. I 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 it 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. And 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. And 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,
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 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. And 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
then convince someone to use and repeat that forever and ever what 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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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, just not to us right now. So the value proposition
alone is kind of irrelevant. It's about, again, back to Paul, 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. They 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. What'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, 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. Like I've seen, 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 hundred thousand two hundred thousand dollars in revenue was me in a
spreadsheet that they couldn't log into so 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
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, five million, 10 million. You 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 now, 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.
What 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've 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.
are there any you know specific financial signals that you think tend to indicate whether a demand
curve is uh structural or manufactured if i'm looking in kind of like the software b2b kind
of space i look at retention customer retention and like specifically net revenue retention is
one of the big things that we look at that's a signal of kind 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 and 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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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 and 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 and 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 Cloud 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.
It 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.
Another 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. I'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,
you know, talking with founders, when you're looking at these AI startups, and you know,
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, you know, 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 it's not just we went
viral on x or we were featured by y combinator on 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. All
the other startups are coming for you. Once we see these metrics that actually look good, then it's
a OK, 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.
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