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September 18, 2025 35 mins

EPISODE 25

In this episode, Metronome CEO Scott Woody breaks down how AI is rewriting the value of software—from “seats and subscriptions” to agents that do work—and why modern pricing must blend stability with upside. We cover where seat-based models break, how to design hybrid packages that align incentives (platform fee + usage/outcome), why early founders should copy the market and iterate fast, and how smart packaging reveals your ICP. Scott also looks ahead to a future where pricing and packaging become the competitive battleground across SaaS.


CHAPTERS

00:00 – AI rewrites software’s value

04:05 – From Dropbox pain to Metronome

10:06 – Hybrid pricing that aligns incentives

14:35 – Early-stage: copy market, iterate, segment

26:30 – Pricing/packaging becomes the battleground


LINKS

Connect with Scott Woody

metronome.comLinkedInX/Twitter


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Connect with Kevin

LinkedInX/Twitter


Connect with Jason

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Mark as Played
Transcript

Episode Transcript

Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
The rise of the Internet though,shifted the value of software.
Software now updates itself. Subscriptions became a thing
before. Before the Internet,
subscriptions was not like subscription software didn't
exist. What I see with AI is now the
value of software is shifting again.
Now instead of software being a thing that you consume, the
software is doing work on your behalf.

(00:21):
And so AI is fundamentally rewriting the value of software.
Welcome back to Founder Mode. The show where we talk to

(00:42):
builders who aren't just chasingrevenue, but making it smarter.
Today we're going to get into what all early stage founders
deal with pricing. From usage based models to AI
monetization to fixing billing friction, this episode is about
how to turn your pricing from a cost center into a growth
engine. Kevin, do you know how many
MANUS credits you've used in thelast week?

(01:04):
And what's that credit to cash exchange rate like how many, how
much should you spend like everyday as you're ripping all
those apps and. Yeah, I do.
So I've spent 10s of thousands of credits, not in dollars, but
yeah. So the the, but exactly how much
dollars it's so it's, it's a penny per credit.
So like basically 199 a month you get 19,900 credits.

(01:28):
But what I've found is that, youknow, they've sort of done some
estimation with pricing and early on they're actually giving
me a bonus. And so every time it renews, I
get like a double 19,000. So I actually get like 40,000
rather than 20,000. And then if you log in at like
5:00 PM every day, they throw another 300.
And every time no dynamics. Yeah.
And then every time, No, no, totally.

(01:49):
And then every time I do like a one star review, they're like,
oh, sorry about that. And they give me a bunch of
credits back sometimes. And so like, I feel like there's
this, I've never ran out of credits yet I continue to use it
more. And so at some level I think the
casino thing plays it where it'slike they're getting me really
used to the product and I like the results that I'm getting.
And so I use it more. And then they're like, oh, you
refer a friend and I've, you know, there's a bunch of

(02:09):
referral credits and I'm like, oh, you refer to five friends
last month, we'll just give you a, you know, 20,000 extra this
month. They'll just, they, they
literally just keep throwing credits in there.
So I've never ran out. I always have somewhere between
20 and 60,000 credits available,yet I'm constantly using.
But you're talking to me like I'm, I'm doing research where I
have Manus, you know, 500 hundreds.
They have wide search now, so you literally can run 100
parallel searches where it sits there and kicks off 100 and then

(02:31):
does the thing. So it's like, go look up, you
know, these hundred companies, go look up 100 people in those
hundred companies, go look up the.
And it's just like, yeah, it's really been fun.
And so I mean, but pivoting a little off that, I mean, Jason,
you pay for a lot of SAS, yes, and a lot of seats.
Like talk to me about that. Yeah, we have, I mean, we have a
lot of consultants, right, that are working across a bunch of
different founders businesses and, and some interesting

(02:54):
companies. And, you know, we're, we're kind
of scaling up and adding people all the time.
But I'm trying to pay attention.I, I never do the annual
subscriptions. I'm like, no, I'm going to do
the monthly because when these people, you know, rotate off a
project and maybe they're in between things, I'm turning off
the Google and Slack accounts. I'm not paying for that 10/12/14
dollar a month seat, right? Yeah, like I, I don't know.
So, you know, that's, that's my take on it.
I I don't like just like the SASper seat pricing, which is why

(03:16):
I'm excited about this conversation.
Today, yeah. I mean, I think, you know,
pricing isn't a spreadsheet anymore.
I mean, it's really like it's your product.
And I think like the narrative and your leverage like that
becomes kind of the everything in a lot of these cases.
Yeah. And the guest we're talking to
actually has built the platform and the playbook for what modern
pricing actually looks like. Scott's a founder and operator

(03:38):
who's helped companies transition from this old school
pricing model to a modern sort of dynamic billing model.
Yeah, and he's not just talking theory.
He's built the tools, he studiedthe patterns and worked with
some of the fastest growing SAS businesses that are like
household names out there. You ready to get into it?
Let's do it. Scott, welcome to founder mode.

(04:06):
You've helped rewire kind of modern software companies think
about revenue from, you know, fixed plans to flexible and now
to real time billing. We'd love to see kind of talk
through like where pricing breaks and what founders can do
to fix it. And so happy you're here.
Awesome. Well, thanks for inviting me.
I'm super excited to talk. Pricing is like one of the, I
would say, the harder parts of running a business and it's
something that we get to spend all day every day working on.

(04:28):
So I'm excited to chat about it.Yeah.
So you've said that pricing was always the pain point.
What was that kind of irritationor or thing that sparked this
whole journey for you? Yeah.
So before I started Metronome, Iactually worked at Dropbox for a
long time, for about 7 years andI ran what we called
monetization engineering. So that kind of think what

(04:49):
happens when you sign up on the website and then how do you get
through the funnel and then ultimately become a paying user.
We owned that entire journey andone of the things that we
realized very quickly was that experiments in that journey like
around pricing and packaging could meaningfully Dr. revenue.
So, you know, we would like optimize the checkout page, we
like change a few words and boost conversion rates by like
10% and make millions of dollars.

(05:11):
And so it was really cool because like pricing and
packaging is a huge lever for the business.
But the flip side was actually those edits like in the
fundamental billing system meantthat like even a very simple
pricing change, which sometimes takes months, there are certain
pricing models that were completely off limits just
because of the technique technology behind the scenes
couldn't handle it. And so that was the spark.

(05:32):
It was this idea that like we should be moving much faster.
We can't, we can't because this infrastructure doesn't work very
well. Well, and that was like thing
like like, OK, let's go solve that problem and figure out how
to like actually make it so companies can move much, much
faster and treat pricing more aslike a weapon rather than like
kind of AI don't know, like a like a, a reluctant thing that
you have to go do. Yeah, it's a long time Dropbox

(05:54):
Easter. I've definitely moved through
plans a bunch, and sometimes youget stuck where I'm like, hey,
how do I just get more of whatever I want, more people or
more storage? Was there like a specific test
you remember back in the day that was like, wow, that was the
one that was really like so frustrating and you're like,
this is broken. I need to leave and go do this
thing. Yeah, I think it was an
agglomeration of things. But like, So what we do now is
we really focus on consumption based businesses.

(06:15):
And at Dropbox, there's a lot ofour products that you could have
thought of as being like usage based.
Maybe it's the amount of like actions the product can take on
your behalf, things like that. Those we were just not even
allowed to try because basicallydo a price, a usage based
pricing model inside of the current architecture would have
taken, I think it was quoted at like 4 years to go build out.

(06:37):
And we were just like, well, there's literally no way that
that's mixed. Engineers, am I right?
I. Know exactly.
So I was like, that was the kindof thing I was like, OK, well,
there's there's something about this usage based thing that's
uniquely hard. It's like, you know, I'm not
getting three months, 6 month quotes, I'm getting year quotes.
Let's go study that problem and then go figure out why is that
so hard? What is different about usage
and consumption and, and, and can you make that faster?

(07:00):
Because if you can, then you'd unlock this entire new business
model set. So you made the case that like
this traditional seat based pricing, like I love as you talk
about usage and consumption, it makes so much sense to me.
But like there's still so many products that build that way.
And now we're in this AI era where we've kind of moved to
credits and tokens like traditional pricing.

(07:20):
I think you even have said like it's not going to survive the AI
area. I would love to hear more about
how you how you think about that.
Yeah, The way that I think aboutit actually is if you take a
step back to like the 90s and you remember I'm like old enough
to have gone into Newegg and like bought software.
Like a physical disk. Like install it on a computer

(07:40):
and you pay 60 bucks and that's it, right?
And there's no updates to it. And then you like buy an
expansion pack or something likethat.
And that was how software in the90s worked.
And like business software was bought same way.
But instead of you installing it, it's installed on a rack in
a server. But it cost, it costs a fixed
amount of money. You like own the bits.
The rise of the Internet, though, shifted the value of

(08:02):
software. Software now updates itself.
You know, like you log into Asana today and you log into
tomorrow and the product actually changes like the the
because the Internet allowed a continuous delivery of new value
to the product, it forced the creation of a new monetization
model. So subscriptions became a thing
before before the Internet subscriptions was not like
subscription software didn't exist.

(08:23):
So seats and subscriptions was born during the Internet.
And the cause of it was that thefundamental value of software
was shipping from something I buy and install to something
that continuously updates itselfand it's value scales and the
number of people in my org have access to it.
And so like actually, the subscription model was a
contingency based on the fact that the Internet came along.

(08:44):
And what I see with AI is now the value of software is
shifting again. Now, instead of software being a
thing that you consume, the software is doing work on your
behalf. So if you're familiar with like
intercom, those agents actually reply to emails on your behalf.
The software is doing work. Humans are, you know, maybe
they're setting up the agents, but they're not doing work using

(09:05):
the software anymore, at least not in in a lot of number of
cases. And so agents, AI is
fundamentally rewriting the value of software and much like
the Internet, the change in value of the Internet positive
business model shift. What is happening in AI is the
value of software is changing and that is forcing a new
commercial model to come in. And the only commercial model
that really makes sense is something in the usage based.

(09:28):
It could be hybridized with seats.
But basically the idea is how doyou monetize work being done?
And the historic way is you pay for the work and that could be
measured as credits, it could bemeasured as tokens, it could be
measured as outcomes, whatever it is.
But it's a very elastic measure.And it is and like, and it is
also anti seats because basically the more agents you
deploy, like you should be hiring fewer people.

(09:50):
So like the seats should go down.
And so actually the only incentive aligned business model
that makes sense in the AI era is something that looks more
like a consumption model. I still think seats will stick
around in some form, but mostly as like a platform fee and less
as like the kind of core scalingmetric.
How do you think about these hybrid models?
Like for us, like we take phone calls and so there's like a cost

(10:11):
to take the phone call. And then there's like if the
phone call was successful, you get paid more where there's like
still the cost for taking it if it doesn't as not as successful.
Yeah. Have you, have you seen that
very much where there's like a kind of a fixed or sort of
recurring cost for sort of doingsome amount of work and then
almost like a Commission or prize for doing something
better? And how do you guys sort of
think about that in your business to apply that?
Yeah, I think the dominant modelso, so think if you think of a

(10:34):
pure usage based business, thinklike AWS, OK, that works for
infrastructure businesses because when you build on infra,
you're not making changes that often to it.
You know, there's a certain amount of predictability in it.
You know that customers will show up tomorrow and use your
service. Now they make it a spike and so
you have to pay a little bit more.

(10:55):
But like you're banking on the fact that the infrastructure is
is there the whole time. And so a pure consumption model
works really well for businessesthat are kind of operating as
like the scaffolding for the rest of the business.
Why the token model, the LMS charge this way for the APIs,
but when you move one layer up into the application layer, a
pure consumption model has this like fundamental

(11:17):
unpredictability to it. Think of like Facebook for some
reason was like you paid for every profile you feed or
whatever. Like the variability on anyone's
usage is extremely high. But also the consumer doesn't
want to be faced with like if I click this button, I have to pay
money, even if it's a fraction of a cent.
It's like it incentivizes the wrong behavior.
And so in these more SAS businesses or take Asana or

(11:39):
Dropbox or whatever the the right way is like it's like pure
usage is too much variability month over month.
And So what you want is you wanta term in the equation that's
kind of more stable. This is where it's used like
seat based fees fit in. So then a CFO knows roughly
they're going to make at least this amount of money and then
they can build these nice product flywheels around usage
base. Maybe it's like, you know, this

(12:00):
call based thing that you're talking about.
If it's successful, you pay a little bit more.
If it's not, you don't pay anything.
And then what that does is it gives them predictability, but
also upside preservation. And the upside side is tied to
an outcome that the customer cares about.
So they're totally happy to giveyou that extra money.
And so that's kind of the way that I see the world, which is
that the hybrid is more stability plus upside.

(12:22):
And I think that aligns incentives like everyone wants,
you know, customers actually do you want the stability because
they want to roughly know how much they're going to pay, but
also they want to know that you're going to be in business
in two months if they don't use the product.
And, and so the stability is fine, but then the upside like
kind of usage comes in through the upside capture.
And, and I, as long as you can map the value of that

(12:44):
incremental usage to actual outcomes for them in some way,
they're totally happy to pay forit because they're, you know,
presumably if they had to do it themselves, they pay a lot more
money to get the same. Aligning incentives makes total
sense to me. Let's talk about early stage
founders and, and the mistakes that they often make when
they're setting prices, you know, maybe for the first time,
you know, how, how do you advisethem?

(13:04):
A lot of the folks that are listening here, you know, are,
are founders. Like what would you say to
somebody who's like trying to figure out their pricing and and
how to course correct once they've maybe gone the wrong
way? Yeah.
I think if you're early, there'sa lot of actually benefits,
which is that kind of what you price.
It's like not that risky. It like looks like a one way
door, but it really isn't because your business isn't a

(13:26):
one way door yet. You know, you're not big enough
that it like it's like, you know, if you had to like start
all over from scratch, it's like, yeah, you lost a couple
months or whatever. And that sucks, but it's not
that big. And, and pricing feels important
because it is important, but it's, it is much more of a two
way door than most people give appreciation for, especially
when you are sitting on $0.00 ARR, you know, like like 0 ARR.

(13:46):
It's like nothing matters honestly.
And so just move fast. The other thing is you should
not be innovating on pricing until, until and unless you need
to innovate on pricing or that'sa core differentiator.
And I think there are certain businesses like we could
probably talk about Clay, which actually used monetization as a
differentiation. I think that's super smart.
But they didn't do that until they had a product that was also

(14:09):
differentiated. And So what I would say is start
by focusing like in the early days, your job is to make your
product differentiated and you would probably exist in a market
and that market probably has a dominant commercial model.
Like keep it simple. Just do whatever everyone else
is doing. The reason why this matters is
because A, it obviously works for your competitors, and B,

(14:29):
consumers are comparing you to your competitors.
If they're comparing apples to apples, that's an easy thing.
If you have some weird exotic pricing, it's apples to oranges.
And again, if you're highly differentiated, then that can be
an advantage. But in when you're small, it's
like, why are you trying to differentiate on too
complicated? It's too it's you're
overthinking the problem. And I think that's to me, my

(14:52):
main advice is like, keep it simple, move fast, iterate often
and don't have like like when you're large, there is a like
sunk cost that you have to pay for.
But when you're small, like you don't have that.
So like just be nimble and move fast and no one will remember.
Like even there's very notable AI based pricing mishaps that
happened like 2 months ago. I guarantee you no one even, I

(15:14):
mean you probably name them. I can name them because I study
them. No one gives a shit anymore.
Like it does not matter as long as you get to the right thing
then consumers will forgive you.Like memory is really short.
Purely, it doesn't take you 4 years to make the pricing.
Change. Even if you're at 500 million
ARR, you can move. If you're moving fast enough,
people will forget and it is fine.
Yeah, you will. Fine.

(15:34):
You, you've talked about creditsbeing like a good starting
point, but not the end game. And I think about like 2 AIS
that I use a lot. I use a lot of Manus, which is
very credit based. And then I use chat GPD Pro
where I've never ran into the limit, even though I use
probably that a lot more. How do you think about those?
And kind of like what's your view on kind of credits versus
not? And then or maybe there is, I
mean there is a credit, I'm sureat some point if I hit ChatGPT
Pro hard enough, like there willbe a limit, but like it's high

(15:57):
enough that like probably a veryfew people hit it.
Yeah, The way I think about it is broadly, credits are a useful
kind of meta abstraction for kind of letting a customer
predict their usage. And then if they go over, they
can kind of get an overage bill.And it's like kind of a, it's
like a simple, it's like rather than having to make a decision
every time they issue a query, they kind of make one decision

(16:18):
once a month and buy a pack of credits.
And then if they overspend, theymake another decision In AB to C
business, if you're selling to consumers, you want to kind of
minimize the number of decisionsper unit time that a customer
has to make. So a, a well designed credit
system usually has like one decision upfront.
And then if you're finding a tonof value, then yeah, you have to

(16:39):
make a a re up decision. But presumably that's backed by,
well, I made so much more money because I use this thing and
say, fine, who cares? It's like a deal, I think.
And and so like in sometimes theideal credit system is one that
you understand is there, but youbarely you very infrequently hit
the limits. And when you do hit the limits,
it's because you're in a you're you're whatever your, you know,

(17:02):
job to be done is being really well satisfied.
The worst are when you hit limits and it feels punitive to
do more. It's like what?
I'm barely getting any. Like I'm having to use a lot of
credit because your stuff doesn't work that well.
Like it's like, it's like, it's like, it's like I'm feel like
I'm struggling against your system.
And so therefore I'm kind of pissed that I have to pay you
more versus like, wow, I'm getting a lot more value from

(17:22):
this. I'm sending a lot more in mails
or whatever. I'm happy to pay you more
because I can do a very simple ROI calculation.
I'd say for like things like ChatGPT, they all have embedded
limits. Most of the B to C ones are
designed so that only the whaleshit them.
And, and if you're hitting them,it's more of like almost always
there is a better package that is better suited to your use

(17:45):
case, right? So if you're routinely hitting
the pro limits, then you go to Max Pro or whatever it's called
and you go to like the suit and,and, and there are features in
that feature set that are different, like distinguished in
the package. So it's not just about more
units, it's about actually a better product for your use
case, if that makes sense. As a smart packaging design
pairs the like credit hate, likethe spend limits with features

(18:07):
that incentivizes more spend. It's like so like SAS guys need
the two extra author like you know, O author whatever.
Or something. Exactly.
The negative version is it's like, why do I have to pay 10X
as much for SSO? That's silly.
But like smart decisions are like, well, you're using a ton
of credits. What about asynchronous jobs
that run at 2:00 AM on Saturday?So it's way cheaper.
Like that's the smart version. And those features are only so

(18:30):
you use packaging to get the smart.
They basically you say actually it's the credits serve as a
packaging delineation for like this user actually is like a
power user and that fundamentally is a very
different need than than than a person who's just using the
product. I think it's like, I think
actually the other advice I giveto young folks or early

(18:50):
companies is that people think alot about price.
They think not nearly enough about packages.
Packages is about user segmentation and user
segmentation is actually the entire game of early stage go to
market. It's like, are you working on
the same ICP or not? And packages is a very easy
litmus test for knowing like if you find that you can repeatedly
sell the same package to the same profile of customer, you

(19:12):
probably have an ICP. If every time you hit a customer
that looks the same and you're constantly like kind of tweaking
and things and you probably don't have a stable ICP.
Yeah, I, I love that you're talking about packaging because
I think so often people just think about pricing and pricing
and packaging go together hand in hand.
You know, this is kind of a, a curveball question for you.
But as you, as you were talking,I'm thinking, man, what you guys

(19:32):
do at Metronome is so interesting.
Like have you ever thought about, you know, Open open AI is
now going after Mackenzie's business.
They're consulting, right? It's like because this Metronome
offer consulting services on packaging and pricing.
You guys probably should. There's a lot of stuff in.
Your head unpaid. That's like my unofficial job is
kind of offer on this. Do you think like one of the
benefits that we have is just because we see all of it, we are

(19:54):
we are very focused on on providing this to all of our
customers, make sure that they know the best in class.
And then we actually host, we'rehosting a huge conference in a
couple days that's like very much just focused on this.
And we're trying to build community around this stuff.
Because what I find is that likethe true experts that you pay
and like McKinsey consulting type of thing.
What I typically find is the industry is moving way too fast.

(20:14):
And so in reality, what you wantis a set of peers who are all.
Like elite level thinkers arguing and kind of figuring out
the market together. Because the other thing that's
happening in the market right now is that the market is super
dynamic where someone will discover like like the thing I
always like to say is like if you talk to any founder about
token based pricing, they're alllike, this is not good.

(20:35):
It is not value aligned, it is not cost aligned.
It is super confusing. It's really hard to communicate,
and yet the entire industry has standardized on it because the
first mover in the space happened to be the biggest mover
in the space, and they set a precedent.
I think they set a precedent that worked for them.
At that point in time, it was very simple.
But I think what we can all agree on is that it does not
feel like the right way to encode this stuff.

(20:57):
And now we're trying to find theright one.
And when someone does, then like, the industry will
reconverge. What do you think is the biggest
risk founders face when they're monetizing AI?
And, you know, I think in this case of credits and tokens, like
how can they avoid, you know, leaking value and that they're
creating with their product? Yeah, I think generally in the
early days my pretty strong. I mean I got this advice very

(21:18):
early with Metronome and I thinkit's important advice is think
about pricing as a product attribute.
Am I, am I the Porsche of whatever the heck you do, or am
I the like yacht or am I the like Honda Civic?
And it's not to say that that one car is better than the
other, right? Like if you're trying to drive
around the city, a Porsche is a pretty bad car.

(21:40):
But if you're trying to like look cool, it's a pretty good
car. And I think what people
misunderstand is that like pricing is a signal to the
market and it literally determines how your business
will win. And so when you're thinking
about pricing, it's like, do I want to be the like, do you want
to be like Amazon, the low cost player that wins over time by
compressing margin and basicallystarving the like low end of the

(22:03):
market and then give up the consulting fee, blah, blah,
blah, the huge deep deployment stuff?
Or am I the opposite? Do I want to be the like elite
group? And it's like, yeah, you get a,
you pay a price premium to use our product.
And that's because it's packagedwith great services and it's a
better product. And I think if you don't think
about pricing very, very early, like it's, it's inherent in your

(22:23):
business design because it informs what markets you're
allowed to go after. It also informs what people will
pay and it also informs your margin, right?
Because basically if you are, ifyou are like pricing as the, if
you're an infra, like a near infra player and you're pricing
at the low end, know that your margin will always be rager thin
and you'll have to do the Jeff Bezos thing of every, every time

(22:43):
I earn margin, I need to pass itdown through as cost cuts.
And you're doing that because the long term strategy is to win
the whole market and to just be ubiquitous.
And and then, and you shouldn't be envious of like the AI
company that's premium priced that has like 90% margin.
You like, you are not the same business.
Like you are playing totally different games.
And so I think one of the thingsthat I advised folks early is

(23:05):
like, think about where are you premium?
Are you like super low cost? Are you somewhere in the middle?
And how does that fit into your like ICP and what you're trying
to buy and, and trying to becomeas a business?
And then what are your competitors going to do?
Because so basically I think youhave to kind of like, it's like
a, you have to play that chess constantly.
And it's not to say you can't make a decision later that's

(23:26):
different, but I actually do think that what how this
manifests is people kind of likethey're way too especially like
technical entrepreneurs, they'reway too timid to ask for the
value that they're providing, right?
And so they asked for way too little and they get way too
little. And what we did in contrast, is
like, you know, thank you to ourearly customers, but we would

(23:47):
sell a deal and then the next deal, we'd be like double the
price. And like, we just kept doing
that until we found the upper bound and then couldn't double
it. And then and then we're like,
OK, well, like, here's what the market price is.
And I think that attitude of like really kind of using price
as a signal value was really important to us because if we
couldn't charge at least, let's say, 6 figures for what we're

(24:07):
doing, we didn't think we could build a business.
Like we just like, fine, then this is non viable.
I'd rather learn that in year 1 than in year 10.
Like, that's a much better lesson to learn.
You talked about like price as sort of discovering like the
value of your product. Was there anything in that like
early customers that helped you shape the infrastructure of like
actually how you built the product and what like features
you needed and like how you needed to design, like the way

(24:28):
you interface with these customers?
Because I think about like pricing is so crazy through a
product and then you guys building a product for that like
it's got to touch a lot of things.
Yeah. We started by kind of assuming
that, yeah. So we, we basically the problem
with pricing and monetization isthat literally you could

(24:49):
probably, if you were like name all the components, I could
probably name like 100. Like you have to have a tax
support and you have to have this kind of discounting like
you just like literally could spend like an hour talking about
it. And So what we realize is like
we're a small startup. We cannot build 100 things to a
good level of depth. So what we had to do was
identify the narrowest possible subset that would actually

(25:09):
satisfy market need. And so why we started with
consumption pricing was because that part of the market had no
vendors and it had these like 3 problems that were super deep
and super narrow. And if we just solved those 3
problems, we'd be able to like sell software and it let us not
build the other 97 things. And, and that was like a way to
get into market early, get validation and start really,

(25:32):
really narrow. And so we basically
deconstructed the product space like if you like, you know,
literal sense Metronome doesn't do billing in that we do not
send invoices to end customers. It's like that's not a billing
system. I'm like, I agree, it is not a
billing system. We are a monetization infra.
We do this narrow set of things.Now over time, we like do more
and more and more. But the point being that we
purposely designed the business to be very narrow targeting only

(25:55):
engineers focus on the hardest technical problem that they did
not want to do. And and then we are completely
coherent with them owning the like front end of the experience
and and the kind of end user experience of of purchase
product pricing and packaging. And we kind of just took the
hardest, most annoying jobs thatthey all hated and caused them
to be on call all night and we did those and then we and then

(26:18):
they paid us for that and then they were able to like re staff
on the more sexy things. Yeah, I don't want to be on.
So what do you think, what do you think pricing looks like 5
years from now Scott? Like is it consumption only
outcome based, something else? What's your?
What are? You, I think it looks like all
of it. Like I think honestly the
history shows us that like basically pricing and packaging
just gets more complicated over time.

(26:39):
My meta theory of software is that it's a relatively young
category. Like, an analogy I like to make
is like, toothbrushes have been along around for like 200 years,
OK. And like, mechanical
toothbrushes existed in the 60s,and yeah, then there was like
slightly fancier ones in the past 20 years.
But like a toothbrush is a toothbrush.
Pricing and packaging for a toothbrush has changed

(27:01):
dramatically. You can buy it on a
subscription, you can buy it in pieces.
You can buy it, you know, in bulk, in giant things.
And like, actually the battleground for toothbrushes is
only about pricing and packaging.
And so my theory of every product, but basically is that
overtime, as the categories mature, the battlefield shifts
to pricing and packaging. Think hard drives, right?

(27:21):
Hard drives. For a long time they competed on
features like, you know, this isflash storage or this is like
whatever a disk and this is, youknow, all this stuff that I
don't know that much about. But basically like for a long
time it was a feature battle. And then in the 20 tens, it kind
of stopped that way. And now it's like market share
is won or lost based on pricing and packaging.
And is it in the cloud or is it on Prem?

(27:42):
Is it all this stuff? And, and so I actually just
think that over time, what's going to happen is all of
software kind of will get held to like every other product in
human existence, which is that pricing and packaging actually
becomes the dominant form of competition.
And, and I think the good thing about software is it's
constantly evolving. So you'll always have some
newness in there. But broadly what I think is
going to happen is that pricing and packaging is going to become

(28:03):
the battleground. So I think what's going to
happen is you're going to see seats, you're going to see
hybrid, you're going to see consumption, you're going to see
like outcomes, you're going to see flat fee licenses, you're
going to see everything and and it just gets it's kind of like a
one way complexity engine. I don't think it ever re
centralizes something simple. I think in some sense SAS like

(28:23):
seats and subscription, it was the was was like very simple
because software as a SAS software as a market was very
immature. And what you've noticed actually
you can see it even now seat based software is actually very
complex now. It has like complex
entitlements. It has complex like, you know
like Slack will have like usage based seats.
So if you don't sign in on a Saturday, you don't pay.

(28:45):
It's like in 2009 when the stuffwas invented, it was like all
the same. And now it's actually rightly
complex. And I think the main thing I
would just say is complexity increases as industries age.
That's like my main prediction. And I do think the good thing
about usage is that there's nothing really more fine grained
than that that I can think of. Like outcomes are just a flavour
of usage. It's like your outcome is my

(29:05):
usage. Like it's not these aren't,
these aren't different, they're just the same.
And ultimately it kind of redounds to this like stream of
things that happened in your product that you and I agree on.
And I choose this, I value them at this and you charge me that.
And it's like kind of what will that's to me, like the terminus
of all this stuff, is that it will all be that and then it
will be reconstructed in fancy packages.

(29:25):
Awesome. So last question, you didn't
talk about pay what you want andwe've seen a couple of these pop
up. Is that just the hype thing like
a marketing thing, or is that something that actually has
staying? Powerful.
Wait, what's an example? You know, somebody comes in and
says, hey, the price can be whatever and I've like you join,
I've seen memberships where you join a membership and you can
join from $10 or you can join for 400 right more.
Common in like communities, creators like Patreon.
Yeah, it's like a. Donationist kind of thing or how

(29:47):
do you, it's like they're sort of saying, how do you value it?
I don't even think the V1 pricing stuff had this right
where it's like, oh you can buy this software and download it
once and pay us whatever you think.
It's these devs that are like more open source guys.
Indie building the indie dev model had it for a bit totally.
Yeah. I think of that as like, yeah,
it's almost like tipping in a way, right?
There's some base fee and then you're like tipping on top and

(30:08):
you know, if you get a ton of value, you get a lot.
I think that makes a lot of sense in places.
Like basically that kind of pricing works.
Like it's interesting actually. There's different types of
pricing that work depending on your trust model.
So this is a high trust model, right?
Because basically I'm going to give you a lot like I am
trusting you, the community to take care of me, the creator.
And basically the more of a relationship with me, the more

(30:30):
you're going to pay, the more you have more money in your
pocket, you're going to give me more.
I think actually outcome based price is another very high trust
model or it only works in high trust environments because
basically outcome based pricing in theory is like I am paying
you for some business outcome that occurred.
Let's say that like there's somemagic sales bot and it drove
sales. OK, In order for that to be

(30:50):
priced as outcome, the followingconversation has to happen.
You and I agree this bot did some work and but you know, I
objectively made $5 million thisquarter.
What percentage of that do I attribute to the bot versus the
humans that are involved? And, and what is the uplift?
The only way to even have that conversation in any way that's
saying is if you and I have a deep level of trust.

(31:12):
And so of course the way we see outcome based pricing actually
working isn't like, let's take that exact example.
What would happen is you do a three month trial of the
software and basically you baseline the pre bought revenue
and then baseline the post bought revenue.
You can say, look the spread is this and we're going to charge
you X percent of the spread. And then and then and the next
quarter we're going to true up, we're going to do the same

(31:34):
experiment and we're just going to basically goal ourselves on
increasing the conversion rate or whatever.
And but think about that entire like journey, I have to trust
that your revenue number is realand you're not like hiding I
don't have access to your systems.
And so it only really works in these more high ROI use cases
like call center replacement. This actually works pretty well
because the deployment cycle is 6 months and I'm on site with

(31:57):
you and I'm seeing that you're literally not hiring people.
And so I'm like, cool, that headcount never appeared on your
PNL. I'm going to charge you a
fraction of that. That's why I like Palantir kind
of gets to this level of of thing, but it really does
require a deep trusting relationship.
And so for me, I actually think one of the interesting things is
that like depending on the trustlevel between you, consumer and
vendor, you can actually get to very different outcome outcomes,

(32:19):
but also just different pricing models.
So yeah. Makes sense.
Where can people follow you Scott?
How can they find you online andand where?
Where can we send them to learn more about Metronome?
Yeah, so I'm like primarily on LinkedIn, I think like I spend
my time in the cringe cringe factory, but but it's fun.
And then the other is just our website, ismetronome.com and

(32:41):
yeah. Offer for like founder mode
listeners companies that are looking to definitely just.
Send me, send me, send me a noteand we'll make sure you get the
the founder mode. We can include include the Scott
e-mail in the show notes so theycan reach out to.
You sure, fine What it's fine. I'm a founder or you know, I'm
used to it, but or you can e-mail, e-mail sales at Metro
NEMA mentioned in founder mode and there we go.
We'll do that. Make sure we'll make sure you
get taken care of. I think like, you know, I think

(33:02):
especially if you're early, we have pricing that's really
designed that it's like frictionless pricing.
Nice. And so if you're like very
early, what we typically say is it's nice to get these systems
set up, but our core scaling value metric is you should make
more money. Obviously, if you're at 0 ARR,
like, you know, zero times the number of 0, it's fine.
We'll make sure that it works for you and that you actually

(33:23):
find value. And our goal in that first stage
is to help you discover repeatable product market fit
and use pricing as a part of that.
So our goal is not to monetize you.
So, but yeah, we're super excited to work with companies
from public companies down to like two people in a garage.
We have customers of all stripes.
Awesome, thanks for being here. That was super sharp and
appreciate it. Sweet.
Thanks, Scott. Thanks.

(33:44):
That was an awesome conversation.
So good, Scott, sure is how pricing isn't just math, but
it's really just a critical partof your strategy.
Yeah, and he reminded us that billing, when done right, isn't
invisible. It's a product and a growth tool
and a competitive edge. Kevin, what were your top five?
Yeah. So I think the big one and and
we're seeing this, you know, AI sort of drives this usage and
sort of outcome based pricing hybrid is going to become more

(34:06):
common, right. It's this really like, you know,
seats plus usage and that gives you this stable base, but also
the upside when things go right.Yeah.
And then for early stage, it's really just copy the market,
right. Don't try to invent yourself,
don't try to do anything crazy and then just be willing to
iterate fast. Yeah.
Packaging is sort of bigger thanprice, you know, to really
understand segmentation and likeare you selling and have you

(34:27):
nailed your ICP? And then price really is that
kind of long term positioning test like testing that ceiling
daily, like are you actually understanding where you fit in
the market and what the value that you're closing?
If this helps you rethink pricing or made you realize that
maybe your billing system could use a little work or is holding
you back, send this to your CFO or your product team.

(34:48):
And if you're enjoying founder mode, drop us a review, like
subscribe or comment and send this to somebody who you know,
thinks about dollars and cents. That's it for today.
Because in SAS, what you charge is just as important as what you
build.
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