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Category: Business Strategy
Tags: AIMonetizationPricingStartupsStrategy
Entities: A16ZAnna PinolAWSFinAIGitHub CopilotIntercomMadavanNFXPete FlintSalesforceSuperhumanTrulliaTwilioUber
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[Music] 20% of what you build in tech drives 80% of the willingness to pay. This I've seen it over and over again.
>> Why is AI making us think pricing generally? >> I think products have very increased autonomy and very increased attribution.
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That actually gives you insane monetization potential. And if you don't capture that from the get- go, you're training your customers to expect more for less.
And then that's a slippery slope, right? So, how do you capture that value?
[Music]
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All right, Madavan. So good to have you and so good to see you again.
Um, I'm Pete Flint, joined by Anna Pinol from NFX. And so it's such a delight to have you back uh on the NFX podcast.
We go back a long way, way back. So
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>> um, a little bit of context. So we were together like a dozen years ago when you were at SKP >> um doing some pricing work at Trullia.
Um and you you I think you'll get into this but we at at truly we started with
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a very simplistic pricing idea like what can we sell um and what is easily understood really really quickly and we left a lot of value on the table and then we were lucky to be connected with you and you came in and really helped to
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improve and had a level of sophistication about pricing and insight which was was not only economically super valuable, but I actually found it fascinating um just just professionally cuz it's just this mix of of um uh
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psychology and economics. >> Yeah, absolutely.
And it was also timely. It was before the IPO, I think.
>> Exactly. Yeah.
>> Yeah. >> So, yeah, it just I think it sort of pretty quickly added seven figures to the bottom line.
So um uh and you've and we stayed in touch over the dozen years
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and so maybe share a little bit about kind of like what um you know a little bit of kind of how you spend your time and perhaps what you're doing right now. >> Absolutely and it's super awesome to be back.
Thanks for having me. So I mean the last uh 15 years I pretty much spent
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working with tech companies on helping them with monetization. And so I worked with over 250 companies, more than 30 unicons, you know, navigating monetization challenges.
I did this in a professional services capacity, SKP or Simon Ker and partners like you called it. Um, you know, me and my co-p Josh
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who was also at Simon Kutcher, we, you know, left last year towards end of last year and we started a venture firm. That's what is keeping me busy now.
I mean combined the two of us have worked with over 500 companies. But the reason we actually uh you know pivoted to like
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uh venture was to specifically also work with very early stage AI companies and we can unpack a bit of that. But my uh you know life right now is uh invest in companies roll up my sleeves and work with founders.
And you've and you've written a couple of books. You've written um the first one uh which is
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monetizing innovation which um which I've highly recommended to so many founders. Um and then the the most recent one which launched just a couple of weeks ago is scaling innovation which is really thinking about monetization in a AI first uh environment which we're in
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now. >> Exactly.
I mean not just building great breakthrough products but how do you build a great business especially AI focused. >> Great.
Yeah. So I think so today we really want to pack in you know we we spend a lot of time Anna and I and and the rest of the firm at N effects thinking about how do founders think
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about pricing in this crazy AI world where you've got these breakthrough products but you've also got a world where you're seeing software become increasingly ubiquitous and potentially commoditized as well. So so maybe Anna you'll kick things off.
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>> Yeah just to kick things off. So, ever since this new wave of AI companies started, it was pretty obvious um to all of us that this new technology was unlike anything we had seen before, by investing early in some of these companies, we were quickly exposed to the new possibilities in terms of value
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creation and as a result like to emerge in terms of value capture. Um and and we often find ourselves discussing pricing with our founders >> as I'm I mean and and one of the things that I wanted to kick this off with was
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how have your own conversations around pricing evolved over the last few years in which we've been in this era and why is AI making us rethink pricing generally? Yeah, I think the big there are a couple of big changes that have
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happened, right? I mean, if you think about uh AI monetization or pricing, when should I think about it has changed dramatically because in the previous vintage of companies, we could still say let's just grow and figure out monetization when you're running a 80%
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SAS margin business to some extent, right? You can't do that in AI for two reasons.
is one there's cost dynamics to navigate from the get- go and there's also like value capture like you rightly said I mean if for the first time I think products have very increased
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autonomy and very increased attribution that actually gives you insane monetization potential and if you don't capture that from the get- go you're training your customers to expect more for less and then that's a slippery slope right so how do you capture that value if you're building something as an
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agentic you know AI product for that taps into labor budgets. Labor budgets are 10x compared to software and IT budgets.
So if you use the old playbooks, you'll completely undermonetize. So what we are seeing is you know monetization and GTM is becoming really really important even in
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the preed and seed companies and even in the previous you know vintage of companies we could say that if I have a 2-year coding head start that is a mode. You can't say that anymore right?
I mean you can probably code things up in overnight. So what is the mode?
you need to have some you know proprietary
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training data network effects and also like GTM becomes a moat uh and in that perspective your monetization model becomes a mode and how can you have durable revenue so all these questions kick in from day one so what has really changed is the focus starts much early I
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mean that's kind of also why I alluded to the fact that you know that's why we also pivoted to like work very early in a venture setting where we are investing and operating as opposed to being on a fee for service model ourselves We we changed our own pricing model if you think about it right. It was more on the usage.
Now we are on outcome basis.
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>> Yeah, that's awesome. And have you seen this happen before?
I guess there's been like prior waves, prior technology waves that have also been known for setting new pricing models. >> Yeah, I think with every um technology wave, there's been a new pricing model innovation that's kicked in, right?
I
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mean if you take Salesforce back in the day you know SAS pricing was a huge uh shift from like on on-prem um you know perpetual licenses I mean to take someone like AWS for instance the you know pay as you go for infrastructure
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that was a big wave that actually started um even companies like Uber started like dynamic pricing as a wave on its own with AI what we are seeing is there's probably a move and impetus to be more outcome driven because we are moving from a you know buy software for
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access to buy software for work delivered and I think that is where the industry is heading the way I see it >> and you are you're a big proponent I mean in your book you talk a lot about um encouraging founders to have willingness to pay conversations early
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um a little bit align with this idea of like pricing is very important since the get-go what are some tactics that you can share to do a good job at that Yeah, sure. I mean, early willingness to pay conversation is really important.
I mean, let's talk about the why, and then we can talk about the how. The why,
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because if you just build a product, slap on a price, and you throw it out, you're just hoping. You just don't know.
I mean, what we talk about testing for willingness to pay is like testing for just like product market fit, right? I mean, entrepreneurs know that.
I mean, if someone comes and asks me, do you like the sparkling water? I like it.
Do
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you like it for $25? The whole conversation is different, right?
So unless you put actually pricing as part of your product market fit, you often hear what you want to hear, right? So willingness to pay is critical.
So you can at least identify even before you're launching your product. Is this product
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something that people need value and are they willing to pay for? And then architect the product around it.
And if if you find there's no willingness to pay, the most important question is to ask why. And then you start hearing all kinds of things that you can actually productize around jobs to be done and unmet needs.
So that's the why. It's
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very critical. Um it's like test and learn, you know, monetization before just slapping on a price and hoping on the how to do it.
Um in the book monetizing innovation, we devoted an entire chapter to that. It's chapter 4.
That's the most important chapter to
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read for the listeners. But I might like let me just unpack maybe you know one specific tactic that um actually Rahul Wara used when he you know came up with his own monetization was superhuman, right?
So what we call is uh it's like the acceptable expensive and
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prohibitively expensive questioning to understand psychological thresholds. So the way that works is you know you take your product you know your wireframe blueprints demos free trials whatever I mean that just put people through the experience of the product.
So you're having your same sales and marketing
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conversation that you'd actually have um you know and then and then have the pricing conversation. So once they understand the value, ask them what do you think is an acceptable price.
You know, clock that answer. Then ask them what do you think is an expensive price.
Clock that answer and ask them what's a
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prohibitively expensive price. This is a very stylized way of asking.
If you just go and ask something like, you know, how much should I charge for this project? You should charge for this product, you'll probably get garbage back, right?
I mean, that's your job. But if you ask it this way after you have pitched the
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you know entire product the sales marketing conversation you start hearing something reasonable because acceptable price tends to be the price where people are negotiating with themselves. That's the price that they love not just your product.
So they're going to lowball all day long. Expensive pricing tends to be
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where it is around your value price. And prohibitively expensive tends to be where they'll laugh you out of the room.
Now if you do this a bit statistically with like let's say even 100 200 people on an online study or however you administer this you start seeing that these demand curves have cliffs like for
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instance after 29 if you go to like 31 suddenly 20% of people actually think it's expensive or you know or 40% don't find it acceptable etc. So then you start seeing these psychological thresholds that's how you know that okay you need to be right around that price
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point if you cross it it's going to be a threshold. So Rahul actually used this for superhuman and found that you know $30 was a great price point for the product that he had and that's also how we actually launched it at a $30 price point.
And he was talking about this in
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an A16Z podcast. That's where I learned that he read Monetizing Innovation and did this and we've been great friends since then.
>> Out of these out of those three different segments uh acceptable, expensive, prohibitively expensive, like where do you want to anchor? >> Yeah.
So if you're in the look, if
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you're if you truly want to be price value aligned, it's typically on the expensive. Probably expensive is like, you know, you shouldn't be there.
That's like it's a price premium paradox where you just want to overpric thinking it's good, but you're actually going to hurt yourself. If you're in the uh acceptable
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zone, maybe in the growth phase, it's still okay to be there because you can actually then you're going to get a lot more acquisition. >> As long as you have a land and expand strategy, it might be just fine.
>> Yeah. Okay.
>> Yeah. But if you want to start off with a value price, then the expensive price is probably more closer to your value
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price. >> It's the price where you know people don't hate you, they don't love you, they're just neutral, they'll pay you.
So >> I'm curious thinking about like popular like GPT cursor um there there are many claims that they might be not fully
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capturing the value that they're delivering. Like what do you make?
Yeah, I think it's um there are some self-inflicted anchors in that space, right? I mean, is a $20 price point actually, you know, good or can it be more?
I mean, back in the day, Copilot,
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GitHub, everyone started at 10, they moved it to like 20, 30. I mean, there's some anchors, right?
I I I really think that for for that you need to really understand what value you're actually bringing to the table and can you charge a value price based on that and can you
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contextualize that you know pricing I mean we talked about superhuman but just to drill down a bit on that one of the chapters we write in scaling innovation is called beautifully simple pricing and how do you keep it simple and he when you think about it when Rahul actually introduced superhuman he was competing
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with free alternates Gmail and others like why would people even pay money for another email app was a question mark but he was actually delivering core value which is you know I can free up your hours and increase your
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productivity because you can you know log into an outbox etc. But the key there was the beautifully simple pricing talked a value story.
So he didn't just say it's a $30 price point. He said it's a dollar a day to get 5 hours of productivity back in a week.
Now that
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$30 doesn't look too expensive, right? And that's actually how everything took off because okay, will you pay the price of a latte to get 5 hours back?
Absolutely, I would do it, right? But so the entire premise was on the value where many of these coding agents, wipe
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coding, etc. while they're emphasizing um you know the fact that you can do things fast, they're not emphasizing necessary the value.
So instead of a $20 per month, if it's a $30 one $1 a day to get incredibly efficient at coding and
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save you like five hours or 10 hours a day, would you pay for it? You would, but you probably never charge.
So why should I? So I think if you start wrong, you kind of end wrong.
Then of course it's a different strategy. You can say I want to grow uh I mean you you see some of you know some of these companies
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having like very fast ARR but we can talk about whether that's durable. What are the margins?
there a lot of question marks. >> Do you have a do you have a point of view on margins?
It's cuz it's it's such a it's such a competitive environment out there and any good idea is
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replicated very quickly and >> with the cost of software coming down it seems the sort of incumbent SAS businesses are kind of holding on to >> margins but it's are we in a world where you know the you see many of these AI
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companies launching and their margins are 90 plus% because they're first mover and they're rep and they're replicating labor budgets whereas you're mentally like well how sustainable are these margins long term >> do you have a point of view on how
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things will evolve >> yeah I think the the key is uh to focus on uh you know both market share and wallet share right that is that's how I see it so it's more profitable growth it's not profits it's not growth it's profitable growth that's also the
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subtitle of the scaling innovation book how to architect profitable growth and what that means is it doesn't mean that you need to have you know equal efforts at any given point in time on market share and wallet share but you need to have equal attention in the sense that
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you know even if you uh gave away on price to actually acquire customers um are you thoughtful about the fact that you can land and expand later and you have a clear vision on how to actually you know go towards wallet share and similarly you know if you
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started more on the wallet share side because you think this is a new market that you can start shaping. Do you have an alternate to actually create a low-end product to actually gain more market share?
So, it's being thoughtful about it and having equal attention but not necessarily equal efforts because at certain points in the company, you might
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actually want to index more on one level or the other. But the best CEOs have been the ones that can actually think about the interaction effects between you know acquisition, monetization and retention and that and then you start building towards profitable growth.
So
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while we talk about some AI companies having high margins on the flip side some of them have really low margins like especially if you take you know some of the coding ones that we talked about I mean there was a tech crunch article that it's either neutral or negative in terms of margin right I mean
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um and if you have a lot of ARR at negative margin or neutral margin we can question is that a great business or do they have a pathway to get to you know better margins would they build their own model is there efficiencies that we will see or if it's just hoping that the us would come down. Hope is not a
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strategy. >> So founders, you know, ask us every day like just how do you think about monetization strategies and what are what are some of your frameworks to think about monetization strategies for early stage startups?
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>> Yeah, I think there are two questions that come up and maybe I'll be curious to see if it comes up in your conversations with founders and if those are the right ones we can unpack each of those. The first question that comes up is um you know how do I charge for this
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product like what's the pricing model because often we say how you charge is way more important than how much should I be on consumption based should I be on seed I saw someone else doing outcome should I do that so like what should I do right I mean that's closely tied to your uh operating your business that it
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it comes up and that's a sort of choice that you take earlier on and the other question that comes up especially with B2B AI companies is hey how do I navigate PC's I'm getting into these commercial agreements my buyer wants to see whether these products deliver value
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how do I charge for it how do I navigate these big deals right so those two questions keep coming up in the preede and seed stage >> and so and so let's just >> is that same with your companies >> yeah it abs they're like okay we have a breakthrough product idea >> we know that this is I mean I think
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there's a in consumer um it's uh you know that in some is the superhuman stories as a reference point for some of these consumer applications. Um, but in B2B it's kind of more complicated because there's a sort of deeper
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engagement. So maybe just walk us through how you might how founders might think about kind of navigating the price discovery with with customers who are who are which we see today like enterprises and and and SMBs are so open
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to AI. They've kind of experiencing it in their daily life.
They say, "I know this can be helpful." Um, so they're very open and receptive to conversations and founders are building amazing tools, but they are not clear how to navigate this dynamic. I mean, what is the value
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I'm delivering and what is the price I'm able to to charge? >> Yeah.
No, totally. I think let's probably then talk about navigating those big deals first and then we can come back to the pricing models later.
So these PC's have become critical
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because like you said there is a lot of curiosity on the buyer side right and also a lot of budgets to experiment. They want to see if AI can actually help their internal efficiencies and things like that but they don't know how.
So they keep asking these AI startups and companies saying prove the value.
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>> Yeah. >> So now the classic mistake that a founder makes is approaching the P as a technical validation.
Right? Because if you're just approaching it as will my tech work in the environment of your customer, you're not really proving out any business case at all.
Right? So we
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actually talk about when you think about PC's is to frame a PC as a business case validation exercise. Tech is tech validation is part of that.
So which means that you know you try to co-create an ROI model with your customer. So what
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that means is you know you start the P and say okay it's a finite amount of P maybe a month two months 3 months whatever not more than 3 months typically and then you say okay for that period we are going to jointly create a business case why is this important because the
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buyer on the other side now actually participates in that co-creation and becomes the smarter person in their organization where they can actually shepherd it after that you know 2 to 3 months and say hey this product will actually unlock X millions for us and we
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should buy this, right? I mean, so you also inevitably make them smarter.
And the other reason to do this is if you just work on something and show up with an ROI model, no one is going to believe you. If they work with you on the inputs, they will, you know, believe the outputs.
As simple as that. So framing
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the P as a business case exercise where you're building a business case saying is there value generated from that AI and being on the same page with customers. This is the key thing and if you don't do that it's a mistake.
Um and
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when you actually do that there are various uh you know things that you need to think about in terms of how do you value sell, how do you create an ROI model, how do you negotiate all of those things become critical but you postpone the pricing conversation to after the P. So the P is typically a fixed engagement
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only to build the business case. Then you tell the customer that okay look commercial discussions will follow because you want to clearly upfront state that otherwise your PC becomes uh you know PC price becomes the anchor for your pricing they just multiply by 12 times.
>> How do you handle like one of these
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customers being like no I don't want to I don't want to postpone this pricing conversations because it's important for me to know now. >> Yeah absolutely.
So that's a that's a great question. Uh if you're asked for price during a P and pushed what would you do?
I would say you should talk
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about price um but in a you know more uh let's say strategic manner. So there are a couple of ways to deflect that question and that's the most important thing right.
So you can say hey look no the goal of the P is to actually you know create that value case and we can
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talk about you know what portion of that we deserve. Let's assume the buyer on the other side says that looks theoretical I still want a price right.
So another way to deflect this would be you know you can say look you know customers like yours have been able to unlock you know tens and millions of
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values and we are typically on a 1 is to 10x in terms of you know your investment in us and the ROI that you get out of it. So, you basically just communicated that you're probably a million-dollar deal when actually it comes to it, but without actually saying it, some
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customers will be satisfied by that because they're like, "Yeah, 1 is to 10 songs fair. We will deal with it.
We'll finish the PC and we'll come to it." If they push you even more, then don't give just a price point because that'll be the most artificial thing you can do because you're also guessing, right? So,
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in that case, I would give a range. I would say look it can be anywhere from 500k to a million for the first year where we would be will depend on how much value unlock we can actually do for you and that is why we are bringing that is why we need to do the value case so in all of these conversations you're
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bringing the focus back to the P is a business case exercise and how do we co-create value but I just answered that okay it's a range I gave you predictability beyond that you don't need to and where you are depends on the business case and if you unlock 10 million you can be on the right side if you're unlocking three you're probably
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on the left side right so I think that's also how you can navigate this uh more uh the best negotiators or the best you know founders who are selling um hardly reveal their you know price because if you don't understand value what is price
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>> is there any are there any tactics to communicate value because I think it's like you might be able to >> Mhm. It may be that I don't know there is um the VP of sales which is using the product but they the CFO may deeply
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understand the kind of value story and so just in incorporating into the product the demonstration the value. Have you seen any companies that do a really good job of demonstrating to constituents the value that they create?
Yes, I think um absolutely and the
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lesson learned in those situations is being uh you know very structured and systematic in terms of how you communicate value, right? Random statements of I'm actually saving you you know this or that just it's kind of lost.
It has to be systematic. So you're
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almost training your buyer to repeat the message that you're giving them internally and they become internal champions. So the best ones actually say hey look there are three categories of you know value that we actually provide.
The first one is incremental on your top
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line based on your business KPIs. So that could be we generate more revenue for you.
We reduce churn. So these are all incremental right.
So that how are we participating in that? If you are communicate that that's separate from every other value element.
So we actually improve your topline. The
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second one is we actually save costs. That could be other license cost savings.
It could be headcount reduction. It could be you know um some tangible cost savings that just happen because of AI.
Right? So these are the cost savings which a CFO would actually like.
Right? And the third one is
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opportunity costs which usually a CEO would like right because you said I'm also freeing up you know 10 to 20 hours for the team on a weekly basis. That can also be quantified.
what would they do with that time? You know, what is that actually worth for the organization?
So,
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when you put it into these three buckets, the incremental, you know, topline, which is really important, everyone cares about it. The cost savings, typically the CFO function and others care about it.
The opportunity cost definitely the management team actually cares about it. Then you can
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start putting your value story across these categories and then train the buyer to actually go paraphrase that wherever they are in the organization. And when you say trained, you mean you mean prompts within the product?
I mean, not prompts in terms of AI prompts, but just kind of visual prompts in terms of just reinforcing the value that's been
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created at every interaction. >> Correct.
And I would even uh, you know, in a negotiation when I'm, you know, I tell founders this, you know, pause and ask them the questions. Hey, this is what I said, you know, how we will add value.
What do you think? What did you get out of it?
Like if you had to repeat that back to me, what would you say? I
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mean, just is a very like I just want to know you understood what we saying, right? I mean like like how do you think about it?
>> They say the best products are those that get people promoted internally, right? >> Absolutely.
>> Get the champions of Yeah. promoted internally.
>> Exactly. And and this is I mean if you
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ask it in the most uh innocent possible way, it's a great test. The we talked about, you know, beautifully simple pricing, right?
One of the tests for whether you have a beautifully simple pricing is Monday morning, go back and ask one of your customers to play back
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your pricing strategy to you. If they cannot, you don't have a beautifully simple pricing.
It's just complex as hell and you probably somehow sold it and they don't understand it. If they didn't understand how they were charged, they don't understand how the value is created.
That's a churn situation waiting to happen at some point. But if
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they can articulate and say hey your pricing makes sense because we get this the price value realization is aligned. So, we've seen we've seen the the evolution of SAS and and in this AI world move from this um uh per seat uh
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licensing to a lot of the exciting stuff is on outcomebased pricing because how do and you've you've got this 2x two matrix maybe break that down for us and and kind of what types of companies are kind of able to capture
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most of the value. >> For sure.
And I think it it the 2x two it goes back to the you know same two dimensions I talked about in the beginning autonomy and attribution right that's really what's changed with AI. So if you think about a you know 2x2 with autonomy on the y-axis and attribution
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on the x-axis >> and low high low high if you take the you know bottom left quadrant where autonomy is low and attribution is low. When we say autonomy is low that means you still need a human in the loop.
You're operating as a co-pilot. Attribution is low in the sense that you
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know your product probably is good but you cannot it's not directly tying into any kind of business metrics that your customers are tracking right so if you are in if you're in that quadrant you're kind of relegated to a perceived model right I mean even if you take a company
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like Slack for instance you can say you know I use Slack and my productivity went up but you can't measure it you can't meter it you can't monitor it you can't charge based on it Right? So the attribution is low and uh it's autonomous autonomy is also low.
It's co-pilot. So that's necessary in a
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seedbased licensing model. But if you take the bottom right quadrant where attribution becomes higher uh and autonomy is still low.
You're still in copilot but you're adding a lot of value. This is also where you know some of the coding platforms have started moving like cursor for instance is here
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or clay is here for instance right where it's a hybrid model makes sense. So it's still a seat but then you also overlay a usage component.
So like certain packages might come with certain number of AI credits and if you use it after that you know you can buy AI credits on
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top. So there is a blend between a seat and a usage model.
That makes sense because it's still co-pilot but the more people actually use it the more value they're getting. So I want to monetize on that.
Right? If you're on the top left quadrant autonomy is high but
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attribution is low. What that means is there's no human in the loop needed for these AI products.
They kind of live in the background and do do their stuff, but they're not directly influencing the KPI of your businesses. So they are more background infrastructure tools,
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platforms. So they have to be purely on a usage based basis because that's your best proxy for value.
There's no seats involved. So there's no point and it'll be bad.
But a usage is the best proxy for value. like you know a company like even the classic Twilio would be
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probably in that kind of quadrant right if you take the top right quadrant that is where autonomy is high and attribution is high that's the kind of exciting quadrant if you can be on uh what that means is your AI is you know fully autonomous and can also do stuff
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that is highly attributable then you can be on an outcome based model that's uh you know the holy grail of uh AI monetization um it's not for everyone because many products uh you can't show attribution uh you I mean even if you show it do do
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people believe it uh is the loop closed uh is it fully autonomous so I think there's still work to be done we are seeing about you know less than 5% probably around 5% of companies that are right now in AI on outcome based we do predict that this will go to like 25 to
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30% in the next 3 years and I think that's kind of where people are moving and we can talk about that but a good example of a company here would be um like if you take intercom they develop finai. So the way it actually works is if the AI agent is able to like you know
31:36
uh autonomously resolve a customer support ticket without any human intervention then they charge for it. If a human intervention is required then they don't charge for it.
And there is selfattributional loops built in here because the customer might say I'm satisfied with this ticket. They're
31:52
actually closed with an AI agent. No human in the loop.
is clear outcome, right? So they charge for that.
Or there are companies that actually have demonstrable savings like for instance a company that you know recoups chargebacks. They do a 25% of the recoup
32:07
money. So that actually is directly you know because they measure it they they understand it they take a portion of it right.
So if you're uh and it's a autonomous so if you're highly autonomous highly attri attri attributable in the top right quadrant you can be an outcome base. So I think
32:23
this is the key thing the the the thing is to really understand you know what is the right you know pricing model or archetype for you based on your product in terms of like how autonomous and attributive it is. Where I see founders making a mistake is
32:41
chasing, you know, shiny objects like they just heard from some, you know, networking event that they went to that outcome based is cool. Like I need to be in outcome based and actually talking about outcomebased pricing when the attribution of the product is incredibly unclear.
That's setting yourself up for
32:57
failure. So like understanding where you are in the quadrant is super important.
Then you can build pathways to also move around if you need to. But if you stop wasting time and trying to like just copycat and like see really what is the right situation for you.
>> It's it's also the the outcome based
33:15
pricing also creates an alignment internally between the product efficacy and and um and tools and also customer expectations. And so that alignment is just terrific because it rather than focusing on like okay how do we sell
33:31
more seats it's like okay does the product actually deliver but as you say I think it's more more challenging. Yeah, but that's a great point because for instance if you take these you know uh customer support ticket resolution like right I mean if I when I start if for instance only 20% of them got done
33:48
by AI without any human intervention then everyone in the company is now incentivized on how the hell do I make that you know 60 or 80% because that's when the product is actually delivering on its value. So you're completely tied in destiny in terms of like your vision everything else with the customer and
34:04
you're partaking on that. Yeah, >> that is where it becomes a very beautiful model where you switch to like you know charging for like work delivered as opposed to access to software.
you talk about wallet share and market share and I you can see that
34:19
outcome based pricing can be critical because or or capture a huge amount of value but at the same time um the the concern is that unless there's a real commitment which is like okay you're paying whatever a particular flat fee
34:35
people are less invested in the product they'll just use it episodically or um or um as an option against many other channels. How do do you see that as a in practice as a real challenge or do you
34:51
or or do you see strategies for companies to to kind of mitigate this sort of one of many one of many outcome based companies? >> No, that's that's an excellent point because there's also some characteristics around when does outcomebased model make sense of a
35:06
company and a market um and also you know when do the other ones make sense. So we actually talk a lot about this in scaling innovation but you talked about episodic for instance if my you know value delivered is episodic um you don't
35:21
want to be on an outcome based model because that almost looks like you know holding someone hostage like when when the value was delivered you're actually coming the you know bill collector is actually showing up think about this in the you know um previous vintage of lifelock right it's it's uh operating in
35:39
my background checking my credit, you know, like uh identity theft, everything else. And then you say, "Okay, I found identity theft breach.
I'm going to charge you." Uh it's like episodic, like it just happens once in a while, right? That actually that but at that time it's
35:54
insane value. You don't want to monetize on that because that actually looks like a really wrong thing to do, but you're actually paying for the, you know, peace of mind and it's like an insurance.
So in those kind of cases you want to actually have a you know either a fixed fee or a recurring revenue basis. So
36:10
like whenever it happens it happens. But of course you need to choose your level of pricing compensate with value.
But if it's like a more let's say you know u uh more frequent um you know deliverables outcome kind of makes sense like a ticket resolution. There is a ticket is
36:26
resolved you get monetized on it and then it adds up right. So I think there are some real characteristics on when each of these apply.
If you're an episodic one, um, probably not. >> Do you do you see any consumer based pricing model, consumer applications
36:41
which have outcome based pricing? You can imagine a fitness app which is like okay if you >> Yeah.
If you lose uh£10 or kind of like do you see anything happening there or or the customer is is perhaps not sophisticated or too much noise going
36:57
on? No, I mean we've actually seen these uh kind of models like that's more of a gamification for me.
I don't know if it's an outcome based. You could claim it's like driving outcomes like if you lose weight then we like you start with $100 a month for in I'm just making it
37:12
up and then if you lose weight then we give you like you know 20 bucks back or like if you study well in a course and you actually get a good grade. We've seen some of these things.
We get some credit back because then you can actually have tie-ins where people will submit their scores and everything else and you know that the product actually
37:27
improved their performance actually works well. It's a it's more of a gamification.
I think an outcome based model in in the consumer side probably has not taken off as much as in the you know B2B side. >> Yeah, >> probably more to come.
37:42
One of the key characteristics for outcome based pricing apart from autonomy is being able to prove I mean there needs to be a key metric that you impact >> and and the company needs to have some sense of like what's their current cost without AI or without your product.
37:59
>> Um what what percentage of do they like do these AI companies are charging? Like how much are they capturing?
Because obviously if you you charge the same as their current cost, they're going to say no. But I wonder what's the discount.
>> Yeah. >> That is common
38:14
>> for for sure. I mean like like you said first of all attribution is super key and the sack that you can attribute it and it's also closed loop in the sense that at the end of the day your customer independently can say I got this incremental you know revenue or cost savings or opportunity cost because of
38:32
the company. Um and then you know the question then really is what is a if you can show that attribution and you unlock value what can you charge right in the in the historical like I mean in the previous vintage we used to say if you're 1 is to 10x it's good pricing in
38:47
SAS um in AI companies we're actually seeing that you could even capture 25 to 50% of that attributable revenue because it's true incremental and autonomous >> right so 25 to 50% is the benchmark that we have for that we seeing actually some
39:04
companies actually do it. >> And do you think this is going to sustain or are there any because another thing that that that makes me think like this outcome based pricing is that it's so simple and clear that is also very easy to potentially switch providers, >> right?
Like if someone comes and it's
39:20
able to resolve that ticket as you know the the current vendor and it's not charging 50% or 25% but is willing to go to 10 >> like the switching costs. Um yeah, makes me think >> I think switching cost is uh um probably
39:36
can be built internally with the product and and uh as opposed to like having your pricing model be the switching cost. In fact, I would argue that if your pricing is complex, that is when people actually want to leave you to like someone else.
If your pricing is
39:51
simple and they understand why they're paying and is based on outcome, it's actually hard to like for someone to leave because you're putting skin in the game. Unless someone is going to charge lower for outcome, but then that's a different question because then your product needs to have some switching costs in the sense that you know it's very well integrated with things.
It's
40:08
hard to rip and replace. It'll take some another AI agent to like do the training all over again and you put some guard rails and you've built some new, you know, let's say enterprise RL models that actually can solve things.
Then of course it's not easy to rip and replace
40:23
because then there are models that you're building. There's training data.
people get used to it, they understand the user interface, they understand how the agents work, then it's not that easy. The I I've seen actually if a pricing is complex, that's when people invite other people in the room, right?
40:39
Because then it's like, okay, I want, you know, simplify my pricing. But if it's a outcome base itself is a moat is what I'm trying to say.
>> Yeah. Everything's aligned and you certainly have also just this easy to communicate and easy to track and measure.
And h how do you see folks do
40:57
you see folks moving around the map or revisiting pricing because it's there's you know in this you know you you we see a number of AI startups which are entering the market with an outcomebased pricing and then building these compound startups where they're like we're
41:13
tacking on a bunch of other value after this very attractive initial wedge. How how do you see how should founders think about that evolution and revisiting pricing?
Yeah, I think like I said it is uh when we when you start based on your
41:28
you know product level of autonomy and attribution you need to pick the right quadrant but you also need to build pathways to like move around the quadrants if that is something that you can actually aspire to do and and this has actually happened in many industries
41:44
already. Maybe we can take an example to unpack that.
If you take we talked about coding um you know agents and coding assistants. So if you think about the classic you know GitHub copilot for instance they started in the bottom left quadrant you know attribution was low um
42:02
autonomy was low so they were a per seat model back in the day Gup was per se per user right I mean we all know that when you take the cursors of this world they actually move to the bottom right which is you know attribution higher you're saving a lot of uh you know time for the
42:18
developer you're creating code that can be almost reused as core attribution but still on auto you know co-pilot mode so they are in a hybrid of seats and usage model but you already hear you know companies talking about I'm building an
42:35
entire autonomous u you know coding platform like I'm going to hire you a QA person who can actually do QA and you don't need Jim or Jen doing QA you can have my AI do it and uh I can actually show you how many bugs we fix everything else autonomy and attribution
42:51
is increasing in that space that you could actually say okay then I might want to actually charge based on outcome how many bugs did you resolve um and is that how's that compared to like a human and should I charge for that agent differently then you get into more interesting conversations but the key is to understand that where you are and
43:09
what do you need to do like how can you build more things in your product that will demonstrate more attribution over a period of time and how can you build stuff in such a way that your product can get more autonomous over a period of time. And for attribution, the some
43:25
simple hacks are things like okay, you actually want to have some kind of, you know, dashboard where I log in as a buyer and I can actually see some charts saying how is this AI actually increased my topline, my cost savings, my opportunity cost and you know sort of
43:42
make that the front page. I mean this hey we we have actually saved these things or it's a report that's commonly available.
you're training people that attribution exists and how do you build pathways towards that before unlocking outcome based pricing etc. So I think you can move around but you need to plan
43:58
for it. the the the pace of AI is getting so much better so quickly.
Um and you know we're we're you know super intelligence uh is a you know a tough definition but um as you kind of roll
44:13
this forward a couple of years do you see outcomebased pricing being you mentioned 25% but do you see it perhaps kind of more prevalent than that over time as as sort of artificial super intelligence becomes kind of more
44:30
pervasive because I think it we have to be building for this world because it's getting better at such an exponential rate. >> Yeah.
I think um the in the next three years also based on like studies that we have seen we have done ourselves talks etc where the buyers are actually
44:46
getting more comfortable right if you look at CIOS and organizations even the ones who used to say I want predictable budgets they're like you know what I'm actually willing to like see if outcome would work because our incentives are aligned right so that's also how we get to that 25 to 30% in the
45:02
next 3 years if I take a more forward look of let's say you know 5 10 Yes, you know, super intelligence, AGI, we can debate what our worlds will look like, but I actually think intuitively outcome based pricing model should make
45:17
a lot of sense there, right? Because uh I could even envision a world where AIs talk to AIs and they reconcile how much to pay each other and they basically, you know, it's based on the outcome and there's actually no bias like humans, right?
I mean, it can actually do that and it has to be on outcome. If you if
45:33
you take a world with less bias, outcome is the right model. >> Yeah.
Yeah. >> There's no debates.
>> Yeah. There's no, you know, necess it's like what is the value you're delivering to me and what is my willingness to pay and >> and it's a pure like individual economic
45:49
decision which lends itself to abs you know some sort of quas auction type situation in a in a um in a real-time basis. >> Yeah.
Exactly. My AI agent hired a you know recruiter agent because those
46:05
models are actually better. I'm a general purpose AI and I hire them and they do the work and I pay them based on the outcome.
>> Yeah. >> And and it all happens in the background, right?
>> No. Yeah.
It's a so yeah it's a bit interesting to see how the world will
46:21
evolve but uh yeah it's anyone's guess. >> Yeah.
But then it's in that environment and I think the founders need to think about what is the true defensibility beyond the sort of the AI product that they're building and which is a lot of data network effects workflow etc.
46:40
So, so if you're um if you're a startup competing against an incumbent uh and you talk, you know, when we spent time together dozen years ago, there's a lot of thinking about bundling and kind of and and pricing and
46:56
different kind of components. you can see an environment where you have a a sort of a an incumbent which arguably has a sort of bloated product set adding an AI component and they're looking to kind of okay this sort of like machine of like okay we need to kind of ratchet
47:13
up the kind of ACV um and then you have a startup which is saying okay I'm going to like monetize on an outcome based on my kind of high value AI product and then give everything else away for free um like
47:29
what are what are some of the merits of kind of that approach? Um and any tactics for found have you seen that working?
Have you seen and have you seen tactics for founders to execute on? >> No, I mean like look when when you have a incumbent in uh in town there are and
47:45
you want to compete as a startup there are probably you know few ways that you can actually do it. Um you can say I would try to be a lowcost provider compared to the incumbent and that's the reason to switch.
But guess what? The incumbent probably has a lot more capital and they can rob the price faster than you can drop, right?
In some
48:01
way. So that's a losing proposition.
It's always the other person who started the price war, right? I mean, so it's that's one way you could think about it.
But the more smarter way actually to think about it is to say, are there some strategic things that I can do in terms of like how I charge my pricing model?
48:18
Can I actually make it different? Are there some core pain points with the current incumbents that I'm actually solving and how can I leverage that?
Right? Even back in the day when you think about Netflix right Blockbuster used to have all these movies and you know you price based on movies late fees everything else but a subscription price
48:35
on a Netflix to keep your DVD however long you wanted was a different pricing model that actually worked I mean and the rest is history so this has been done in various vintages like where a pricing model conversation itself is the reason for disrupting an existing
48:51
incumbent. So if a incumbent because think about it a a really big incumbent with multi-product many different teams you know just building AI into their existing ar you know tech architecture which does not have AI what are the chances they will move into an outcome
49:07
based world zero they're going to have 20 debates consensus and they will shut it down and say no let's just preserve our margins for a current business and they won't do it but if you're if you're coming new into the market you have nothing to lose if you say look I win when you win and my model is outcome
49:22
based great maybe that's how you start stealing accounts >> right so I think thinking about those things would be key and I've seen it work all not just now we we're not just seeing it now we have actually seen it historically >> and we're seeing this this trend right like with AI at the end delivering work
49:40
right it's reducing the the need for so many people in a company and and like a seatbased pricing thrives when a company adds more headcount right so >> yeah it's like catching a falling knife if you're on seatbased pricing right Exactly. Yeah.
You Yeah. It's kind of like the the classic innovators dilemma.
49:56
>> Yeah. So, so in the book you talk about these um these founder archetypes and perhaps failure modes and kind of things that folks don't do so well.
Can you talk through a little bit of those uh the failure modes and archetypes? >> Sure.
I think it ties back to the same
50:14
market share and wallet share, right? I mean, so um I love 2x two.
So I got to use one more. Oh, we love 2x2s and effects.
They're like frameworks. >> Yeah, exactly.
>> So, so when you think about uh you know market share on the yaxis and wallet
50:29
share on the x-axis, right? Uh and let's take the top left quadrant first.
High focus on market share as in a leadership archetype or a person who has high focus on market share but low focus on wallet share. You know, we in the book we call
50:46
them the disruptors, right? These are people who say I'll grow at all costs and I'll figure it out in terms of monetization.
Right? If you take the bottom right uh uh you know quadrant where wallet share is the big focus but
51:02
market share is not that big focus for the CEO or the leadership. We call them the money makers.
These people actually think about from day one how to build a great commercial business but uh you know not focusing more on the market share. And then you have this bottom left where you're neither focusing on
51:18
market share nor wallet share. We call them the community builders, right?
They're focusing on a core set of customers and they want to do right by them and just keep working with them. And then the you know if you take each of these archetypes, I'm sure all of us have seen many of these, right?
Let's take the disruptor one focusing more on
51:35
market share um but not paying attention to wallet share. Not equal efforts, equal attention, even not even paying equal attention to wallet share.
uh and you're basically selling a $180. Literally, that's what's happening.
So, you fall into two traps. Um you know,
51:50
you're probably landing without expanding in the sense that you gave the farm away in your entry product and then you're chasing your tails to like build something and hoping to monetize that often does not um you know sort of uh translate. Um and that happens with
52:06
disruptors all day long. And the other one is making the mistake of thinking that market share one is market share earned.
What that means is you're so focused on acquisition that you're keep thinking about getting new customers. You're not focusing on keeping those customers, retaining them, adding more
52:22
products, value to them and retention is not the focus. Acquisition is the focus.
So you want market share but it's not durable. Right?
That happens with the disruptors. If you take the money makers, you know, focuses more on making, you know, money and or thinking
52:37
about that before the uh market share, they fall into a couple of uh traps. One is the price premium trap, which is hey uh you know, I'm I want to charge a premium because I learned that premium price means that it's value and you know, I'm the next Eve and uh you know,
52:54
$200 wine is like value and whatever. I mean they've learned stuff that but the par I mean while there are obvious connotations that if you know price is a signal of value the price premium paradox is when you charge it so high that you become irrelevant to like your
53:10
audience right so that actually happens all the time like when you start charging for a you know juice machine at like whatever 700 bucks when you can probably squeeze the packets and you have the same result you're on a price premium paradox right I mean so that's
53:27
uh different or you also fall into a um you know nickel and dimming kind of trap which is you're so focused on the wallet share that you have these your pricing is incredibly complex money maybe even different you know elements of the fee structure things like that because
53:42
you're only think about that not the market share if you're the community builder this is an interesting one because there's also some literature around let's just focus on a few customers build the product and scale it CEOs who have actually done that have still been very thoughtful about wallet
53:57
share and market share and paid attention even though they started community builders. But the community builders who don't pay attention to these they fall into traps like you know giving away too much uh for too less because they're so you know want to
54:13
please their customers in that community. They keep giving.
They keep giving. And they train their best customers to expect insane value for less.
And they can never undo it because once those customers become reference customers, they'll be like, "Yeah, I got that for like $10. Are you kidding me?" Like, it just doesn't make sense because
54:30
you just train someone to like get insane value low price, they're not even going to be good reference customers because they're they're going to say what price they actually got it at and that's going to be the reference point for everything that you actually do. That's a trap that you fall in.
Or the other one is uh you know you fall into
54:45
this trap of uh uh you know you're solving for uh you know current uh let's say base but you're missing the frontier which means you're so focused on the current customers that you're not even thinking are they adjacent markets or others who look different to my loyal
55:02
base that I should be building towards. So you miss adjacent markets you know opportunities to acquire new types of customer segments.
So the best quadrant to be in is the top right which is the profitable growth architect is what I call it where you know you're focusing
55:17
both on market share and wallet share like I said not equal efforts at all point but equal attention so a profitable growth architect is actually a disruptor a community builder and a money maker all at the same time how do you do that and that's really the thesis of the book as in you know we talk about
55:33
nine strategies to build towards profitable growth and you know demonstrate that you could become a profitable growth architect if you follow those strategies. Four of them for the you know 0ero to one startup phase and five of them for one to five when you're scaling up kind of thing.
55:49
That's the whole thesis of the book. >> We actually have this thing called axioms.
I want to unpack that too if you guys are open for >> yeah going to be our next question. >> Oh great I mean so the uh the the axiom related to this thought is the what I call the 2080 axiom.
This is my favorite one. I've uh you know seen this over and
56:07
over again with tech companies. I don't know if you'll agree with it, but let's uh let's let's you'll agree with it, right?
20% of what you build in tech drives 80% of the willingness to pay. This I've seen it over and over again, right?
I mean any product that you say
56:22
okay 20 if you ask people recall on like why do you buy this product? What are you paying?
It's always like 20% of like what someone has built. 20% of what you build drives 80% of willingness to pay.
The biggest irony in tech is that this 20% is the easiest thing to build.
56:38
So what happens if you're in that disruptor mindset you will build that 20%. You'll say okay you know that and it's the fastest thing to build you'll say okay let's build it put it out in the market let's call it MVP give it away for free.
So basically what have
56:53
you done you've basically given away the farm and now you're going to build 80% of ridiculously hard stuff that's only driving 20% of willingness to pay. Right?
So you're basically disrupted but you have no pathway to like get to
57:09
profitable growth or monetization. You just gave away and you're hoping that something would happen.
The right person would say okay this is the 20% you know that's driving willingness to pay. How do I probably get it in such a way that maybe is there some usage things I want to give it away for free but after a certain point you have to monetize on
57:25
that. So can I actually compensate on a land and expand and you'll have that equal attention kick in and then you'll actually put it in such a way that you will you know cross both market share and wallet share but if you didn't you'll just go on leaning on one side right I mean so that we call it the uh
57:41
the 2080 axiom which is is is so true every time people will give it away and and then just chasing their tails >> yeah and it's surprising how founders like have such a hard time some like being afraid to charge a out for their
57:56
>> I mean in this case they don't even charge they just give it I think we should stop calling things minimum viable product we should call it most valuable product this whole MVP definition needs to change I think it's uh it's I also heard another definition most lovable product that's a good one
58:11
actually I think that's a better definition but this MVP which is the 20% that you can build is the core of the willingness to pay if you gave that free tough luck >> what are other axioms that are her favorite. >> Yeah, I think there is um the axiom that
58:29
I talk about uh you know on the price increase um axiom. So usually I mean the price increase axiom is that to to do a price increase often you know the uh reluctance to do it is internal and emotional.
It's not external and
58:45
logical. And we unpack that axiom in the sense that and I think Warren Buffett said this well.
They said if if you need to have uh you know for doing a 10% price increase in a company if you need to have a prayer session you have a terrible business right I mean so how do you do a price increase if it's a 10%
59:01
and we talk about that like you know how to actually achieve that but the uh axiom there is that every single time we found a price increase being more internal and emotional as opposed to external logical there's always a way to do it because you know the price of like
59:18
everything that you consume goes year-over-year your software or AI cannot be on the same price for the last 5 years. There's something off.
I mean, it's internal emotional. It's not external logical.
So, that's one that I uh >> that's why we that's why we love network effects, right? Because it's like if you
59:35
as you as you scale the business without necessarily providing more features from a software perspective, the value of the product increases over time. And so if you and you know you and then actually sort of uh pricing and increasing
59:50
pricing over time is sort of like a natural part of the service you provide or or increasing value within the the product you're providing. >> Oh totally.
And every person who brings in another person makes it valuable for the whole network. Right.
I love network businesses too. So
00:06
>> another action that I like it says something like attract customers who won't leave. >> Oh that's a good one.
Yeah. importance of choosing your customers.
Um I mean always but also especially early on. Yeah, that that goes to the I mean promotion example that I was giving,
00:21
right? I mean if you acquired customers to three promotions who are going to leave, that's not robust revenue, right?
I mean that's just revenue. It's not durable.
Um the best way to stop churn is to acquire customers who won't leave. That is the axiom, right?
Because most
00:37
people try to stop churn at the time that someone says I'm going. It's too late.
You can prolong it by a few more months but that person is going to leave right um and it's reactive. The proactive way of understanding churn is say look at my customer base and say who
00:54
are the types of customers who tend to stay longer? Who are the ones who actually tend to you know engage with me more?
The usage buying more products over a period of time. Who are they?
What do they you know how can I find more of them? Can I transfer all my acquisition dollars to find more of them?
Yeah. Then you're stopping churn
01:11
because you acquired the right set of customers. >> Yeah.
It's interesting how sometimes like a retention problem is really an acquisition problem. >> There you go.
That's it is it is totally right. Nice way to phrase it.
>> And last question on this one. Um how would you relate this to like the what
01:26
we were discussing before about PC's? Like it's very critical, right?
>> For sure. All of these tie back because if you choose customers I mean first of all you know you need to separate the you know tire kickers from the people who really want to use your product.
For
01:43
that you need to charge for a P. That itself is a lead qualification mechanism.
Like many founders ask, should I charge for a PC? I'm like hell yes because otherwise you're going to get some curious buyer who will take you down a three to six months pathway might never buy.
They're just curious to see the how do you know they have budget or
01:59
they want to do something right. So charging for a PC is at least identifying some customers who want to partake in that because they have to put some effort for it.
Um and also like how do you uh you know frame it as a business case so that your monetization is part of the value delivery that
02:15
becomes key so that you're not giving the farm away. So all of these principles actually apply there.
So what we talk >> so if you're so let's just say you're an early stage founder you raise your preed or seed seed round led by NFX and 49
02:31
palms >> that's great and you're building an AI product like what are like what are perhaps three pricing tips that they should do in the first 90 days? Uh so the first thing that I would probably uh
02:46
you know look at is uh you know how do they charge or how do they plan to monetize because that's a more strategic and fundamental question as opposed to how much how much can wait right so that's a 90-day question like should I >> tactics of spec specific
03:02
>> specifics around how they will charge whether that's outcome whether that's >> and that's unpacking their entire product seeing what value they actually offer to their customers how do the customers realize value. Do you have some value elements?
For instance, you know, can you charge based on a
03:17
resolution, tickets, whatever? Or is it like consumption on tokens?
Is it like usage based? Is it hybrid?
What? All of that stuff can be um you know, ironed out pretty fast based on the archetype and everything else that we talk about.
So that's the first thing that I would do. The second thing that I would do in
03:33
the first 90 days is to actively start uh framing PC conversations as business case conversations. So that to your point Anna before that I start selecting customers who actually want to invest time to jointly investigate with these
03:51
founders that there is value in this AI product as opposed to some just technical diligence. So I would probably you know coach them on on on that right and uh that would be the uh second thing and the third thing >> and by business case you really it's really deeply understanding the um the
04:09
needs of the customer in terms of their expectations their cost structure business model etc. >> Exactly.
And the third one is also like preparing the founders on how how to have these conversations with the the customer. Right.
I mean there's some
04:25
because what I often find is founders will show up with a product and demonstrate what they can actually do from a technical standpoint but like are they actually having the right value messages? Are they actually talking through that?
So like you know coaching founders on how to articulate value,
04:42
create needs not just discover them. Um and how do you value sell and negotiate becomes key.
So actually like for instance the options that we talk about right I mean things of that nature that you can actually start being more strategic in terms of how you negotiate. >> Yeah
04:57
>> and I think that's the other training that we can actually do. I would love to have a situation of a joint captain with you.
>> I'm sure I'm sure I'm sure >> great that would be great. >> So anything else that we missed as as founders think about pricing in this in
05:12
this new world? One thing that probably, you know, I I keep getting asked and we sort of unpacked that, but if there's interest, we can unpack it was all these AI companies are getting to like, you know, revenue pretty fast.
Is that good?
05:30
Is that Have they cracked the pricing code? Is this durable?
I think that's an interesting topic. We kind of talked about the negative margin or neutral margin based on the Techrunch article.
I mean so that's one aspect of that but there are several aspects of it which is very interesting I think which even investors need to know right I mean
05:46
there is there's a there's a there's also like u you know where am I getting that uh let's say revenue from um is it contracted revenue or is it p revenue so there's a lot of uh you know things that
06:02
you actually see okay I hit a 10 million and you start unpacking it it's probably more P revenue than contract I got contracts from like Tesla, Apple, Google, and other companies. Like, okay, it's a 90-day PC.
That's not a contract, right? So, I think so, let's be all
06:17
careful about like what these reported revenues mean. That's one aspect.
And then there's also, you know, uh the other aspect of like is this revenue durable? That's also important question because there's a lot of curiosity on the buyer side to actually, you know,
06:33
look at these AI products. Is it working for me or not?
So there's a lot of curious buying which means are they going to be there after 3 to 6 months? So you cannot take something and extrapolate it to 12 months when you've only been there for like 3 months.
You don't even know how churn is actually going to affect you. Is that durable
06:48
revenue or not? Key question for us to think about, right?
I mean is this do they have foundational modes? Is it is it truly delivering value that people will actually have an ongoing monetization conversation?
Yeah, it's you see it all the time where you got the board of directors pushing down into their kind of CEOs and and VPs saying
07:06
what's our AI strategy and so they go out and sign a bunch of PCs or experimental budgets to try sort of things to tick the box and then they and then they move on. Is there any and just from a founder perspective is that really just looking at you know does the
07:21
engagement and retention increase over time? Is it is it as as simple as like watching core usage and and core monetization within on a per customer basis on on specific cohorts?
>> Yeah, I would uh nuance that to say on a
07:38
segment basis like what are the types of segments of customers I'm attracting? What is their usage intensity?
>> You know, are they actually who are the ones that are using are they going to tend to stay? So like doing cohort analysis.
Exactly. That's the that's the key because if you just look at it on on average averages will always lie right
07:55
and there's also all these pressures on like what is the ARR I think we also need to like in especially in AI think about is ARR the only right metric no we there are probably other things that we also need to look at for the health of the business and even AR how is it even reported I mean um some of the things
08:11
that we saw I don't know what you see like and we we we met a founder was actually we talked about seasonal products for instance right seasonal products a seasonal product. Um I mean it didn't come up in the conversation because it was seasonal.
We understood that was seasonal after talking. But if
08:26
you look at the financials in terms of how the ARR is done, it's like take the maximum in a 5 month period and multiply by 12. I'm like no that was the peak month.
What happens the other month? You can't just do that to extrapolate your AR.
So like how is the AR even computed?
08:41
Um is is a question mark, right? I mean like uh if you don't account for like how do you do it?
So I think being thoughtful about this um as a community of like founders, investors and others like what KPIs are we looking at usage retention you know I think
08:57
>> and the the seasonal one is an interesting one because you could look at let's just take auditing or taxes like actually you know to many organizations like I don't want to like staff up for a 3-month period and then staff down again. I like if there's an AI that can do that for me then it's
09:14
terrific. And so actually so your kind of your your kind of fixed labor becomes variable and so and so you might look at seasonality as a negative but I think we see a lot of companies doing very well because they're just purely seasonal because they don't need to go through
09:29
the headache of hiring and firing. >> Yeah.
This one was like uh uh usage exists in other months but in certain months the usage peaks and we leave it at that which is a bit different case than what you're saying but yeah it could be negative or positive >> and then thinking through the the ICPS
09:46
we we see there are there are number of um small companies intrigued by AI but they don't necessarily have the um kind of uh economic sophistication to think through okay if I substitute this action
10:03
with this piece of software, then I'm able to see an ROI where you you see a lot of the kind of mid-market companies that are perhaps more aggressive or professionally run that actually see a lot of adoption for these type of deep these types of products. at the same
10:19
time like it it's been I mean it used to be that when in B2B in particular like you started selling to mid-market more and like enterprise would come later and now we're seeing all these founders being able to close deals very fast with with enterprise um but but to your point
10:34
I completely agree that it's a little given like how much curiosity it is and it's also >> kind of our jobs to you know learn >> to assess also like the quality of that revenue and also coach founders as um in this process.
10:50
>> That's that's the right way. >> Yeah.
Because sometimes, you know, we don't have time to wait for a renewal, right? Like to >> Yeah, >> for sure.
For sure. But I think that's also where I mean, especially in the businesses that you're probably investing in that network effects itself
11:05
become a mode and is that strong enough is something I'm sure is part of your you know thesis and is it durable and is it quality revenue? I think those are the diligence that needs to be done as investors but also as founders being thoughtful about is my own revenue you know durable or am I just reporting
11:21
something that you do you actually believe it ask yourself that question or in the mirror if you can sleep well okay if you can't what do you need to be answering to actually see if it's durable or not and then work towards it right >> wonderful well thanks so much for
11:38
joining great conversation great insights >> and excited to do some co-investing together. >> That would be awesome.
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