Monetizing Expert: Your Pricing Is Killing Your Startup

20% of what people build drives 80% of willingness to pay. Price is a signal of value. I mean, a $200 wine, most people

value. I mean, a $200 wine, most people in a blind test would say it's actually great, even though it was a $2 wine. And

actually, you worked on the product for 2 years without no idea of some whether someone would actually pay for this. I

ended up working with over 300 companies, more than 30 plus unicorns.

Price before product, period.

>> Most founders think pricing is an afterthought. That mistake has killed

afterthought. That mistake has killed billiondollar companies. Today we're

billiondollar companies. Today we're sitting down with the man who's advised 30 plus unicorns, helped build entire pricing playbooks inside Silicon Valley, and has seen more startups fail from pricing than product. This is the pricing conversation founders should

have had on day one. Well, everyone,

very excited to have uh Mavan here for the Library of Minds podcast. He is a pricing guru and an expert and investor in Deli, author in two books. One of

them here, he just released Scaling Innovation. And I'm super excited to

Innovation. And I'm super excited to have you here to talk about pricing.

Super excited to be here.

>> So, how does one get into the expertise of uh software and tech pricing?

>> Maybe I can talk about my journey, how I got into it.

>> Yeah.

>> Um, so when I was graduating from Stanford, this was uh probably uh 17 17 years ago. And uh you know, in classic

years ago. And uh you know, in classic fashion, I wanted to uh you know, found a startup and we had a team and I was this guy who was in charge of uh the marketing plan and everything else. And

we went and pitched to a VC and I remember getting the question, how do you know you'll actually make money on this innovation and I pulled up my spreadsheet with all kinds of assumptions and I showed it to

him and he said, "You label them right.

Those are assumptions. How do you truly know?" I was I don't know. So I got into

know?" I was I don't know. So I got into pricing by just guessing and hoping for the best. You know, build some products,

the best. You know, build some products, slap on a price, and hope to monetize.

That's probably how most founders approach pricing. That same week I got a

approach pricing. That same week I got a call from uh uh in a company called Simon Kutcher which is regarded as the largest management consulting company focused on monetization. And I was like

that's interesting. That's exactly what

that's interesting. That's exactly what I wanted to learn. So I thought I will go there and you know learn the arts and tricks and go and you know start a company. One thing led to another. It

company. One thing led to another. It

was such a great ride. I stayed there for over 15 years. I ended up working with over 300 companies, more than 30 plus unicons and uh Josh who's my co-GP

now at 49 palms and myself we started the tech practice and scaled it. So it

was a great ride. So that's uh you know my journey into pricing was by accident but what I really put out in these books is what is the science behind monetization because most founders

approach it as an art >> and it has to be a good combination of art and science. So my whole motivation for writing the book was to give back a bit of what I knew so that founders does

don't have to like start uh the journey that I did which is you know discover it by chance.

>> Yeah. And I I started uh reading a bit of your first book as well where you talk about how some products fail not because of engineering but because of pricing. And I'm curious if you have an

pricing. And I'm curious if you have an example of maybe two companies that had near identical products but it was really the pricing that completely changed the trajectory of one over the other.

>> Yeah, I can think of several examples.

Um because when you talk about pricing it has different layers. Is it a pricing model? Is it a price level? Um you know

model? Is it a price level? Um you know what does it actually mean? So maybe

take a couple of examples. The classic

example is uh you know Blockbuster versus Netflix. Same product. It was a

versus Netflix. Same product. It was a DVD that you can put on into your you know DVD players back in the day and actually watch a movie. Blockbuster used

to charge based on you know different titles late fees you need to get to the store and it was a per movie basis very painful for those of you who have done it in the past. And then Netflix came up

with a new pricing model that was revolutionary saying, you know, just subscribe and it's a flat fee per month and you can get to keep the DVDs however long you want, no late fees, etc. And um which is a different pricing model. Rest

is history. Blockbuster did not adopt to that model and you know Netflix uh really crushed it with a how to charge question which is often way more important than how much to charge.

Another example that comes to mind is uh Zing versus LinkedIn. Both of them actually started at the same time identical products in terms of being able to like network and you know form a

professional network or a personal network kind of products but Zinc started with uh rushed in with actually subscription plans and uh put a lot of features behind the payw wall. LinkedIn

actually purposefully kept the product to be you know free and thoughtful and and the story of LinkedIn is actually well captured in monetizing innovation where I wrote a chapter on LinkedIn's journey but even from the very early

days when we had worked with them they were very thoughtful about you know how to land and expand what is the overall strategy you know what is that critical mass of like getting consumer adoption before they actually start switching

monetization and their entire business model was different because they started monetizing on the talent side, then they started monetizing on the sales side, then they started monetizing on consumer

side with like premium profiles etc. But all of that was thought through even the pre in in the preipo days when we worked with them. Uh which was a kind of

with them. Uh which was a kind of identical product but you know LinkedIn crushed it with their pricing and pricing models and zing.

>> Want to go deeper? Talk to Mavan's digital mind on deli.ai link in the description. That's a good segue to

description. That's a good segue to another question I have. you know,

LinkedIn, like you said, I I met the CTO of LinkedIn. He talks about how they

of LinkedIn. He talks about how they were optimizing for profiles and like revenue really wasn't a target early on.

And so, when does it make sense to delay pricing and monetization um based on, you know, you're hoping to get network effects, you're hoping to get data that you can monetize later versus trying to generate revenue right now because

LinkedIn could have done that. They

could have made revenue at Target in the early days, but they didn't.

>> For sure. And even back in the day, we actually tested that there was a willingness to pay on the consumer side.

But uh consciously that was a delayed decision. We knew it was there. So we

decision. We knew it was there. So we

knew they were building the right you know feature set for instance even things like inmail that was a classic debate. Should it be free and give it to

debate. Should it be free and give it to everyone to connect with everyone on LinkedIn or should it be a premium feature and uh there were also uh you know sort of um considerations like an

inmail is actually a premium thing because you don't want everyone in the network to call everyone. on it is a premium thing to actually connect but there are certain things that need to be free. So it was very thought through but

free. So it was very thought through but already tested. So in the book scaling

already tested. So in the book scaling innovation I talk about how to architect towards profitable growth and that is the key not profits not growth but profitable growth. What does that mean?

profitable growth. What does that mean?

That actually means being able to dominate both market share and wallet share. And the mistake that founders

share. And the mistake that founders often make is, you know, they focus on either one at the sole exclusion of the other and then get it all wrong. So if

you focused on market share from the get-go and say that you're disrupting the market, but you're not thoughtful about how you would monetize or get the wallet share, most likely you have given uh you know the farm away in your

entry-level products, trained your customers to expect, you know, more for less and then you would struggle to actually monetize, right? U if you focus too much on the wallet share, you're probably missing out, you know, markets

that you can actually go capture. So the

key here is having equal attention to both market share and wallet share at all points in time in the company journey.

>> But that does not mean equal effort because at different points in your journey, you might actually want to push one lever versus the other. So naturally

if you have things like you know network effects or you're building you know core data that can be monetized you need to uh delay monetization but be thoughtful about how you would do it and even test

that early that that's actually that delayed decision will pay off at the end not hope for it if you just build on hope that's not a strategy. Sure. And

how do you think about testing monetization strategies and new categories where maybe not everyone really knows what the pricing model will be both consumers and businesses.

>> Sure. So that's kind of why we wrote monetizing innovation because you know I used to work with a lot of um uh products which were you know new category products and I used to get a

call saying hey we need help with monetization and pricing I'm like how long do I have is like I needed it yesterday like how long did you take to build a product was like 2 years I'm like you worked on the product for 2

years without no idea of some whether someone would actually pay for this that seems so wasted. So the idea here is that in monetizing innovation what we

talk about is to do uh and do a product market you know price test which is important because many founders when you talk about product market fit they would say yeah we tested the product for

making sure there's a fit in the market and we're developing the right product.

I mean someone comes and asks me do you like this sparkling water? I like it. Do

you like it at $10? The whole

conversation is different. So if you don't put pricing as part of your product market test, you're often hearing what you want to hear. So even

in new categories what we talk about is let's say 6 months before you launch the product you know put wireframes blueprints you know just the same kind of product or even a prototype in front

of people let them struggle with it and have that same sales and marketing conversation that you would have um that you'd have after launching the product but try to do it before

>> and ask the simple questions around would you pay for it and if someone says no the most important question to ask is why and then you start hearing all of these jobs to be done unmet needs that

you can actually productize and that's the key right so the idea is to understand that broad brush strokes is there a range of willingness to pay you can get precise and optimize as you actually build out the product often

what happens is if you just build a product without even knowing whether there's a willingness to pay you get into all kinds of issues that you just build a product slap down a price and you hope to monetize right so testing

for pricing is highly possible in early stages. And maybe the other way to think

stages. And maybe the other way to think about this is as an entrepreneur, a founder, you don't have a choice whether you'll have a pricing conversation with your customer. You're going to have it

your customer. You're going to have it one way or the other. Either you're

going to build a product slap on a price and have that conversation or do what we kind of practice, which is have that conversation early and test and learn.

And if someone actually says no in that same after you pitch the value, after you have the same sales and marketing conversation, someone says no, chances are 5 months after you build the product, they're going to say no again.

At the end of the day, you're selling it to the same buyers. You're testing and learning. And there are various ways to

learning. And there are various ways to understand what is the willingness to pay that actually makes sense based on let's say economic value that's unlocked for the buyers. And how do you actually

come up with the right price anchors even in new categories. So if there's one chapter in monetizing innovation that I'll encourage readers to read, it's chapter four. It's called how to have the willingness to pay

conversation. And we really demystify

conversation. And we really demystify that whole thing so that founders can go and put it in action. I mean Rahul Wara for instance you know read the book and set a pricing for superhuman which was an it was an established category but

the alternative was free Gmail how do you price superhum so he followed the you know principles in the book and even talked about in a 16c podcast that's how

I got to know him is there a strategy in free and then making people pay versus paid and then trying to catch up with

everyone else who maybe had free >> yeah I think the Like there's always been this lure of free for distribution, right? I mean there's a quintessential

right? I mean there's a quintessential founders dream. I'll give it a fair free

founders dream. I'll give it a fair free and everyone will want my product, right? I mean, so I think everyone

right? I mean, so I think everyone thinks about that. The key is even when you think about free, there are various versions. Does it need to be a free

versions. Does it need to be a free trial? Is it a premium? Is it an always

trial? Is it a premium? Is it an always free product? So in the book scaling

free product? So in the book scaling innovation, we talk about what considerations will lead you to which pathways and should you even do free in the first place. And not every category needs to especially if there are you

know costs behind the scenes. If your

product is such that you can offer a free variety then you need to be thoughtful about landing and expanding.

Most companies only land they're not expanding. So you need to have a

expanding. So you need to have a pathway. Here's the thing that I've

pathway. Here's the thing that I've learned which is a counterintuitive truth across all the companies that I work with.

>> You know 20% of what people build drives 80% of willingness to pay. And that 20% ironically is the easiest thing to build. So what founders typically do is

build. So what founders typically do is build that 20%, put it on the market for free and then train the customers to expect that that's the free product and then they're chasing their tails to build 80% stuff that's only driving 20%

willingness to pay.

>> So you kind of already gave the firm away. But if you do these kind of price

away. But if you do these kind of price experiments and understand what drives willingness to pay, you can be thoughtful about the free experience in such a way that you might gau it based on either features or maybe even in

terms of certain usage amounts and then have a freeto- paid conversion that's actually thought through in a meaningful fashion. So if you can afford that in an

fashion. So if you can afford that in an AI business, that's a great business to have. But that's by itself not

have. But that's by itself not sufficient because you also need to build switching costs in the business to make sure that okay if someone else comes and offers a free product is are people just going to go to that or what

actually makes them sticky just giving something for free also signals different things in the sense that was it really valuable?

>> Sure psychological thing.

>> Oh totally. I mean sometimes the price is a signal of value. I mean a $200 wine most people in a blind test would say it's actually great even though it was a

$2 wine. Yeah, I remember uh a couple

$2 wine. Yeah, I remember uh a couple times there have been customers who have said you're massively underpricing like I would pay $100,000 for this and you

know every year AI gets cheaper and cheaper and so you know we could say yeah we'll charge $100,000 for this but at a certain point like the real value of these things are going to become

clear as more and more people can build them. When you think about pricing in

them. When you think about pricing in the age of AI, should you be pricing from a let's just change our pricing model every year to match the market or do kind of what we did which is start

with the end in mind and price for where the world is going to be 5 years from now. Definitely the latter which is keep

now. Definitely the latter which is keep the end in mind and you know price for what that is but I would also encourage people to adopt a valuebased pricing

mindset with AI because what is really changed with AI is two things increased autonomy and increased attribution which means you have more pricing power. So

avoiding the cost plus mindset. If

you're in a cost plus mindset naturally if the costs are going down you're going to keep changing price to reflect the cost. But if you're in a more value

cost. But if you're in a more value based mindset then you're basically when the costs go down that's when you'll actually get margin and you can actually then say okay it's not just revenue but

it's durable revenue I mean you can reach 100 million in ARR but if you're negative 15% margin you need a pathway to actually get profitable too right so you can't expect that the price will keep going down so I give you an example

like how you price for instance um you know finai prices based on number of tickets resolved based on an AI agent Right? If an AI agent resolves the

Right? If an AI agent resolves the ticket, that's when they charge. If a

human intervention is required, they don't charge. That's a value based

don't charge. That's a value based metric. If they just base it on like how

metric. If they just base it on like how much it costs them to resolve the ticket, that's a slippery slope. Yeah.

>> Right. So, being in that value based mindset is key.

>> You know, let's say you have product market fit and it works in a subset.

Should you spend more time dialing in that pricing model or when does it make sense to you know start investing in you know ads or uh you know B2B if you're starting as a consumer company or any

other company?

>> Yeah, I think I mean I often say that how you charge is way more important than how much you charge. Pricing model

is probably one of the most important decisions that companies need to grapple with from the early days and that keeps evolving as you go on, right? uh

especially for AI companies. I mean,

should you be on seedbased? Should you

have a hybrid? Should you be on usage?

Should you be on outcomes? Those are all kind of like day one questions because you're, you know, starting to train your customers on how to actually engage. And

we actually developed a pretty cool 2x2 framework in scaling innovation. We can

talk about that if you want as to when to pick which model. But

>> okay, cool. So when you think about AI companies specifically, what has happened? autonomy and attribution.

happened? autonomy and attribution.

>> So, think about a 2 by 2 where autonomy on the y-axis from low to high and attribution on the x-axis from low to high. Right? I love 2x2. So, I'm going

high. Right? I love 2x2. So, I'm going to persist with that. Um, if you take the bottom left quadrant, it is where autonomy is low and attribution is low.

When I mean autonomy, that means, you know, you're running it in a c-pilot model. You still need humans in the

model. You still need humans in the loop. Uh, the AI cannot be fully

loop. Uh, the AI cannot be fully autonomous. When I say low attribution,

autonomous. When I say low attribution, it means that your products kind of help with the co-pilot motion, but they don't necessarily translate into key business outcomes that your customers are

tracking. If you're in that quadrant,

tracking. If you're in that quadrant, most likely you have to be in a seatbased model because you're copilot and you can't attribute too much value.

So, for instance, you know, take Slack, which was a great company in the previous vintage. You can say my

previous vintage. You can say my productivity went up when I use Slack.

You cannot measure it. You cannot

monitor it. You cannot charge based on it. the attribution is weak um but it's

it. the attribution is weak um but it's a co-pilot and it's a you know um interesting product so it's a seedbased model if you go to the bottom right

where attribution is higher but autonomy is still lower you get into hybrid models so these are companies like you know clay or cursor they actually have a seedbased model but they also layer in

AI credits so each plan comes with a certain amount of AI credits that you can use if you use it then you need to buy packs of AI credits These are hybrid models because attribution is more clearer because you use cursor or clay

then you know that okay there's I could write my code much better with cursor for instance and there's clearly attributable and you save time for you know people and writing code etc but it's still in a you know co-pilot mode

so they're in the hybrid model. uh if

you take the top left quadrant where autonomy is um you know high but attribution is low most likely you're a back-end infrastructure play which is running on its own doesn't need humans

in the loop um but the attribution is still not fully uh aligned with business outcomes so like Twilio is a great example it's on a usage based model in that quadrant right the golden quadrant

to be in and this is not for everyone is if you're fully autonomous and also fully attributable right if you're in that quad quadrant then you can be on an outcome based pricing model because the

AI does things on its own and it's clearly valuable so then you can be on an outcome base so Finn AI is a great example they actually are in that quadrant where you know the agent runs itself resolves the tickets their

customers would say the ticket is resolved the humans didn't even come in the loop so they charge based on a ticket resolved by AI agent if if humans are required they don't charge for it or

companies like for instance charge flow which actually recover over chargebacks that's pure incremental revenue then you can say I'm taking a percentage of that chargeback for instance as your monetization model right the key is to

like pick the right archetype for your products based on where you are in the journey on autonomy and attribution and then build some pathways to actually get to more attribution and autonomy over a

period of time if you can get to that right and that's the key like even if you take coding platforms they start GitHub started in the bottom left quadrant on a per user Kurser and others have actually even

GitHub copilot now moved to like a hybrid model but then they're already talking about you know fully autonomous QA agents that you can hire and it's an outcome based kind of model that's going to the top right um so I think picking

the right pricing model from the get-go is key and then having a pathway to how it'll evolve if you're in a you know B2C situation that could take different forms like for instance what do I get

started with right now which side of the marketplace should I monetize is there a monetization on the other side of the marketplace place uh you know can I layer in additional revenue streams through like ads and others uh those all

become you know decisions as you go along but none of those will actually make sense to until you build a critical mass of like consumers etc right >> sure >> so that's uh that's also uh why a

pricing model conversation is from day one but it evolves as you you know build your company >> makes sense and what what is the biggest mistake you've seen a company that you've worked with make and tell tell us

the horror Sorry.

>> Uh probably delaying monetization for too long and then training the customers to expect more for less. I mean the classic example that comes to mind is uh

Evernote which probably did we almost had about 200 250 million users on the free product. Very compelling free

free product. Very compelling free product and there is no um you know there was no necessity for someone to even take the paid product because the free product was really uh very compelling. So they delayed the

compelling. So they delayed the monetization for a long time. Of course

they got the volume of users but they didn't monetize on that uh in time. Um

and then the question is you know companies like for instance notion probably started that in a different way where they were thoughtful about what is the free free trial experience what are the paid products what are subscription

products and also having products for businesses etc and being thoughtful about that. So I think um like Evernote

about that. So I think um like Evernote realized that and tried to pivot but it was a bit too late. Uh, a couple more questions then want to open up to the team. When you think about raising the

team. When you think about raising the ceiling and lowering the floor, you know, getting more people into your product versus uh generating more revenue of the people

that are already on the product. How do

you what's your decision tree uh for when it makes sense to do one or the other?

>> Yeah, you need to actually be thoughtful about both of them at the same time. I

don't think it is a priority on one or the other, right? If you just uh prioritize let's say getting new customers um then you're actually going to see that you did not monetize on your existing customers indirectly. What that

means is you did not train them on what value you're actually bringing to the table. So they're likely to churn. If

table. So they're likely to churn. If

you focus too much on your existing customers then you probably were not you know focusing on acquiring more customers in the first place. So it's

being thoughtful about both and uh having equal attention to both of those.

the efforts might be different because initially it might be more about acquisition because you don't have too many customers to also have ongoing conversations but at some point the effort on existing customers might be

needed more than acquisition but being paying equal attention is key >> yeah absolutely I mean and I've seen too many companies get it wrong where you know they either focus on one or the

other at the exclusion of the others or focus on neither that's actually the worst where you're neither focused on market share or wallet share but such just a core set of customers and you're

kind of a community builder. You missed

all the markets that you could have built for because you're obsessed with this customer base archetype in the book.

>> Yeah. Exactly. And and then you also trained your existing customers to expect more for less. So you don't even build a community in terms of you know wallet share. So

wallet share. So >> so I think being uh thoughtful about both from the get- go. That's my answer.

>> What's one question you wish founders asked you more?

I would definitely want uh you know founders to ask me when should I think about pricing and my answer is uh actually encapsulated very well by the

folks at uh first round capital they summarized the book monetizing innovation in four words price before product period which means you're actually testing for your product

whether people need it do they value it is there a willingness to pay as you build it so that you can you know build towards successful launches as opposed to slapping on a price and hoping to

monetize. So I would wish everyone would

monetize. So I would wish everyone would ask me when and the easy answer is should have already been thinking about right now. Yesterday exactly

right now. Yesterday exactly >> uh if you could have dinner with one person dead or alive who would it be?

>> I would say uh I mean this is probably such a cliche answer but I have to say it. I would say Steve Jobs. Um, in

it. I would say Steve Jobs. Um, in

chapter 2 in monetizing innovation, my original title was you're not Steve Jobs. And uh, the editor thought it was

Jobs. And uh, the editor thought it was too provocative, so we turn toned it down to like why good people get it wrong.

>> Oh, that went so good. It's exactly why you should do it.

>> I know. I mean, uh, but the the rational behind that is everyone talks about how Steve was a product genius, but what is probably often missed in literature is

how he was also a pricing genius. When

you talk about Apple, you know, they have actually mastered things like, you know, coming up with a higher price product, scheming the market, building for different segments, having behavioral psychology in that. Like I

remember going to like a, you know, iPhone store and iPhone X was available for $1,000. I mean, I I was like, what's

for $1,000. I mean, I I was like, what's a $1,000 phone going to look like? And I

go there and I know all the pricing tricks. I go there, I'm like, not going

tricks. I go there, I'm like, not going to buy it, but there's this $799 phone without the retina display that looks pretty good enough. So, I'm like, I fall for that because that's my segment. So,

if you look at what Apple did, they didn't price their products. They

productized to different price points.

And that's actually quite deep because there's a product for every budget or wallet that you can actually buy. So,

they were actually very thoughtful about their monetization. And even when they

their monetization. And even when they released the Apple Watch, everyone was talking about the $17,000 gold watch, which no one bought. Um, but the $700 watch didn't look too expensive compared

to the $17,000 watch that was actually talked about, right? So I think when you think about it there actually been and Steve has especially I mean if my personal view is that he was also a

monetization and pricing genius. If I if I could have uh you know go back in time and have dinner maybe with uh with the with at least have a conversation with the deli AI for Steve that would be fascinating.

>> Mine uh I have two questions. Uh the

first question uh pricing models they constantly change but something that doesn't change as human nature. Uh are

there any stories or resources that have taught you a lot about how humans just think about pricing in general?

>> That's a good one. Um so there are we we you know we we um we call it like behavioral pricing just like behavioral economics is you know if you take like B2B situations at least till date it's

humans having a human conversation. You

can set all the pricing you want but you're sitting across the desk and negotiating pricing. So things like

negotiating pricing. So things like behavioral and how people think is way more important than the price sheets or whatever you actually use to like come to that discussion, right? And how you

frame that actually matters. Maybe I'll

tell you a story which was super impactful for a recent founder that we actually work with AI company, right?

And this founder was actually is a kick-ass product, great autonomy, a great attribution, um, and was able to demonstrate, you

know, millions of like savings for their customers purely incremental because this AI was there like in the tens of millions. But the going in assumption

millions. But the going in assumption was I want to charge this on a 50k per year contract. And our question was like

year contract. And our question was like why you're unlocking, you know, many millions. Why 50k? Why not more? And he

millions. Why 50k? Why not more? And he

was like, I don't know if I have the courage to actually put a larger number.

What do I what happens if I lose the deal? I want to make sure I have logos.

deal? I want to make sure I have logos.

And so we actually told him, okay, look, present two options on the table, right?

We said, say that the first option is 50k fixed deal plus 10% of the outcome or a 500k fixed deal. And that actually

gave him a courage to put a 500k price point on the table because he had a 50k price point at the table. The entire

conversation revolved around what is that 10%, how do you measure it? How do

you monitor it? Where do you actually add value? That's a fantastic

add value? That's a fantastic conversation to actually have because that's value based selling. You're all

focused on, you know, what is that 10%, how do you add value? No one talked about the 500 and that 500 got negotiated down to 400 because the buyer at the end of the day said, you know what, that's great. I understood how you

add value and they did the computation and they're like if you do this 10% we're going to pay them way more than the 500k so let's just go with the 500k option I like that and then negotiated

him to 400k so instead of the 50k getting negotiated to 40k which is which was a default he 10xed his price now this is completely behavioral in some ways behavioral for giving the founder

courage to actually put a bigger price on the table behavioral for the buyer to actually say you know how do I actually look at all of these and actually choose and you know often I say that giving

choice in these conversation is way more common than you think. People try to make pricing simple and then erroneously make it very simplistic. Even if you go to a pizza store, buy the pie or buy the

slice are two different pricing models and you encounter that daily, right? So

there are behaviors that are ingrained in us where we can choose and self- select and in that same situation another buyer actually took them up for 50k and 10%. That's a high class problem

because now you actually invented an entire pathway to like make your product better and kick ass so that you can take part in that 10% of the value creation right so these kind of uh human

considerations are like very important and also like price signaling value like I mean there was a Stanford experiment where you know a $2 wine branded as a $200 wine and a $200 wine branded as a

$2 wine when you do a blind test everyone would say the $200 wine was better it doesn't stopped there. They

actually did an MRI scan and figured out that the dopamine effects was way more higher when the $200 wine was actually at play even though it was a $2 wine.

So, not only do we perceive value, we don't we think it's valuable, we perceive it, right? So, price as a signal, anchoring high and negoti all of these considerations important. We

devote entire chap chapters to this in both books. I think it's a great

both books. I think it's a great question. Were there instances where you

question. Were there instances where you uh learned something and you were impressed by a founder that you remember >> there there's always a balance between what data tells you and where your

conviction actually lies right as a practitioner of the field I used to index more on this is the data this is what you back in the day right I mean when I started working with founders but then conviction is a totally different

thing if you actually believe in something and the future the future manifests itself to your beliefs you start creatively visualizing the outcomes. That is something that I

outcomes. That is something that I learned from this founder that was super inspiring that even though I thought that was a really hard pathway to take just by him repeating this to his teams

and the market, it just happened and it was probably one of the most fantastic products out there. You use it today.

But the answer that we actually gave that founder was a tad bit different than what he actually did. So what I realized is you know data and insights and things like that are all useful. It

goes a certain way but then conviction is a whole different thing and probably for the next 100 companies that I work with um I used to tell my teams that we

are change agents you know we need to enable change and how do we build conviction in our answers and manifest that to reality. I think that was probably my biggest lesson. I was trying to probably already take that example

right away with the specifics of the situation, but I'll be giving too much credit to one founder when I worked with a lot, so I don't want to be sounding too partial here.

>> Great. Well, thank you so much. Awesome.

Appreciate your time. Thank you so much.

>> Thanks for tuning in. For personalized

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