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My guest today is Madhavan Ramadhan.
Madhavan quite literally wrote the book on how to price products.
It's called Monetizing Innovations, and his concepts have been used by companies across the world like Portia, Uber, LinkedIn, and Superhuman.
Our conversation is a masterclass on pricing.
We discuss common mistakes when pricing products, why you need to focus on benefits rather than features, and how to pick the right monetization model.
Please enjoy my conversation with Madhavan Ramadhan.
So Madhavan, I loved reading your book years ago and then again in preparation for our conversation today for one major reason.
And we'll talk a lot about that reason in a few minutes here, and we'll go all over the place and all the things you've studied in business.
But the one thing that you sort of blew my mind on with your book is the importance of pricing, which is something that so many entrepreneurs out there struggle with, and the order in which pricing should come in a product conversation.
I think almost everyone puts it at the end.
Let's have an idea, let's talk to customers, let's design something, let's build something, and then let's figure out what to charge for it.
I'd love you to provide your alternative perspective on that order of operations and why you arrived at a radically different way of building products.
I think probably framing the problem at hand.
For many years, I was working as a pricing consultant, especially in Silicon Valley, and I really witnessed how everyone was so obsessed on creating amazing new innovations, but hardly paid attention to how to monetize successfully or to even have a willingness to pay in the market.
Now, we used to even get calls saying, hey, I've built a new product, we've been working on it for the last two years, and we need a price.
And by the way, we needed it last week.
And you couple all these reactions with the failure rate that you actually see in innovation, it's remarkably high.
And when I took a step back and I kind of looked at it, I think the classic phrase that comes to mind is that these companies where I would say simply spraying and praying and hoping that they can monetize and they can build products that people will eventually buy.
But the core issue here is they were hoping because they truly didn't know they built a product, slapped on a price and threw it in the market and hoped for the best.
I mean, this had to change.
And this is why I wrote monetizing innovation, what we call a winning approach is to think pricing early and to really test for whether there's a product market pricing fit before you go too far in the journey.
And the reason for this is inverting that mindset is critical because when you're building something as an entrepreneur, as a company, you actually don't have a choice whether you have a pricing conversation with a customer.
The only thing in your control is when you will have it.
And we are advocating having that much earlier so that you can design the product around what customers need, what they value and what they're willing to pay for, in a sense, know that you will monetize as opposed to hope that you would.
Maybe you can bring this to life and make it tangible for us with an example because it's hard for me to imagine having a price conversation before I have a product to show somebody.
It seems like the impulse is build something, even if it's like a vaporware demo or something and be able to walk in the office and say, this is what we do.
And then maybe have a pricing conversation.
But I think you think pricing conversation should be even before the design and building phase.
So how does one of these conversations unfold if there's nothing to show in the first place?
Yeah, probably I'll take an example or a story and we talk about this in the first chapter of the book.
It's a story from Porsche.
In the early 90s, they were actually, they're thinking of an innovative idea.
They said, okay, should we build an SUV?
But an SUV for a Porsche that just seemed off.
Now, what they did was interesting.
They went to the market.
There's nothing drawn in terms of a blueprint sketch or even a product, but they just went and tried to identify whether there's a need for a Porsche SUV.
And more importantly, would someone pay for it?
Very high level. Pleasant surprise, they actually found that people said, yeah, Porsche SUV could make sense and I would pay for it.
I mean, people who had probably moved on from Porsche because they had a family, et cetera, but they wanted to come back to the Porsche umbrella.
What happened next was super fascinating.
What they did is they came up with blueprint sketches and kept having this conversation with customers trying to identify what did they need, what did they value in an SUV and are they willing to pay for it?
They even did what we call as car clinics where they would build a prototype, full scale prototype, where they would actually bring in people and let them ride the car around.
And not a single unit has been, let's say, manufacturer or productized yet, but it's still a prototype.
And then after that experience, they would have these kind of willingness to pay conversations.
Things like, for instance, a big cup holder, probably which goes against the grain of most engineers, this will look very aesthetically appealing, is in the car because people said they needed, they value it and they're willing to pay for it.
I mean, a six-speed manual transmission, no one needed that in an SUV that was out of the window.
So everything that went into the car was actually battle tested with customers to see if they needed their value.
And more importantly, are they willing to pay for it?
This is a very different way of innovation as compared to like the age-old approach has been always build a product perfected.
Our customers don't know what they want.
Let's slap on a price and throw it in the market and hope for the best.
Very different. But if you look at the output of this exercise, also couldn't have been more different than traditional innovation processes.
I mean, this SUV was launched with the name of Cayenne, which we all know today, accounts for more than half of Porsche's profit and is built in hundreds and thousands of units.
One of the roaring successes in automotive history.
I think the key here is to have that conversation with your customers early.
We are not saying you just have it once.
It's a bit of, you have it over a period of time and sustaining.
Like if you built a prototype and you pitched the value and you pitched the benefits and if someone actually says they won't pay for it, chances are they're not going to pay for it when you build a nicer looking version.
And that's the point. So having the testing and learning much earlier and if someone says no, they won't pay for it.
The most important question is to ask why?
And you start hearing all of these things to design your products around what drives customers needs, what are their value and what are they ultimately willing to pay for?
The folks at first round wrote a blog article which they summarize the entire thesis of the book, monetizing innovation and four succinct words.
They said price before product period.
What I like about that example is Porsche is not showing up saying, we'll build anything you want.
What do you want? They do have an SUV in mind.
They're willing to build single prototypes to test reaction.
You're not walking with a white sheet of paper.
Like there's some opinion that they have, but they're still testing that willingness to pay very, very early on.
And I want to make sure we highlight what is distinct about willingness to pay versus just positive feedback.
Because I think lots of things, features and products or whatever, people might react positively to, but that's not the same as their willingness to pay.
So I want to make sure I understand the difference and then I'll ask what it looks like to have a great willingness to pay conversation.
Like how do you actually structurally execute that strategy?
Most of the companies, at least in the tech space, would tell you they try to achieve a product market fit.
And while that is good, it is not sufficient.
For instance, if someone comes and asks, do you like the headset that you're wearing for this conversation?
Like I like it. Do you like it at $200?
The whole conversation is different.
So if you didn't put pricing as part of your product market fit validation, often you're hearing what you want to hear.
The idea is to get to a product market pricing fit and try to truly understand if at the end of the day, someone will pay for the innovation, as in do they truly value it?
Because I think it also comes down to like, how do we define price?
When we talk price, most people think of a dollar figure.
That's just a price point.
I think we need to educate people to think about price as a measure.
For instance, liter is a measure of volume.
Price is a measure of value.
And when you think of it this way, price really stands for do people want your product and how badly you want it?
And in a way, the easiest way to remember this in Latin, there's only one word for price and value.
It's called Pre-tium. And I think they figured this out long back.
It's reflections of the same coin.
I love that idea that it is the same thing.
And now I want to talk about how you can suss that out in a customer.
There's lots of stages to this.
The first one that's kind of interesting to me is, how do you make sure you're talking to the right potential people in the first place?
One customer's value is maybe very different than another's.
Picking your customer becomes like a really important part of the answers that you get back.
What are the best companies that you've seen do this do?
We'll get to the conversation in a minute.
But before you even do that, you got to pick the people.
How do you do that well? The very first thing to do is to identify what is the problem you're trying to solve?
And is there an unmet need?
And I think this is what you're validating with your customers.
If you just go and ask them, what is the solution or how should I build a product, you'll probably get garbage back.
That's the job of an entrepreneur or a company.
I think you're identifying problems, not solutions, keeping that in mind.
And when you think about problems and unmet needs, likely it is actually going to be very different across your customer base.
So identifying what pockets of customers are you building for becomes critical.
I've worked in most industry verticals and I've not seen a single situation where customer needs are homogeneous.
It's always heterogeneous, whether we like to accept it or not.
I mean, I'll take a very simple example.
Like if you put water in a fountain, it's free.
You put it in a bottle, it's $2.
You put gas in it, it's $2.50 cents, throw it in a mini bar, it's $5.
Same damn water. At the end of the day, it's productized package differently because people have different needs.
I mean, I might like to carry it around.
I might be price conscious.
I might be lazy and I want it in my mini bar or I prefer gas or whatever.
So if you could identify even different needs with a basic thing like water, chances are for your products, you should be able to do that.
So having these conversations with as many people as possible to identify what are those clusters of customers with common needs.
And this is what we call as a segment.
A segmentation should be based on what customers need, what their value and what they're willing to pay for.
And then you productize to segments.
This is what companies, let's say very successful actually do, not build a product and then try to identify who's the decision maker and try to position your product to different segments.
You've already lost the battle.
You need to be able to productize to segments.
And then when you find these clusters of customers who need something and let's say that's a large market that you can capture, you can build the right product for this particular audience.
And that's how I would go about it and identifying who to build for, what need are you solving, what problem are you solving.
And then you need to come up with a solution.
Once you come up with a solution, take the blueprint wireframe, go and pitch the benefits, not the features.
Features is what you build.
Benefits is what customers get.
And if you pitch the benefits, you're trying to see if their eyes light up and are they willing to pay for it.
And like I said, chances are if they're not, no matter what you do and put some perfume on this and make a better product, they're not going to be able to do it.
And you can do this in stages.
I mean, you can do it in multiple stages and keep iterating your products around this kind of information.
And that is the crux of what we are preaching.
Can you put a little more description around this idea of productizing for a segment?
So let's imagine a product, maybe we could stick with the Porsche or something.
You would think, like, okay, there's one version of this product, I could highlight it in different ways.
But do you actually mean build a slightly different product for each segment and maybe just describe that a little bit more because it sounds like kind of an unusual thing?
Yeah, the most common approach, which is also the faulty approach is to build a product.
I've even heard this phrase called, we are building a one size fits all.
I usually correct people saying one size fits none.
You're trying to build one and then try to position the same product to different segments.
That's the wrong strategy because in those kind of situations, a segment is just purely based on who are we servicing?
What is the persona? What are their behaviors and how do I position the products?
But what is missing in this whole strategy is you truly don't know what different segments need.
What do they value and what are they willing to pay for?
So segmentation needs to be based on needs, value and willingness to pay so that you can build the right product for a segment so that you can offer the right product at the right price.
And this is what I mean by productizing to a segment as opposed to positioning a product to different segments.
And in this case, when you scan the market, you will actually see that the needs actually differ or different unmet needs actually exist.
You need to find clusters of people who are actually willing to pay for things.
Similarly, need certain things and have a willingness to pay.
And that's what you're productizing towards.
And if you look at Porsche, for instance, they would have different classes of their own cars.
Why is that? Because they're actually servicing different segments.
I mean, it's the same thing with Apple iPhone.
If they had said, let's keep it simple and just build one model that would have never been a successful strategy, right?
I mean, they wouldn't be the most profitable company in the planet if they had done that.
I mean, they said, let's just build a $99 iPhone.
And that's that if you actually look at it, there's an iPhone from $299 all the way to $1499.
In a way, they're productized to a price point or a segment.
They have not just priced their products.
To give you a more tangible example, remember the iPhone X was launching it was $1499.
I was like, okay, and look at it.
I was not willing to pay this, but there was another phone without all those retina features for like $799.
I'm like, I'm paying for that.
So I belong to that segment.
So there was already a product for that segment that is the key.
If that product didn't exist, I wouldn't have probably purchased the phone at that point in time.
And then you're just building one product and hoping.
But at that same token, if you have one price, you're either going to be overpriced for some or underpriced for others, you're never going to get this right.
So you're productizing to different willingness to pay or different segments in a sense.
If you go back to the beginning of the innovation life cycle, so we're at the stage of the prototype SUV, let's call it, talk us through how to have one of these conversations with a perspective customer.
What are the kinds of questions that you recommend companies ask to make sure they're getting an accurate measure of some sort of price or a willingness to pay or a value or something?
I think this is the most critical and important step in the whole process.
And we've actually dedicated a whole chapter in the book, monetizing innovation chapter four, it's called how to have the willingness to take conversation.
If you go and ask a customer, what should I charge for this product?
You will get garbage back.
That's your job. That's not your customer's job to solve your pricing strategy.
But there's some clever ways of asking this in such a way that you get some meaningful responses.
For instance, one of the easiest things that I remember a founder actually did to find out their pricing strategy is he kept doubling the price in every deal till someone laughed him out of the room.
Okay, he found that there was a threshold and he hit that and then he knew that that's why he needs to stabilize.
That's at the basic level, right?
I mean, just keep doubling till you hit the ceiling.
That's one way to have that conversation.
Some other ways to have that conversation is put people in a relative mindset.
I mean, tongue-in-cheek, I say people are absolutely meaningless but relatively super smart.
What I mean by this is if you go and ask them on how much should I charge, you'd get garbage.
But relatively speaking, people can make a very intelligent and informed decision.
For instance, if I am, let's say I'm making a software product, SaaS product, and I go and ask the prospect that I'm trying to sell to and I say, hey, do you have Salesforce installed in your install base and say, yes, I do.
Okay, if Salesforce was indexed at 100 in value, what do you think we bring to the table for your business?
That's a question people can answer all day long, which is if they say it's 70 or 80, then that's how much you're off compared to like Salesforce.
Similarly, if you say if Salesforce was indexed at 100 in price, where do you think we should be?
That's also an answer that people can make more sense of.
In fact, you can bring that back into your negotiation strategies when you're selling this product again saying, hey, look, you're paying X for Salesforce.
Typically, this is the value we are here and we can justify our price and you can quickly justify the price that you're actually coming up with.
So these are kind of relative questions.
There are more in-depth ways of asking.
One of the probably most useful Monday morning ways of actually asking this is to ask what I call as the acceptable, expensive, and prohibitively expensive question.
What this means is think about this.
You identified a problem and unmet need in the market.
You came up with a solution to actually address this unmet need.
You built a prototype wireframe product, whatever you want to call it blueprint, and then you pitch this to the customers, pitch the benefits, pitch the value, and go to the same exercise you would go through after you launch the product, but before pitch the value and then ask them, what do you think is an acceptable price for this innovation?
Now, we all know that people love to low ball themselves.
They would negotiate and they would give you an answer clock that and then ask them, what do you think is an expensive price and then follow that with like, what do you think is a prohibitively expensive price?
What we have seen across thousands of projects that we have done in this space, acceptable tends to be the price that people not only love your product, but they also love your price.
If you're in some really fast growth mode, you could keep it because it's a no brainer, no friction price, no one thinks about it.
The right price usually tends to be around the expensive price.
This is the value price.
As in what people will pay you for the value you bring to the table, they would not necessarily be your best friends, they won't be enemies.
It's a neutral reaction.
It's like the value price prohibitively expensive tends to be the price that they would actually laugh you out of the room.
And if you do this at scale, you can start seeing what are the psychological thresholds in the market.
Is there a let's say $49 per month that I need to be at because once I cross 50, the demand actually just drops.
You will be able to validate these kind of what we call as psychological thresholds and we write about this in the book.
And it's super important to know these things because if you don't, without knowing it, you could actually be losing a lot of demand when you could have been just a bit under the threshold and sort of had a better pricing strategy.
Rahul Wora from Superhuman actually used this method after he read Monetizing Innovation.
I think he talked in one of the podcasts.
I think it was an A16Z podcast that I heard that he actually used this and that's how he priced Superhuman.
Of course, there are more advanced methods which involve putting people through actual purchasing decisions and seeing how they would react.
This is very akin to real life and then change the situation and then see how they would react again.
So you're tapping into the mental models and rules that they're using to make decisions and infer what drove that decision making.
We write about this also, but starting with doubling your price all the way down to purchase simulations or scenarios, there are a range of ways to actually go about the willingness to pay conversation.
The key is to do it. It sounds incredibly empirical, which makes it really, really appealing.
I wonder how you've learned about the motivations of buyers.
What are some heuristics for how a buyer processes evaluation on the fly for something like a Porsche?
What is going through the prospect's mind?
What is driving their feedback?
So the key thing is, as a, let's say, a seller of this information, you need to put the buyer in the same state of mind that you would if they had the product in front of them when they don't have it.
I mean, as close as possible.
And so the buyer needs to be in that mindset of decision making, where they truly understand what does this product bring to the table?
What need is this product solving?
Hence, what benefit do I actually get?
Is that benefit tangible?
And then the natural question is, what portion of that benefit am I willing to give back to the seller?
When you need to put them in that mindset, if I get a unlock in terms of efficiency, what am I actually willing to pay for it, for instance?
So the key is to pitch the product and the value and benefits as opposed to discuss features and tell your buyers what can they expect from the product and what unmet need is the product solving.
And then you need to put them in that mindset of, okay, I need this product and there's more of a decision making buying mindset is how I would define it.
There's this great little phrase in the book when it comes to product configuration, which is leaders, fillers and killers.
Can you talk about what those three things are as we start to move from how to have the conversation to actually arranging the product, whether it's for a segment or overall?
Let's say you're testing a whole bunch of benefits, then you need to assemble these benefits or let's say even features that you're building into a product.
That's a packaging exercise or you might actually take multiple products and come up with a bundle of different products.
Either way, it is basically configuring what you're actually selling.
So the leader, fillers and killers sort of principle is useful in determining what to productize, like how to configure your product.
The easiest way to understand this is if you think about a McDonald's, Happy Meal, your burger is a leader product.
That's what people are actually coming for.
Your french fries and coques are the filler product.
If you put it in a bundle, more people would probably take french fries and coke.
If it's stall stand alone, probably people are looking still for the leader product, which is the burger.
Killer products are the ones that you need to be careful about because if you put it in a bundle, it'll kill the bundle.
For instance, if you package a coffee along with a french fries, coke and burger, it's going to kill the bundle.
No one needs a double dose of caffeine, hopefully, when they're having a burger.
But there are people like me who disproportionately love to have a coffee with a burger.
So what happens is the coffee is stripped and sold standalone at a higher price point because I'm actually willing to pay for it.
If you put this in a bundle, what's happening is it just depreciates the price point for everyone because majority of them won't pay for it.
So you're actually selling it at a much lesser rate.
So the idea is to take it and say, okay, that's an add-on.
How do you come up with a bundle or package which has leaders and fillers, avoids the killers, and then you need to determine whether the killers can be standalone products or simply stuff that should be not productized per se?
What are some of the biggest mistakes or traps that you see companies fall into when running this process?
So even if they're doing what you've said so far, they're having the pricing conversation early, they're thoughtful about segmentation and productizing for segments, all the things we've talked about so far.
What are some of the big mistakes that still happen?
Let's assume that you had the conversations early, you focused on segmentation, you had the right product.
One is thinking about pricing as just how much to charge as opposed to how to charge.
What we, Tangin-Chik often says, how you charge is way more important than how much you charge.
As in, what is the right pricing model or monetization model and keeping that in mind?
And the other one I would say is talking features and not benefits.
If you don't speak, the value of your product people won't get it.
And you need to be able to speak benefits as opposed to talking features.
Let's take this in reverse order.
Maybe give an example of, or even a rule of thumb for what is a benefit versus a feature?
Like, how do I know that it's a benefit versus a feature or vice versa?
I can probably take an example to illustrate this.
And we discussed this example also in the book.
I mean, I'm sure you've probably heard of a company called Smug Mug.
They used to have a pricing plan, which you needed to probably scroll down and actually see.
And it was all the features that were listed, everything that was actually engineered.
What they did is they didn't do any changes to the products, but they just simply changed the way they communicated their products to customers.
They actually started focusing on benefits.
And for them, let's say the benefit, let's say, was the ability to sell photos online.
That is a benefit. But there's probably 10 or 15 features that actually need to be in place to enable that benefit.
Initially, they used to talk about all the 10 or 15 things.
But then once they started talking about benefits, the ability to sell or the ability to have personalization, this is the benefit.
It was double digit improvements in revenue, no changes in products.
Just the way you talk about the product and the value.
I mean, having that articulation becomes key.
And one of my favorite examples of value communication also comes from Porsche.
I think it was when they were launching the Taycan.
I think their CEO said something like, Taycan is not one of the most affordable electric vehicles you can buy.
There was never Porsche's goal.
First and foremost, it is a Porsche.
Something like this is dramatically resonating with their customer segments.
I mean, how do you pitch the value fast?
And how do you talk about the benefits becomes key.
And if you don't, then you're left with features and then you leave the customers to interpret what benefit they're actually getting.
Ideally, you would be able to also tie your pricing strategy in terms of your pricing model to the benefit that is being realized.
And that's part one of them is step.
Simple way to think about this.
A benefit is what your product does for them and a feature is how they use your product to do it or something like that, like the one, the how.
Yeah, exactly. Yeah, that's a good way to think about it.
What did you build and how does that impact the customer?
If we go back to the how to charge your customer, I think in the book you highlight, memory serves like five distinct models for charging.
Maybe you could just tick those off.
We don't have to go through each in detail.
But I would love to hear at a high level, how you see successful firms triangulate on the way that they're going to charge.
Some things are just obvious.
For a burger, you're going to charge for the burger.
You're not going to probably not going to charge like a monthly subscription and all you can eat to McDonald's or something.
Although maybe that's possible.
Maybe just take the five off and then we could talk a little bit about why this is so important for success.
So we talk about different pricing models and the most common ones are, should you have, let's say, something like a subscription model, which is more on a predictable basis, same price, month over month, for instance.
Or should you actually be more on a pay as you go or usage based models?
This is the second one. You're basically paying upon consumption.
And of course, you can have a hybrid with a portion of it being in subscription, portion of it being in pay as you go.
Then you also have models like the dynamic pricing models.
How do you price in such a way that it's an equilibrium price between supply and the demand side?
How does it actually change over a period of time?
There's also models like, for instance, completely being freemium.
That's also a pricing model.
To what extent should you build a freemium?
And what is the difference between, let's say, a freemium and a premium pricing strategy?
So there are various models to consider, but I think the key thing is not to gravitate to one or the other just because someone else is doing it, but to truly identify what is the right pricing model and then build around it and focus on how you charge questions.
We even talk about an interesting way of quickly getting to the pricing model.
I mean, we even do some experiments.
For instance, if you put someone in a thought experiment and say, okay, look, if you're selling an item for $100, if I charge you, let's say, 10% or if I charge you $5.00 and 5% or if I charge you $10.00, are you indifferent among these or do you prefer one?
I mean, everything that we learned in school, mathematics, economic, human being, rational stuff would say that I'm indifferent.
I've done this experiment, I simplified it, but I've done this kind of experiment thousands of times.
I've never seen the indifferent actually.
There's always a model that just makes intuitive sense for your customers and identifying that.
And if you can tie it to the value being generated, nothing like it.
It's kind of another version of the same thing you started with, which is the important thing is to have the conversation and have it in relative terms, not absolute terms.
Is that kind of the basic sum up?
Yes, that is the basic sum up.
And I think, like I said, tying it to the value is at the end of the day, if people can understand why they are buying in a certain manner, that actually is super important, not just rushing to, let's say, subscription versus usage, but truly trying to understand what makes sense for your product and your business situation.
Do you find that most of the time, the value piece of all this boils down to the same few common denominators?
Like one example would be, I could sell you time, I could sell you money, I could sell you signaling value or something like there probably aren't that many core motivations if you keep asking why.
Do you find that that is true?
Yes, that is definitely true.
Time money is probably a great example.
Are you able to do certain things faster compared to like, let's say, existing alternates?
Are you able to do it better?
That could be better in terms of, let's say, starting as basic as better resolution to like a better way of approaching things and people actually relate to that.
And of course, is it saving some money and it's an efficient process, etc.
But then what is it? I mean, the level two is probably important.
The level one is probably these high level dimensions, but what exactly is that?
For instance, if I'm saving money, where is that coming from?
Is it inventory reduction, for instance?
What service level can I actually achieve from that inventory reduction?
What kind of pricing strategy can I have for a software that lets you reduce inventory but keep the same customer service level?
What gains do customers have?
Is that a problem? Am I solving it?
Is there an economic value that is generated?
And what portion of that economic value can I capture?
So that's literally how this conversation goes.
And as a rule of thumb, what we have seen is you should be able to capture at least 20 to 25% of the economic value that you are actually bringing to the table.
This is a good range to be in because if you're around the 50%, most likely you're leaving space for someone to disrupt you.
If you're less than the 20%, you're under monetizing.
So at least 20% is a good rule of thumb of the economic value that you are generating for the customer.
This could be time savings.
This could be efficiency gains, money savings, whatever it is.
Does that insight translate into net margins, operating margins, gross margins, some combination of them?
Like it sounds like a margin insight.
Which margin? Before I rush to like a margin framing, I would frame this as you're trying to align your price to the value that someone subscribes to the product.
And then you need to control your cost structure to like maximize your margin.
This is why you have to make a distinction between your pricing strategy and the market willingness to pay.
So everything that we've been talking about is the willingness to pay of the market.
That determines the price.
And of course your cost structures and how you can improve it will determine margin.
So this is not a cost plus margin strategy.
That is famously called the cost plus pricing strategy.
That is usually very suboptimal.
You need to be more value based pricing strategy, which is by definition deeps and bounds better.
What are some things that you tell entrepreneurs as you're talking about pricing their product that tend to most surprise them?
I think it starts with even understanding that there is a science behind this because they all approach this as an art.
It's often an afterthought, but it's also driven based on gut feeling.
To substantiate this and say, no, there's actually a science behind measuring willingness to pay itself is a revelation for many entrepreneurs.
This is also why I wrote the book to give back a bit of what we actually know, to educate people that there is a science and an art to pricing.
The second thing that probably surprises entrepreneurs, which you already talked about is having that conversation early and often and not postponing this to the very end.
Because most entrepreneurs or companies, especially in the tech side, are so fixated on the product that they are not thinking about how to have a commercial conversation with their customers till the very end.
And by that time, it's probably too late.
And we, they might end up building one of the four failure types that we talk about in the book on for monetizing innovation failure types.
The idea is to build the fifth category, which is called the breakthrough category.
For that, you need to have these conversations early.
That's probably also equally revealing for entrepreneurs.
The third one I would probably say is thinking about what to build and who are you building for?
Because often we think about our customers and say, we are the best proxy for our customers and start building something.
And that's sometimes or probably most times not true.
So like thinking about segmentation and productizing to segments, I mean, which we just talked about is also a key unlearning a bit of what they already are used to, which is build a product and then try to somehow sell it in the market as opposed to build the right product for the right segment.
Obviously, everyone wants to avoid being one of those four failure types.
At a high level, what are those?
Those four most common categories of failure?
The first monetizing innovation failure type is what I call as a feature shock.
These are products where there's simply just too much going on.
I mean, if you hear things like, our customers don't know what they want, let's just pack this in.
Most likely you're building a feature shock and it's just an excess.
And at the end of the day, it does not resonate with anyone in particular.
You've just thrown in the kitchen sink and you hope for the best.
Swarovski Armini. Exactly.
I mean, the idea is to probably productize into different segments, as opposed to just throwing everything in.
I mean, happens in some of the most successful companies of our time.
I mean, if you take the Amazon Firephone, I mean, Amazon is ridiculously successful company of our time, but the Firephone, I mean, MarketWatch actually documented all the plethora of features that no one wanted.
And the phone started at $179 and six months, it was 99 cents.
And they wrote off that entire business because people were not willing to pay for stuff that was actually there.
I mean, in fact, they would say, why am I paying for this?
The second one is probably more prevalent in tech companies.
It's called minivation.
So this failure type happens when the product or the company or the entrepreneur build the absolutely right product market fit product, but they did not have the courage to charge the right price.
So we call that as a minivation to give you an example.
One of the semiconductors here in the Bay Area, their companies, they came up with a groundbreaking revolutionary chip and this was just game changing.
And there's this thing in semiconductors called Moore's law, where every generation, there's an expectation that the price would decrease because the farm factor is decreasing.
So your cost to produce the goods is lesser, but they knew that they had come up with something truly innovative.
So they said, let's undo Moore's law.
And the previous generation was 65 cents.
They said, let's price it at 85 cents.
And the product flew out of the shelf.
Secret in the room was that everyone knew that they could have charged more, for instance.
They went and did a post-modern two years after this product was launched.
What they found out was these consumer electronics companies that ended up using these semiconductor chips could actually charge $50 of premium from people like you and I simply because this chip was inside.
And when you look at 85 cents for $50 of economic value, that was completely unfair.
And in fact, most of them laughed saying you could have gone all the way to $5 and we'd have been just fine.
I mean, you multiply that with the millions and billions of these chips that were actually sold.
How much money was left on the table that is staggering.
That's a minivation where you had the absolutely right product market fit solving the need, but you just didn't have the courage to ask the right price.
That's a minivation. The third monetizing innovation failure type is what we call as hidden gems.
So these are products that kind of go against the grain of your company or your DNA.
And you just don't want to productize this because you're worried about cannibalizing your existing business.
So you just put it in a shelf and it's hidden.
The famous example here is Kodak, which had the IP for digital photographs back in the 1970s, but never productize it because they're worried about cannibalizing the entire print business.
But if you take someone like autotrader.com or cars.com, these are multi-sided marketplaces where consumers can go and buy cars from dealers.
They were started by the Chicago or the Atlanta Daily newspaper because they realized that ads were actually going to shift from newspapers to internet.
So they built multi-sided marketplaces and that's actually a fascinating example of harnessing a hidden gem.
Usually these hidden gems happen when there's an inflection point like a software company going hardware, hardware to software, offline to online or the other way around.
So looking for them is important.
If you don't go looking, it is mostly hidden.
And the last category of monetizing innovation failure probably by far my favorite is what I call as undead.
So you can call them walking deads or whatever.
These are like in classic science fiction movie fashion.
You should have never produced them because they come back to haunt you.
And they come in two varieties.
They're either the wrong answer to the right question or the answer to a question no one cares about.
Either way productizing it was a bad idea and you should have stopped it.
I mean happens all the time.
And again, even in some of the most successful companies, if I take Google for instance, super successful company, the Google Glass Initiative was a complete dead on arrival in two months.
I mean, price at 1500, the Paparazzi swore it for two months and it's unsetted the product.
We actually wrote in monetizing innovation that better strategy would have been to actually take segments that are willing to pay for this and productize and perfect the product before going consumer like the B2B segments.
For instance, if I was a technician and I could have my hands free when I'm doing a repair job or if I could have my hands free when I'm a surgeon and I'm doing a surgery, there's clearly a willingness to pay for these kind of use cases and how can I productize to these use cases and build the glass would have been a better strategy.
This is productizing to the segment that we talked about, not just building a product and hoping to position to different segments.
We haven't talked at all about the companies and how they look behind some of these success stories.
Who is it that tends to be doing this work?
Is it the CEO of the company?
Is it someone else? And is there anything you've noticed about the way organizations work or are structured that either leads them to be more or less prone to doing this kind of work well?
We run the world's largest pricing study every other year.
I mean, as part of our work at Simon Kutcher, which is where I spend my time.
What we found is that 72% of innovations fail to monetize, but then the clear question is what do these 28% do?
And there are only two success criterias that actually is relevant for these companies.
One is the price before product, which we have discussed.
The second one is C level involvement.
As in a CEO, founder, or at least a C level involvement when it comes to topics around monetization, growth, or monetizing innovation.
And we were able to benchmark that companies that had this involvement were 35% better than companies that did not in all kinds of KPIs.
And to me, pricing, monetization, growth, especially when you think of it as a growth as a topic, is a 100% CEO topic.
And in the book, Monetizing Innovation, every chapter, we end the book with what questions a CEO must ask in, let's say, meetings.
This does not mean that the CEO should rush and roll up their sleeves and start setting price books.
That's not what we're talking about.
But it's about setting the right culture, the right tone, asking the right questions so that you build a culture around profitable growth and not just growth at all sake.
I love the idea of senior involvement.
It seems to be the answer to a lot of problems in companies, lack of focus, this sort of thing.
When you see someone that's doing this well, and they're especially trying to choose how to deliver the pricing, so the models you mentioned, pay as you go, or usage-based subscription, et cetera, do you find that there are good rules that these leaders can use, like heuristics almost, to have a general sense beyond just asking, like, which way would you prefer
to pay us? Because sometimes usage-based just may not work for the economics of the business.
It might work really well from a revenue standpoint, but have some cost problem or vice versa.
Any heuristics you've developed for knowing which path to guide people down around how to charge?
Yeah, absolutely. I think let's maybe keep the focus on subscription versus usage-based models, because I think those are the ones that are commonly used and also commonly misused.
There are certain situations under which a subscription model could make sense, and certain situations under which a usage-based model might make sense.
When you think about subscription models, or how to charge based on subscriptions, it totally makes sense when customers, let's say, demand predictable bills, as in they want things to be predictable, and hence you are by definition tied to subscription.
Or it could also make sense when, let's say the usage is similar month over month, for instance, if you're ordering tightpots, it's not like suddenly you start washing more clothes in May compared to like June.
It's kind of predictable.
So a subscription would actually make sense because the usage is similar month over month.
Or it could also make sense when usage is highly variable, because if you don't have a subscription and you have a usage-based model, your pricing is going to fluctuate too much month over month.
So then having a subscription is probably a better customer-friendly model, as opposed to giving a heartburn every other month, so to speak.
Or it could also make sense when the usage is intermittent, but the value delivered is ongoing.
So the easy example here is if you take someone like LifeLock, for instance, an identity theft protection product, there is a value that is ongoing because they're actually giving you peace of mind.
The usage is very intermittent.
It only happens once when your identity is actually compromised.
If you start saying, okay, I'm going to price based on, at that moment on usage, if your identity got compromised, that's the worst pricing model you can actually have.
I mean, a subscription makes total sense because you're paying for peace of mind.
As in, the usage is intermittent or episodic, but the value delivered is ongoing.
And the last probably way a subscription could make sense is when simplifying the conversation is to your advantage.
For instance, if you look at the famous example of Netflix versus Blockbuster, they simplified the conversation.
That was to that advantage.
And it just made sense because people had all kinds of reactions to Blockbuster's pricing model back in the day.
If you think of payers, you go, when does that make sense?
I mean, it makes sense when, first of all, you have a situation where people want to commit less, and it's a low commit, less friction kind of model makes it easier for users to onboard.
So the AWS model is a good one.
I mean, you don't have to plunk in a lot of money for infrastructure and server needs, but you're actually paying in chunks as you actually consume.
So that in those kind of situation, it makes sense.
Or it could also make sense when customers demand transparency and fairness.
I think this is an absolute distinction that people should keep in mind because transparency and fairness has nothing to do with being predictable.
Most people confuse this.
They would say, oh, I'm predictable.
Why? Because I want to be fair to the customer.
No, that's actually completely different.
Transparency and fairness is typically linked to usage and to the value that you deliver.
Am I paying the fair price for the value realized?
That's how you should think about fairness.
For instance, if you don't use a subscription for a few months, is it fair to charge the customer for those months?
That's fairness. So we should not mix fairness and transparency with being predictable.
Those are very different things.
A few more situations, I would say if your usage is intermittent or episodic and the value delivered is also episodic and not ongoing.
So it's a bit of a different case than the LifeLock example, which means that it's like booking a flight or you want to go to a movie.
You call the McDonald's, for example, you go there, you have a transaction.
Of course, you can think of a subscription for some users, but for most users, the usage is intermittent or episodic and the value delivered is also episodic and it's not an ongoing value delivery.
That's when a pay as you go can help.
Also helps when they're underlying costs with scale with usage.
I think AWS is a good example.
There's a cost to infrastructure that highly scales with usage.
So if you don't have that and you just have a subscription with more usage, someone might actually be the negative margin customer for you.
But the alternate to have a pay as you go model would make sense because then as much as you're using, you're also like kind of paying the other fundamental thing to keep in mind on pay as you go, which I find many companies struggle with is you need to have a metric that you and your customers clearly agree to and there is attribution, not just rushing to a model based
on usage, but you need to be able to track this.
You need to be able to measure according to this metric.
You need to be able to show value delivered according to this metric.
And that is also important.
And often that does not exist in many SaaS products.
And if you're not very clear about attribution on where you're actually delivering the value, but you just know it at a high level, maybe the easiest strategy to be is on a subscription model rather than pay as you go.
The fascinating set of ideas.
Like you said, different heuristics, different situations under which one or the other would work.
I love three dimensional plotting of a business of frequency of usage, frequency of value delivery and the cost of value delivery.
You could kind of put all three of those together and plot businesses in that space and see fascinating results.
It's definitely an exercise I'm going to start doing and it makes a lot of sense.
Twilio and software, they have a very high cost.
They have low gross margins relative to most software and the same with AWS.
The usage based model jumps off the page.
I love it. I think it's a fantastic way of thinking through the problem.
As you were talking, it brought to mind another question, which is the behavior changes or the things you've learned as the absolute price goes up and down.
I saw something interesting recently, which was that for something that's very high priced, and this was a software centric, but I guess it could apply everywhere.
It almost demands that you have to educate the customer.
If something's very low priced, you better not have to educate the customer.
It's just not going to work.
It has to be incredibly simple and intuitive to use.
Have you found anything like that in your exploration of the absolute price curve that monetizing something at a million dollars a user is very different than $10 a user and points of interest in between?
Yeah, I think a couple of things.
First of all, price needs to be a measure of value, like we discussed.
Often, people use pricing as a cue towards is the product actually good or is it valuable?
We have to keep that in mind because as a behavioral component, if you walk into a, let's say, a safe way and you see a $10 wine and $100 wine, chances are you would say the $100 wine is better because most people would probably say that with higher prices, better quality, etc.
But then on a blind test, actually fail it completely.
When you think about higher price, that also signals high quality in some way, shape or form.
So if your product is, let's say, emphasizes quality or like iPhone is a good example.
When they came out, it was emphasizing quality, brand, etc.
So then having a low price for those kind of products would actually be counterintuitive.
It will actually work against you because you didn't emphasize what people should learn about your products.
And pricing is how people learn about your products.
If it is a low price product, often you probably need to have land and expand where you're probably acquiring people on a low price products, but then you have something else to upsell them over a period of time.
So those products need to have pricing that just makes, like you said, intuitive sense and it's a no brainer price.
And often it's the acceptable pricing that we talked about rather than even the expensive price, but a product that just brings people into the ecosystem and then you can monetize more as and when their needs, as and when the customer needs actually increase.
I wouldn't oversimplify it to saying that if your pricing is low, you don't need to educate and if your pricing is high, you need to educate.
I would probably correct that to say, it's your job to educate your customers as to what you're charging based on the value that you deliver.
I mean, you need to educate people on value no matter what.
And as a consequence, defend your pricing strategy and your price integrity.
If you think about the thousands of episodes of this that you've seen firsthand, is there a pricing genius, a person out there that most pops to mind?
Like when I say pricing genius, does any one person come to mind?
Yes. Steve Jobs was a pricing genius.
When most people think about Steve Jobs, they think about a product genius.
In fact, I even get a question sometimes saying, yeah, you talk about willingness to pay, market validation, customers, everything else.
But famously, Steve Jobs said, I don't need to ask customers anything and I would just come up with stuff.
To me, let's say most misunderstood concepts.
This is just according to me.
I think that lazy approach is to say, Steve Jobs didn't test with customers and I don't need to.
But if you look deeper, I think what he was trying to say is that it's your job as an entrepreneur to come up with a solution to a problem and there is no point in asking a customer to dictate that.
Similarly, there's no point in asking customers what should I build or what should I charge for this product.
You'll get garbage back.
The idea is to identify these problems and unmet needs and then solutionize yourself.
And then the prototypes try to understand is there a willingness to pay and would markets actually pay for it?
If you look at Apple or what Steve Jobs did, he just didn't launch a product, but he actually had a clear pricing strategy in mind.
When you think about, let's say the iPhone came up at a very high price and there was a skimming strategy, which we talk about in the book, launched the product at a high price and over a period of time, the prices reduced, more generations actually come out.
It's actually built to different segments.
Like I said, there's an iPhone at $299, $399 all the way to $1499.
So they didn't even price the product.
They productized to different price points of willingness to pay.
Then there is also the emphasis on what type of pricing model might make sense, how to educate customers on the value of these products, the behavioral pricing tactics, everything that we talk about in the book has been emphasized in the launch strategies.
I mean, if Steve had been sitting around a room and said, let's price this product at $99 and we just need one version, we need to get growth, that would be the absolutely wrong thing that they would have done.
I mean, not to say they wouldn't have been probably successful, but they wouldn't have been successful to the scale that they are, which is being the most profitable company in the planet.
I consider Steve Jobs as a pricing genius, not just as a product genius.
And I think the most misunderstood concept is that he's just a product genius.
In chapter two of the book, I actually wanted to title the chapter as I haven't said this before, but I wanted to title the chapter as you are not Steve Jobs.
And the editor thought it was too provocative.
So we actually toned it down to why good people get it wrong.
Same concept. Less memorable.
You mentioned in the book that you have these questions that leaders can and should ask as a result of the ideas in the chapter.
If it was your job to boil everything down to a single question and you knew that tomorrow every business leader was going to ask themselves a single question, what question would you pick?
I would probably ask simple question.
How do you know that our customers would pay for this innovation?
And that will probably lead to a very good discussion.
How do you truly know? This has been one of my favorite books on this topic.
It can be an intimidating topic.
Like I said at the beginning, it's certainly one that comes up all the time working with entrepreneurs trying to figure out this problem.
I think the refreshing thing about your book in this conversation is that it is approachable.
It requires a lot of work.
You have to go do it. That's the most important thing.
But there are strategies for doing it.
And I think we've talked a lot about some of the best ones today.
And I really appreciate your time.
I ask everyone that I talked to the same traditional closing question.
What is the kindest thing that anyone's ever done for you?
I would probably say that I'm blessed to be surrounded by some amazing people both in my personal life and my professional life who have been super kind and supportive and I wouldn't be here without them.
But I think for the podcast, maybe I'll keep my answer to like a business context or professional context, if you will.
I think many, many people have taken a bet on me earlier in my career, have given a helping hand, being kind and supportive.
But one example that comes to mind is Duncan Robertson, who was actually the CFO of OpenTable at that time.
And I worked with OpenTable many, many years ago, like probably 10 years ago or something as a pricing consultant.
And he was very impressed with the work and out of his own account, he came and said, do you want to meet Bill Gurley and discuss the outputs of your work?
And I was like hiding my excitement.
I was like, sure, but I was like internally, hell yes, I mean, that would be awesome.
And he introduced me to Bill and Bill was on the board of OpenTable back then and he did this out of his own kindness.
I met Bill. We have stayed in touch over the last decade and Bill has been incredibly supportive of me and a big proponent of the work that I do.
I can confidently say that 100%, I would not be here today without support from folks like Duncan and Bill.
I can't thank them enough for their kindness and support, but there are many, many more examples, but this particular one probably stands out to me.
Well, thank you so much.
Bill Gurley, definitely a good friend of the podcast.
I think he's actually our most frequent guest at this point, which makes that's a fun closing answer.
Thank you, Madhavan, so much for your time.
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