Validate_Business_Ideas_Without_Building_Anything

[00:00:00] Welcome to Business Conversations with Pi m, PT 2.0, where the advice is real, but the voices are ai. I'm sc and we're harnessing cutting edge artificial intelligence to tackle real world business challenges and deliver actionable strategies you can implement. Right now. Joining us is our newest AI voice, Peet sharp, insightful, and ready to challenge conventional wisdom.

The questions are real. The data is vast, and the insights game changing. So buckle up SC believers, it's time to get across the start line. Let's dive in.

 PI: Welcome to another deep dive. We are, uh, so glad you're here with us today. 

Piet: Yeah. Really excited to get into this one 

 PI: because if you've ever had a brilliant idea, um, you know, one that just pops into your head in the shower while you're commuting and you thought, this is it, this is the billion dollar idea, 

Piet: we've all been there, 

 PI: right?

If you've had that moment, then this deep dive is exactly for you. Today, our mission [00:01:00] is to figure out how to validate a business idea. Quickly and, uh, cheaply without actually building a single thing. 

Piet: It sounds almost counterintuitive, doesn't it? I mean, the traditional instinct is to just start building to get to work.

 PI: Exactly. 

Piet: But today we are gonna look at why that instinct is actually the most dangerous thing you can follow. We're pulling insights from a really fantastic stack of materials for this. 

 PI: Yeah, we have a great lineup. 

Piet: We've got notes from Stanford Seminars featuring Alberto Savoia deep Dive webinars from the team at strategizer plus the foundational principles of the Lean Startup methodology.

 PI: Oh, and don't forget Rob Fitzpatrick's book, 

Piet: right? The Mom Test. Incredible practical wisdom in that one. 

 PI: Okay, let's unpack this because, uh, uh, we've all seen it. Everyone thinks their idea is flawless, but the reality is most ideas just completely flop. You spend months, maybe years, thousands of dollars, you finally launch it.

Yeah. And you just get crickets. Nobody cares. 

Piet: Mm-hmm. 

 PI: Why does that happen [00:02:00] So consistently across like every in. 

Piet: Well, it happens because we fundamentally misunderstand the nature of failure. Alberto Savoia, who used to be an engineering director at Google, introduces a concept he calls the law of market failure.

 PI: The law of market failure, 

Piet: right? And he breaks it down using the acronym, 

 PI: F-L-O-P-F-L-O-P. 

Piet: That stands for failure due to launch operation or premise 

 PI: launch operation or premise. Okay. Walk me through what those actually look like in the real world. 

Piet: Sure. So launch means your marketing was bad. You built something great, but your messaging was off or nobody even found out about it.

 PI: Got it. What about operation? 

Piet: Operation means the product itself was broken, the app kept crashing, the servers went down. Or you know, the food at your new restaurant tasted terrible. 

 PI: Right? 

Piet: But here's the kicker. The vast majority of new ideas do not fail because of launch for operation. They fail because of the premise.

 PI: The premise itself. 

Piet: Exactly. Meaning even if you [00:03:00] execute the product flawlessly and you market it brilliantly, the market simply does not care. People do not actually want the product you built. 

 PI: Wow. That is a genuinely tough pill to swallow. 

Piet: Yeah. 

 PI: I think we all like to believe in that, uh, that feel of dreams, myth.

Piet: If you build it, they will come. 

 PI: Right. If you just build it Right, they will come. 

Piet: They won't. And that brings us to the core theme from the Lean Startup methodology. Startup success isn't about having good genes or being a singular visionary, or just magically being in the right place at the right time.

 PI: So it's not just luck. 

Piet: No, it is a discipline process called validated learning. Entrepreneurship is actually a form of management. 

 PI: I love that reframing, 

Piet: navigating extreme uncertainty can be engineered. You can manage the search for a business model by rigorously testing your assumptions before you ever start executing on the final product.

 PI: Which leads us directly into our first major hurdle. When you have an idea, what is the very first thing you naturally want to do? You wanna go to your friends, your [00:04:00] family, your mom, and ask, Hey, do you think this is a good idea? 

Piet: And Rob Fitzpatrick's work makes it very clear that this is a terrible, terrible question, 

 PI: the absolute worst.

Piet: He refers to this as the PAOS problem, PAOS, which stands for pathological approval seeking 

 PI: pathological approval seeking. 

Piet: Yes. When you go to someone, especially someone who cares about you, and you expose your ego by saying, I just quit my job to build this app, what do you think? You are practically begging them to lie to you?

 PI: Wait, but isn't that what focus groups are for? Companies spend millions of dollars every year asking people what they'll buy next year or what features they want. Are you saying that asking people what they want is just a waste of time? 

Piet: Basically? Yes. If you ask a hypothetical question about the future, you are going to get a worthless answer.

When you ask your friends or a focus group, if your idea is good, you're putting them in a position where they have to protect your feelings or they just wanna sound agreeable. 

 PI: Right? Nobody wants to be the bad guy. 

Piet: Exactly. So they give [00:05:00] you what Fitzpatrick calls, fluffy mistruths. They say, oh wow, that sounds amazing.

I totally buy that. 

 PI: And you walk away thinking you've got market validation. 

Piet: What all you really got was a polite compliment. 

 PI: So how do you get around that? If you can't ask people, if they like your idea, how do you know if it's worth pursuing? 

Piet: What's fascinating here is how Fitzpatrick's Mom test provides a framework to bypass that social friction entirely.

It is a set of three simple rules designed to get the objective truth out of anyone, even your own mother. Even your mother who is biologically hardwired to lie, to protect your feelings. 

 PI: Okay, what are the rules? 

Piet: Rule number one, talk about their life instead of your idea. Rule number two, ask about specifics in the past instead of generics or opinions about the future.

And rule number three. Talk less and listen more. 

 PI: Let's ground this in an example from the materials because it illustrates the shift perfectly. 

Piet: Go for it. 

 PI: Imagine you wanna build a digital cookbook app for the iPad. You go to your mom. [00:06:00] The wrong way to do this is to picture You say, Hey mom, I'm building this iPad cookbook app.

Would you buy it? 

Piet: Because of course she's gonna say, yes, honey, I'd buy 10. 

 PI: Exactly. It's a hypothetical question about the future, 

Piet: right? But if you apply the mom test, the conversation completely changes. You don't even mention your cookbook idea. 

 PI: Not once 

Piet: you focus entirely on her actual behavior, 

 PI: you say, Hey mom, how's the new iPad?

What's the last thing you actually did on it? And she says, oh, your father and I are planning a trip to Italy. 

Piet: So you dig deeper, 

 PI: right? You say, did you use a specific app for that? She replies, no, I just used Google. I didn't even know there was a travel app. 

Piet: Perfect. 

 PI: Then you ask. Well, how do you normally find out about new apps to download?

And she tells you. She reads the Sunday Papers app of the Week section. 

Piet: Notice what just happened there. You didn't pitch your cookbook once. 

 PI: Yeah, you kept it entirely about her life, 

Piet: but you learned a crucial foundational fact. Your target demographic relies on physical Sunday newspapers to find software [00:07:00] not browsing the digital app store.

 PI: If you had just built the app and waited for her to organically search the app store, your premise would've failed completely. 

Piet: And what if you had asked her about cooking? 

 PI: Right? So you ask, when was the last time you bought a cookbook? And she says, oh, I haven't bought a cookbook in 20 years. I just used my grandmother's old recipe cards.

Piet: That is what Fitzpatrick calls a lukewarm response. 

 PI: I think a lot of aspiring entrepreneurs get discouraged by that. Worse, they try to start pitching harder. They try to convince the person why the app is better than the recipe cards, 

Piet: which is the exact wrong reaction. You shouldn't try to convince them.

You should be thanking them. A lukewarm response or complete apathy is incredibly valuable. 

 PI: Valuable because it saves you 

Piet: precisely opinions and future promises cost the customer nothing. I would definitely buy. That means nothing. Apathy. Apathy is a clear, reliable signal. It saves you months of time and tens of thousands of dollars by telling you [00:08:00] immediately that this customer does not care about the problem you are trying to solve.

 PI: Learning that your core assumption is wrong on day one is a massive victory. 

Piet: It really is. 

 PI: It sounds so obvious when we say it out loud, test the waters before you build the boat, but I think we have to acknowledge why this is so hard in practice. 

Piet: It's the ego. 

 PI: Exactly when you are the one with the idea, your ego is so tied up in it, it physically hurts to put the idea out there because part of you is terrified of seeing that apathy.

Innovators, and especially engineers fall into this trap all the time. They start their journey by focusing on feasibility instead of desirability. 

Piet: Yeah, so this is a major focus in the Strategizer methodology. Feasibility asks the question, can we build this right? Desirability asks, do they actually want it?

And if you prioritize feasibility over desirability, you are risking everything on a massive gamble. 

 PI: There is a brilliant case study about this involving a company called CS Imaging. Tell us about what they were trying to do. 

Piet: C'S Imaging was a team of incredibly smart engineers. They wanted to provide precision [00:09:00] agriculture data to farmers.

Things like crop health, moisture levels, that sort of thing. 

 PI: Vital data for a farm. 

Piet: Absolutely. So what was their grand idea? They wanted to build a highly sophisticated drone, equip it with a hyperspectral camera, fly it over the crops autonomously, and sell the resulting data, 

 PI: and naturally being engineers, their first instinct was to go straight to feasibility.

Piet: Of course it was. 

 PI: They wanted to prove they could stitch the software together, build the drone, and make it fly without crashing. 

Piet: Precisely. But building and testing, a custom autonomous drone is insanely expensive. It's time consuming. If they had started there, it would've been a massive waste, 

 PI: but they didn't, 

Piet: fortunately, no.

They were guided to halt the engineering and focus on desirability First. They needed to understand the farmer's actual pains and gains. 

 PI: So they actually talked to their customers. 

Piet: They went to the farmers, applied principles, very similar to the mom test, and asked about their daily operations 

 PI: and what did they find out?

Piet: The [00:10:00] farmers essentially said, we love the idea of getting that precision data, but why on earth are you building a drone? Have you seen all those crop clusters already flying over our fields every single day? 

 PI: I love that so much. The farmers basically looked at this million dollar engineering problem and pointed out that the delivery mechanism was completely unnecessary, 

Piet: right?

The farmers didn't care about the drone. They cared about the data. 

 PI: So what did the team do? 

Piet: They just attached their cameras to the existing crop duster planes that were already flying. They got the exact same data, tested the desirability of that data with the farmers, and saved an incredible amount of time and money that would've been wasted engineering a drone from scratch.

 PI: That is such a huge pivot. 

Piet: If we connect this to the bigger picture, it illustrates a fundamental rule of testing business ideas. You absolutely must prioritize your most critical assumptions first. 

 PI: The most critical assumption. 

Piet: Yeah. Yes. The one that if proven wrong, makes everything else you were [00:11:00] doing Completely irrelevant for Sarah's imaging.

If the farmers didn't care about the crop data, it wouldn't matter if they had built the most advanced aerodynamic drone on the planet, 

 PI: right? Because the core assumption was the desire for data. Not the flying of the drone. 

Piet: Exactly. 

 PI: Here's where it gets really interesting, because testing desirability without actually building the product, leads us to a concept called preto typing.

Piet: With an E. 

 PI: Yes. That's not a typo, folks. Preto type spelled with an E. 

Piet: This is a term coined by Alberto Savoia, and the distinction between the two is crucial. For anyone trying to validate an idea, 

 PI: break it down For us, 

Piet: a prototype with an O asks the question, can we make it? It's fundamentally about feasibility.

 PI: Yep. 

Piet: A preto type with an E asks the question, should we bother making it in the first place? It's entirely about desirability, 

 PI: and the whole goal of running a preto type is to obtain what Voya calls Yoda. YODA, 

Piet: your own data, 

 PI: because as we established earlier with the mom test, it is way [00:12:00] easier to get people to open their mouths and give an opinion than it is to get them to open their wallets and give you real commitment.

You need skin in the game. You need Yoda. 

Piet: There are several brilliant methods for gathering this data quickly and cheaply. Let's look at three of the most effective ones, the fake door, the facade, and mechanical turk. 

 PI: Let's start with the fake door method. This is for when you have. Absolutely zero product, but you pretend you do.

Just to measure actual measurable interest. 

Piet: A great example of this is the Justin Bieber doll concept. 

 PI: The Justin Bieber doll. 

Piet: Yes, imagine you think the world desperately needs a new high-end Justin Bieber action figure. The traditional way is to hire a designer, manufacture 10,000 of them in a factory overseas, fill your garage with inventory and then try to sell them.

 PI: And when nobody buys them, you're bankrupt. And living in a fortress of unsold Justin Bieber dolls 

Piet: a very expensive, very depressing failure. 

 PI: So how does the fake door work? Instead? 

Piet: The prototyping way is to spend a few hours [00:13:00] on a Tuesday afternoon, mocking up a really convincing website. You create a nice digital rendering of the doll.

Set a price and put a big bright buy now button on the page. 

 PI: Then what? 

Piet: Then you spend 20 or $30 running targeted ads to drive traffic to that specific site, 

 PI: and then you just sit back and watch the analytics. You measure the actual level of interest 

Piet: exactly 

 PI: how many people look at the offer versus how many people actually click that buy button.

Now, if they click buy, maybe they get a message saying out of stock or coming soon, but the data is what matters. 

Piet: The data is everything. If a hundred people visit the site and zero people click by. Your idea is dead in the water, 

 PI: but you only spent 20 bucks instead of your life savings, 

Piet: right? It forces you to measure the best case scenario.

If you can't get people to click a button, when everything looks perfect online, they certainly aren't gonna buy the real thing. 

 PI: That makes total sense. Now, the second method is the facade method. This is slightly different. 

Piet: Very different. This is when you [00:14:00] have a limited amount of the product, or you do things in a completely manual, unscalable way behind the scenes just to test if there's real consumer interest at a larger level.

 PI: Like the origin story of Zappos back in 1999. 

Piet: Oh, that's a great one. 

 PI: We have to remember the context of 1999. The internet was still mostly dial up. People were terrified of putting their credit cards online and the idea of buying shoes, something you inherently need to touch, feel, and try on sounded completely insane to most investors, 

Piet: right?

The friction was massive. So the founder of Zappos didn't go out and raise millions to build a massive automated warehouse and buy thousands of pairs of shoes in every size. 

 PI: Instead, he created a facade. 

Piet: Yes. He went down the street to local shoe stores, took photos of the shoes, sitting on the physical shelves, and just posted those photos on a very basic website.

 PI: Wait, so he didn't actually own any of the inventory he was selling? 

Piet: None of it. When a customer actually ordered a pair of shoes on the website, he would literally walk back down the street to that local store, buy [00:15:00] the shoes at full retail price, put them in a cardboard box and mail them to the customer himself.

 PI: So he was losing money on every single sale. 

Piet: Yes, but the goal wasn't to turn a profit on day one. The goal was to test the core hypothesis. Will people actually buy shoes online at scale? He proved the desirability of the premise before he ever worried about the feasibility of building a massive supply chain 

 PI: that is so smart.

And you see this method scale up to massive companies too. Elon Musk did a version of this with the Tesla model three. 

Piet: You did? 

 PI: He stood on stage with literally one. Prototype car behind him. He said, we might make this in a couple years. It'll cost around $35,000. Give us a thousand dollars deposit right now, 

Piet: and 325,000 people put real money down for a car that did not exist yet.

 PI: That is ultimate skin in the game. If nobody put down a deposit, you better believe they would've pulled the plug on that factory. 

Piet: Absolutely. Which brings us to the third method, the Mechanical Turk. 

 PI: Wait, mechanical Turk. [00:16:00] What does a Turk have to do with validating a business idea? 

Piet: It's named after a famous illusion from the 18th century.

There was this machine that toured Europe and it looked like a mechanical mannequin dressed in robes that could magically play a flawless game of chess against human opponents. 

 PI: People thought it was a real robot. 

Piet: They thought it was an incredible automaton, but in reality it was just a fake box that human chess grand Master squeezed inside manually moving the pieces with magnets.

 PI: Ah. So the modern business version is using a human being to simulate a complex technology. 

Piet: Exactly. Rather than spending months coding an automated AI driven solution, you just have a person do it manually. Behind the curtain. 

 PI: Do we have an example of this one? 

Piet: There is a great case study about this called the Josh Bot.

A startup wanted to build an AI chatbot for Facebook. This was right when chatbots were the hottest new trend. The standard engineering route would be to spend $500,000 in six months of development time to build a sophisticated [00:17:00] natural language processing ai. 

 PI: Let me guess. Instead of building it, they put a guy in a box.

Piet: Essentially, yes. They set up a fake Facebook bot page over a weekend. They invited a hundred potential customers to use it, and behind the scenes there was no ai. 

 PI: It was just Josh. 

Piet: They just had a guy named Josh sitting at a keyboard manually reading the incoming messages and typing out the replies as fast as humanly possible to make it look like an instant automated response.

 PI: That is hilarious. What happened? 

Piet: They realized their core assumptions were completely wrong. The customers didn't actually want the service they were offering. The test failed in just eight minutes, 

 PI: eight minutes, 

Piet: eight minutes, and because they used a mechanical turk to test the desirability, that eight minute failure saved them half a million dollars in engineering costs.

 PI: That's brilliant because it intercepts our default reaction of let's go make one. It forces you to prove that the solution actually solves the customer's problem before you invest in the complexities of automation and scale. Now, [00:18:00] I can hear you thinking as you listen to this. Okay. This is all great for apps and websites and digital stuff, but faking a digital bot is one thing.

You can't fake a physical piece of plastic or a real world object rock, 

Piet: right? Actually, you can. Real world physical testing is just as viable. 

 PI: It absolutely is. Consider the IKEA Val Hub story. An independent team designed a simple plastic key holder meant to attach to the wall, 

Piet: the wall hub, 

 PI: right?

Instead of manufacturing 10,000 of them trying to secure meetings with IKEA executives and negotiating a massive distribution deal, they preto typed it in the most gorilla way possible. 

Piet: This sounds like a corporate heist movie. What did they do? 

 PI: They went on eBay and bought a used IKEA employee uniform.

Piet: Oh wow. 

 PI: They created a fake official looking IKEA product label complete with a barcode and name their plastic prototype the valve up. Then wearing the employee shirt, they literally walked into a real bustling IKEA store, 

Piet: just walked right in, 

 PI: snuck their product onto a display shelf [00:19:00] right next to similar items and stood back to watch.

Piet: The audacity of that is incredible. They just observed the shoppers. 

 PI: Yes, they wanted to see in a real retail environment, not in a survey. Would people actually stop, look at this object and put it into their shopping cards? 

Piet: Did they? 

 PI: I read. They actually got all the way to the cash register before the cashiers got completely confused by the fake barcode.

But the point is, if you see two real shoppers put your fake product into their cart 'cause they genuinely wanna buy it. That isn't a hypothetical opinion. 

Piet: No it's not. 

 PI: That isn't a focus group. That is undeniable Yoda. Your own data. It is real data based on real consumer behavior. 

Piet: Okay? Faking a plastic key holder is one thing, but what if your product actually goes into people's bodies?

You can't fake a beverage. You can't just put colored water in a can and watch people drink it. 

 PI: True. But you can still dramatically reduce the time it takes to validate it. 

Piet: We see this at the major corporate level too. There is a detailed project involving Carlton and United Breweries. [00:20:00] CUB. They wanted to launch a new hard seltzer.

Normally, a beverage company might take a year or two for market research, focus groups, and flavor development. CUB went from a rough concept to a physical product on the shelf in just 60 days. 

 PI: 60 days. How is that even possible? 

Piet: They did it through rapid physical iteration with real consumers. They brought target consumers right into a test kitchen.

Instead of waiting for metal cans to be manufactured, they used 3D printed cans just to test the physical feel and weight of the product in the consumer's hand. 

 PI: And they were iterating on the design live. Right? Why? They literally had graphic designers sitting in the back room. A consumer would hold the 3D printed can and say, I don't like this font.

It feels too plain. And the designer would immediately mock up a new label, print it out. Slap it on the can right then and there for the next person. 

Piet: Meanwhile, the food scientists are in the kitchen changing the actual flavor profile live based on the feedback. Too much vodka. Okay, [00:21:00] let's dial it back for the next batch.

 PI: That is incredible agility. 

Piet: Exactly. They adopted a mindset of what would have to be true to test this today instead of why can't we do this by combining physical prototypes with immediate. Unfiltered customer interaction. They bypass months of traditional abstract market research 

 PI: and it works for physical spaces and architecture too.

Piet: Yeah. 

 PI: Look at the Boston Core flute bar story. A major beverage company wanted to redesign the physical layout of bars. 

Piet: This is a wild one. 

 PI: They had a theory that if they increased the surface area of the bar itself, bartenders could serve more people faster, which means more sales. So they designed this Coved bar shaped sort of like the top of a castle wall with full alcoves for people to step into.

Piet: But building a permanent wooden bar like that in a popular venue just to test the theory, would cost an absolute fortune, not to mention the lost revenue while the bar is closed for construction. 

 PI: Right. So instead they took over a real bar in Boston near Fenway Park and built the new bar shape [00:22:00] right over the old one using cheap temporary core flute material.

Basically corrugated plastic. 

Piet: And what did they find? 

 PI: They let real customers in for a busy, happy hour and just watched how this space functioned. And they immediately discovered a fatal flaw. 

Piet: Oh no. 

 PI: The little coves acted like traps. Customers would step into them to order a drink, and then because of the crowd pressing in behind them, they would get completely stuck.

They were unable to move back out into the crowd. The flow of the entire room was ruined. 

Piet: This raises an important question, how fast you want to fail. The people who ran that test in Boston didn't view the core flute bar as a disaster. They viewed it as a massive success 

 PI: because they found the trap early.

Piet: Exactly. They reframed failure as reducing time to data. If you know you are inevitably enough to fail 20 times to create a hundred million dollars product, you should wanna get those 20 failures out of the way as fast and as cheaply as humanly possible. 

 PI: So what does this all mean? Let's bring it all together.

The overarching lesson here is that. [00:23:00] You do not need permission to test your idea. You do not need a team of engineers. You do not need massive VC funding, and you definitely do not need a finished, polished product. 

Not at all. 

What you need is to ask the right questions, questions about people's past behavior, not their hypothetical future promises.

You need to avoid fluffy compliments at all costs. And most importantly, you need to get people to show you their real behavior through some form of actual commitment. 

Piet: Exactly. So what stands out to you? In all of this, I want you to think about your own backlog of ideas. Maybe you have a spreadsheet full of them on your laptop or a notebook sitting in your desk drawer.

 PI: We all have that notebook. 

Piet: Are you avoiding testing them because you are secretly terrified of getting a lukewarm response? Remember discovering you are wrong. Early is not a defeat. It is the ultimate competitive advantage. It frees your time and your capital up to go find the idea that actually works.

 PI: Here's a final thought to mull over before we go. [00:24:00] What if the biggest risk to your next big project isn't that you lack the coding skills or the marketing budget or the team to build it? 

Piet: What is the biggest risk? 

 PI: What if the absolute biggest risk is that you will execute perfectly on something that absolutely nobody wants, and maybe.

Just maybe we use complex engineering to build these massive, elaborate products simply because we're using all that work to hide from the vulnerability of real human rejection. 

Piet: Wow. That is definitely something to think about. 

 PI: How can you design a test for your great idea tomorrow morning for exactly $0?

Piet: Good luck out there. 

 PI: If you got an Aha moment out of this deep dive, do us a huge favor. Send this right now to a friend who has been sitting on a business idea but hasn't tested it yet. You know exactly who I'm talking about. They need to hear this and drop a comment below. Tell us which prototype method you're gonna use first, the fake door, the facade, or the mechanical turk.

Thanks for diving deep with us today.

That's a wrap. SC believers, you just experienced the power of AI [00:25:00] driven business insights with PI and PI 2.0. Real advice, artificial voices, unlimited potential. If today's episode sparked an idea, challenged your thinking, or gave you that breakthrough moment, don't keep it to yourself. Share it with a fellow entrepreneur who needs to hear this.

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Until next time, keep moving forward, keep taking action, and we'll see you in the next episode.