[MUSIC] So, it's my real pleasure today to introduce Rob Fitzpatrick. Rob is the author of a wonderful little book. This little book, which I think ounce for ounce has more packed between its covers than almost any book I've ever read. Rob welcome. Thanks for being here. >> Thank you so much for having me John. >> So I going to read this subtitle of the book here. And then I want to ask you about this provocative statement. The book is titled, The Mom Test. How to talk to customers and learn if your business is a good idea when everybody is lying to you. Why do they lie to us Rob? >> I think the big mistake of talking to customers is we go we asked them and we'll say hey I've got a business. I've got a product. I've got an idea. What do you think? We feel like we're asking for feedback right? I'm being scientific. I'm talking to my customers. I'm learning. But in reality there's two big reasons we get lied to. The first is the, this way of asking about our idea, about our business, it exposes our ego. And I was saying, I built this thing, I love this thing, I'm so excited about this thing, what do you think about it? >> And how could they say no? >> Yeah, it's very difficult and you know, no one wants to make you cry and some people say they hate every new idea, some people say they love every new idea but either way you're not getting good data, right, you're getting their opinions. So that's a huge mistake, it's just exposing our ego. And the second is that we ask for people's opinions. And an opinion is not real data. No matter how honest you're trying to be about my business, the truth is you can't see the future, you don't know. All sorts of crazy ideas end up turning out to be great and vice versa. Even Venture capitalists, investors, they're the best in the world at this. They're still wrong. >> And they're not very good. [LAUGH] >> Yeah they're wrong one time in five, or sorry they're correct one time in five. >> If that. >> Yeah, so how much are you going to value anyone's opinion. It's quite fluffy. It's not real data. >> So you say there's an alternative to that? >> Yes. >> Would you describe it please? >> So when we ask people about our idea and the reason the books called the Mom Test, we say, hey Mom, I got an idea for a business, what do you think? She goes, It's amazing, you're so smart. That's a compliment. That's an opinion, it's not real data. But if we ask the questions differently, if instead of asking about our idea, we ask about her life as a customer, we can learn a lot. So if we're building an iPad app, >> So, Mom, >> Yeah, we might say, so, mom, you have an iPad. How do you like it? She says, I love it. We say, which apps do you use? How did you choose those apps to purchase? Where did you find out about them? Which apps have you deleted? What else have you tried? We ask about her life as it already is in the past. We ask about our customer's lives. We don't say would you like an amazing travel planning app? We say the last time you planned a trip. How did you do it? >> How did you do it? >> What did you search for on Google? Did you look for an ad? Did you hire a travel agent? Like what else have you tried? How are you dealing with it today? And then we get facts about their lives and we can make our own decisions as an entrepreneur. >> Mm-hm. So you want data here. Evidence. Rather than fluff and opinions. >> In an ideal world, yes. >> Yeah. >> It's not always possible. If you're building a video game, for example, it's very difficult to get good information. You can't say hey, do you like having fun? Would you like to have more fun? You're not going to get much. You can learn more about how people decide which video games to buy. You can learn pieces of it. But ultimately in that case you need a prototype. You need something to put into your customer's hands to see how they actually engage with it. And that's more true of consumer apps. With consumer apps, you need the prototype a lot earlier to keep learning. With business-to-business apps, you can learn a huge amount just by talking to people and asking good questions. >> So in this wonderful little book there's a chapter on avoiding bad data. Would you explain how that works? >> The biggest bad data is compliments. Compliments and opinions. And yes, you avoid that by just talking about their life instead of your idea. Another type of common bad data. Is what I call Fluff or Hypothetical Promises about the future. So, you say, hey John. >> What if? >> Yeah, what if you have this? Would you ever use a product which did this amazing thing? And you think and you go, well, I might, someday. Yeah, I could definitely see myself using your products like this. So now, your customer who you're talking to, they're imaging this alternate future, and like, yeah, I might definitely use that. But that's very different, that's an opinion. A fluffy hypothetical about the future. That's very different than a commitment to actually purchase it. And the best way to break through this type of data is you just ask them for a commitment. You ask for a bit of their reputation. >> Like a check? >> A check is the best case. If you can ask for money, do it. It's great, even though it's scary. If your product's not so far along, you might ask for some reputation. You say, hey would you introduce me to your boss? Would you introduce me to your co-workers? Would you write a public testimonial about the product? Or you could ask for their time. You know, will you seriously commit to give this trial a real attempt for 3 weeks? So you ask for something they value and it kind of cuts through these hypothetical, I might, I would, I will. And it gets concrete, yes, I'm committing, I'm serious. >> Hm-mm. So there's a process here by which this learning about customer behavior and what they really do today unfolds. How do you translate what that person tells you with what they're doing today. Into to what you're hoping they would do tomorrow. >> I think this is both the hardest part of it and it's also why businesses are still built by people and entrepreneurs, instead of built by robots There's a sort of visionary leap, there's something you have to figure out as a founder. You can learn about your customers and the way I think about it is having good information about my customers that gives me firm footing. It's a foundation of customer understanding. But then from this foundation I still need to take a leap myself to a solution to a product. I go, okay I understand and I think this what will fit in your life. You're not just saying what should I build you? Give me a list of 10 features and I'll implement them. Building stuff by focus group, by survey just doesn't seem to work. >> No. And so when you take that leap and build a product, ideally you build as little as possible, you know that you can figure out if people want it or not. You don't spend all your money on it. You try to put little pieces to move our learning forward. But you might be wrong, you know? You've learned about your customers. >> In fact probably you're going to be wrong. >> That's a better way to [CROSSTALK]. >> At least in part. >> But that attempt it gives you further information, and now you've got your understanding about the customers, and you've got some data from a product, and you can start combining these, and stepping forward. And it goes pretty quickly. And soon you're like I'm getting somewhere. People are excited, they really care, there's a budget attached to it. I can make some money. This might actually be a business. >> So all this makes good sense, yet most entrepreneurs skip all this stuff, right? Why? [MUSIC]