The SURPRISING Reason Businesses Fail

In this video, I want to talk about one of the most underrated problems that you will face when trying to start a business. And the best way to explain this is to do a review of a book that I read years ago. Back when I first started my business, this book was trending and quite popular at the time. And I think I made it around 60% of the way through the book before it got a bit repetitive. The book strongly emphasizes the importance of only building the simplest minimum viable product that you can and then using user feedback and empirical data to develop the product further. If you read through this book, you may find yourself getting quite excited because the way that the book lays out the process of building a business iteratively seems so simple. But from having tried to apply some of these concepts, I can say that it's not quite that easy. To be more specific, I'd say that one of the major problems is that the bar for what qualifies as a minimum viable product has increased substantially over the years. Many of the ideas that worked in the 1990s or early 2000s don't work anymore today. And if they do, they're substantially harder. To start with an example, let's say that you want to build an online store that sells products. And because you just want to make money, you don't have any particular conviction about what type of product you sell. So, you decide to apply the lean startup mentality and simply set up the minimum store that you possibly can to gain data about which type of product will sell more with the intention of doubling down once you know which product will sell better. And so, you spend a couple hours and set up the most basic website that you possibly can. Then, over the course of the next week, you get absolutely no sales or visitors to your website. And once you realize how difficult it is to get organic traffic when starting from scratch, you decide to buy some. And so you decide to spend $300 on Google Adwords to try and get a bit of initial traffic. But then $300 later, you still have zero sales. So now you're out $300 and you still don't have any data and you wasted time setting up a website that doesn't really get any traffic. And if you're trying to start up a new business, this is the most likely outcome for you. And unfortunately, the lean startup model doesn't really say much about what to do in this situation. Maybe you should just stick to t-shirts and try out different designs. Or maybe you should experiment with different designs of water bottles. Maybe you need more products in your store. Maybe your prices are too high. Maybe your prices are too low. Maybe you should focus on content creation first. The possibilities are endless, and the amount of time that you can waste trying to optimize something that doesn't matter is infinite. Building a business can be thought of as a search problem. And if you're not efficient at navigating the search space, you'll go out of business. In summary, the core issue that you will face is the difficulty of trying to collect a statistically significant enough amount of information. To even make good business decisions in the first place. To collect data, you have to run experiments. But even simple experiments cost time and money. And if you don't collect the information fast enough, by the time you figure out your business model, the world may have changed and it might already be obsolete and not work anymore. And for experiments like this one, not getting any sales is probably the best case scenario. Years ago, I tried an experiment just like this one. I set up a couple very simple product pages on a website to test out some business ideas. I bought some ads to drive traffic to these pages, but very soon into the ad campaign, my ads were disabled. The reason that was given was that the quality of the pages was too low. So, of course, to continue the experiment, I had to put more time and effort into improving the pages and made sure that they comply with all the terms and conditions of the ad network. In the end, I never actually ended up getting enough data to convince me to pursue either product idea. If you've ever done any kind of online marketing, this experience of being banned and limited is something that you're probably familiar with. Over time, all of the different payment processors and advertising networks have been getting increasingly aggressive at banning people. Sometimes this is due to legitimate reasons like not specifying terms and conditions or having confusing shipping information. But many times the real reason that you get flagged or limited is not always obvious. Most of these decisions are now made by artificial intelligence that constantly gets things wrong. Even as I speak right now, all of the products in my online Shopify store are currently disabled in my Google Merchant Center account. The process of setting up and configuring the Shopify account requires specifying a lot of information about shipping and other things. And all of the information that I specify has to match what's included on the website and in Google Merchant Center. During the setup process, Google Merchant Center recommended that I change the return window from 30 days to 90 days. So, I simply went ahead and followed the recommendation in the settings. Unfortunately, I forgot to update this return window number on the actual store web page, which was still out of date and indicated 30 days. This is just one of the things that Google Merchant Center flagged in my online store. I've since fixed this issue, but unfortunately, after two appeals, all of my products are still disabled due to so-called misrepresentation. At first, you may find issues like this one frustrating. But if you decide to start a business, you will face issues like this constantly, and you'll eventually get used to it. To give you another example along the same lines, this is another product that I once tried to sell in Facebook Shop. Back when Facebook Shop first came out, I didn't really think much about it, but I kept getting notifications in my business account aggressively asking me to try it out. So, I decided to test it out with one simple product, which was my regular expression laptop stickers. Almost immediately after creating the product entry, I got a notification saying that the product was rejected and it wasn't a good fit for the platform. Issues like this one are a very common occurrence for small businesses that don't have a lot of reputation. And this is despite the fact that platforms generally require you to verify your business and upload your personal identification in order to create a merchant or advertising account. I've also experienced similar issues when using Facebook's advertising platform as well. One time my ad account was banned for seemingly no reason. After doing a bit of Googling, I saw a whole bunch of other people reporting the same thing. A few days later, my advertising account was mysteriously reenabled with no clear explanation of why. Having said this, I do think that there are valid reasons for disabling the accounts of lowquality merchants. And since all of this automatic disabling and account banning is done automatically by algorithms, it's extremely important to make sure that your account is in good standing. Things like making sure that your terms of service, privacy policy, shipping policy, return policy, European Union privacy standards, cookie consent forms, and all of the other necessary legal disclaimers are in good order. If they're not, you might find yourself randomly banned. And the worst part is once you get banned, they probably won't tell you why. and this will make it very difficult for you to fix the problem. To give a bit more context on my advertising experience, I would say that I've probably spent around $6,000 or so on various ad platforms over the last 10 years. During that time, I did a lot of experimentation of many different types of ads on different platforms. Unfortunately, I was never actually able to profitably make sales off of an ad. Instead, I eventually shifted my advertising strategy to targeting events that were higher up in the conversion funnel. I did see what I viewed as a little bit of success with lead generation ads on Facebook. Having said this, with the benefit of hindsight, I think that my core issue is that I just didn't have enough money to run the adsets with a high enough volume and frequency to get a statistically significant enough amount of data to make the adsets profitable. So this brings up an important question and that is how much money do you have to spend on an ad before you know if it works or not. Now statistics can get very complicated but a fairly widely used rule of thumb is 30 samples to get close to statistical significance. So given this number of 30 samples the next question is how much profit do you make per product? Let's say that the product sells for $45 and $20 of that is profit. So you have 30 samples times $20, which is $600 in gross profit. Now, I can say from experience that breaking even with your ads is a very significant accomplishment. And by breaking even, we mean a scenario where the advertising cost is equal to the gross profit on the products. So $600 in ad spend to generate $600 in gross profit means you're breaking even. And if you can do that with 30 sales, you can now say that you can break even with fairly good statistical significance. And even though breaking even might not sound like a significant accomplishment, the key is that experimentation is now free. If you can find even a tiny change that you can make to your ad or your product to make it sell better or make it more profitable, you'll be making money and you can just continue dumping more money into ads. But what about the other case? What if you don't make 30 sales after $600 in ad spend? Well, you just lost $600 minus 20 times the actual number of sales. And if you're losing money, you can only do that for so long until the universe forces you to give up. But then again, if you're losing money, this specific ad might not be good enough. Maybe you should take another picture. Maybe you should make a video. Maybe you should do more content marketing. And this is another area that highlights the psychological difference between marketing and software engineering work. I think that a very underappreciated view of entrepreneurship is a comparison to gambling. If you're trying to make money with ads, it's very easy to say, "Well, let's just try another ad type. Let's try another campaign. Let's make another video." At some point, you're going to have to call it quits. But no one will tell you when. And finally, I think it's also worth considering the cost to the customer in this experiment. If the product cost is $45 and the goal is 30 sales, the total spend by the customer for this experiment is $1,350. All just to show you that you can break

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