The Startup Story I Want To Hear
whattofix.com
whattofix.com
In 2006, I quit my job to work on it full-time.
In 2007, my co-founder and I finished the MVP. No one came.
In 2008, we got a big break and it was used by 4 million people.
By 2010, 10,000 companies and 6.5 million people were using it, but we still weren't profitable.
In 2012, we finally figured out a business model.
This past Thursday, 8.5 years later, I got to show it to Barack Obama in front of the national press: http://www.whitehouse.gov/blog/2013/05/10/recap-big-day-open..., and he mentioned it in a speech later that day: http://www.youtube.com/watch?v=2glCSMxXIF8#t=11m7s
We're on the verge of several deals that could take us to profitability with a headcount of 6.
It's been an insanely difficult road. I think there are many reasons for that, but here's the chronicle:
http://wensing.tumblr.com/post/1215873671/bootstrapping-stor...
http://wensing.tumblr.com/post/26830276239/bootstrapping-sto...
Part 3 should be out soon. :)
+1. Even though @jstanley is correct about the latter quote, I do agree that most start-up stories are dominated by these fantastical circumstances and ridiculous buyouts. I think there are primarily two reasons for this:
1. Retention (or lack thereof) in the start-up world
2. The success bar
As far as (1) is concerned, I think why we don't hear about people that try, try, and try some more for many years is that once you reach a certain age or once you have kids, you can no longer afford to live on Ramen noodles and Ritz crackers. If you fail once, twice, or three times, it really is very very difficult to try again. Even tough you've (hopefully) gained some valuable lessons by failing, you've lost (a perhaps disproportionate amount of) resilience. Thus, you're much less likely to try again.
(2) is moreso culture-dominated than rooted in the real world. As far as I'm concerned, I'd consider myself "successful" if I launched a 1-person start-up and sold it for mid-to-high 5-figures. That's not even close to "Facebook successful" and maybe my success bar has been lowered since I've failed a bunch of times, but most of these books/interviews/talks are written/given by people that have had outstanding exits. No one wants to talk to the tiny 2-man studio that built a company and sold it for $300k (even though I would argue that's a successful exit).
Can look at an information technology startup essentially the same way. A great example is the Canadian matchmaking site Plenty of Fish -- long just one person, two old Dell servers, ads just from Google, and $10 million a year in revenue.
There are some advantages to an information technology startup: First, if connect a server to the Internet and keep it busy sending Web pages with ads, then at common ad rates will get the five figures a month in revenue. E.g., send two Web pages a second, send an average of four ads per page, get the charge per 1000 ads displayed (CPM) average of $2.125 in the KPCB Meeker report, and then get monthly revenue of
2.125 * 4 * 2 * 3600 * 24 * 30 / 1000 = 44,064
If the usage keeps growing, fine: Get more servers. Else, the $44 K a month will do fine for providing for a family.
Moreover, most of the work is just learning the coding skills, e.g., in the Microsoft world, .NET, ASP.NET, ADO.NET, IIS, system management and administration. Then if the first Web 2.0 site flops, use the skills to bring up another one.
But, it might grow, especially if it was carefully planned to from the beginning to grow. So, then, let it grow.
Any questions?
Where do you plan to get your 5 million PV's per month?
So, for a first answer to your question, have to 'plan', that is, think of a Web site that can attract that much traffic, at least from publicity, viral effects, other network effects, happy users, etc.
How to do that? Well one way is just to think of a 'business idea' (John Doerr said that business ideas are easy and plentiful; bad business ideas are; maybe good ones are more difficult and rare!), develop a prototype, use 'lean' methodology and/or the Steve Blank approach of continually 'iterating' with the customers and revising the prototype to achieve 'product/market fit', 'pivot' if this doesn't work well, and keep trying.
I have another approach in mind borrowed from project planning examples going back over 100 years. A joke version is, a good recipe for rabbit stew starts out, first catch a rabbit! More seriously think of what one venture partner calls a "big ass" problem. I would add detail: Want a problem that is 'big' in the sense that we are sure that the first good or a much better solution will be a very valuable 'must have' and not merely a 'nice to have'. To keep risk down, want no doubt about this. If there is any doubt, pick another problem. Another local, mobile, social, sharing app has too much doubt. Similarly for another 'social graph' recommendation site. From all I can see, mobile payments also have too much risk from regulations and need for 'critical mass'; if try this, then be ready to jump quickly on the first good acquisition offer.
The obvious example of such a "big ass" problem, although not from information technology, is a safe, effective, inexpensive, patentable one pill cure for any cancer. Then don't have to worry about 'product/market fit'. Instead, a sad reality and not at all a joke, have to hire security guards to keep desperate customers from breaking down the doors to the lab and trying to steal the pills. Why don't we have such a pill? No one knows how to make one. But the first person or group that figures out how to make one and patents it will have a low risk, first good or much better very valuable solution and a very successful business.
So, right, we are getting a hint: For the success we want, it might help to do some original research!
So, for step (1), think of a suitable "big ass" problem.
Step(2). For this "big ass" problem, want to find the first good or much better solution that will clearly be a very valuable 'must have'. For the very valuable part, in part want a barrier to entry. For a cancer pill, could use patents. For information technology might use Fred Wilson's "large network of engaged users" (but apparently now he is moving into mobile payments instead!), a network effect (everyone uses it because everyone else uses it, e.g., LinkedIn; nice to have; usually tough to get started), a brand name, etc. Or have a technological barrier to entry, that is, have a solution too difficult to duplicate or equal. The common claim that there is nothing new to permit such is just not true. Uh, the technology might be original and not on the shelves of the research libraries -- right, that's commonly called 'research' and venture capital won't fund it, evaluate it, review it, or even think about it and instead will throw it into the bit bucket because their backgrounds in bizdev, marketing, and selling made them afraid and jealous of it; also they want always to be "the smartest guys in the room" which raises a risk of the other guys not being smart enough to make money!
So, to get this solution, do something different for recent information technology entrepreneurship but nearly standard for much of engineering going back over 100 years:
For our step (2), faithfully convert the real problem into a mathematical problem, e.g., as in the applied mathematics in each of most of the fields of engineering.
E.g., notice that the wings don't fall off Boeing 747 airplanes. Why? A major part of the reason is the applied mathematics of mechanical engineering.
So, from our step (2), we now have a clearly stated mathematical problem.
Although we are in information technology, notice I didn't say we have a computer science problem. We're talking applied math, complete with theorems and proofs and possibly with some advanced pure math prerequisites, common in engineering going back over 100 years, e.g., to Maxwell's equations, but recently rare in information technology startups.
Step (3). Get a solid mathematical solution to the mathematical problem. Have two advantages here: (A) Generally it is relatively easy to check such math for math correctness. So, get lower project risk. (B) The math approach can yield solution techniques more powerful and too difficult to think of otherwise. So, get a better shot at the first good or much better valuable solution with a technological barrier to entry.
Step (4). Write software to do the data manipulations specified by the mathematical solution. There are two advantages here: (A) The math really should provide a precise, usually succinct, specification of what the software needs to do. E.g., we are not trying to write an 'artificial intelligence' application based on, say, 'rules' and Forgy's RETE algorithm where have to keep 'tweaking' the rules until they appear to work, i.e., keep throwing the software against the wall to see if it appears to stick. We don't have to keep trying maximum likelihood estimation of 'machine learning' to see if it appears to stick. Similarly for neural networks. Instead, if the software just does the data manipulations specified by the prior math, then likely the software is essentially correct, has done its job. So we lower project risk. And such software tends to be easier to write than the common, elaborate user interface software. (B) Such software is relatively easy to check for correctness because of the fundamental advantage that we have a precise, and usually succinct, specification of what the software is supposed to do (the lack of such a specification is the main problem in establishing software correctness).
Step (5). Deploy the solution. Get publicity. Likely have built into the problem specification that want a lot of virality.
The steps (2) through (4) typically are challenging and high risk. But there are two advantages: (A) Typically these steps can be done essentially just on paper, e.g., as an applied math Ph.D. dissertation or engineering project planning document. And, as for most applied math research, the work usually needs just one person. So, the cost, 'burn rate', is low. (B) The work, the applied math and software, are relatively easy to check for correctness thus lowering project risk.
If can't get through the fourth step, then return to step (1) and another problem.
Back to step (1), picking the big ass problem: Here definitely want no doubt. But 'social' is not well understood so that for highly 'social' applications we will usually have too much doubt.
More generally this 'way' of doing projects won't work for all projects and would not have worked for all successful projects in the past. Right. But the intention that, once step (4) had been completed successfully, the 'way' gives high financial return at low risk for an appropriate project and enough, broadly, to get the business progress we have in mind.
So, that's the plan to get the page views!
Great insights there.
You need to read again. What's there is great stuff, far beyond what you described, that I largely borrowed from the past 100 years of engineering and technology history.
The bottom line points are: Getting through step (4) is comparatively cheap, when can do it. So, didn't spend much money. Then in step (5) get to deploy a solution that has high promise of big financial gains with low risk. That's not good news?
The 'secret' is that by the time get through step (4), really have something valuable. So, well before launch or traction, are quite confident will get major success. That's big, huge stuff.
There are many examples from the past 100 years. Now, note, that after step (1), steps (2)-(4) are just technical. So, we want to know if my claims for those steps are supported by history. Well, for an example, at one time the US wanted to do photo reconnaissance of the USSR. We tried the U-2, but it flew too low and too slow and got shot down. So, Kelly Johnson proposed an airplane that would fly at Mach 3+, at 80,000+ feet, for 2000+ miles without refueling, be relatively difficult to see on radar, and not get shot down. His design and proposal were essentially just on paper. The project was approved, and he delivered as promised. So, the lesson is, really can remove nearly all the technology risk just by work on paper.
Then with the 'big' problem as in my step (1) and solid technical work in my steps (2)-(4), enter step (5) in really good shape. This is good news. Sorry you don't see this.
If you want to insist, just insist, against all evidence keep just insisting that the usual wildly unpredictable, super high risk work of Silicon Valley venture funded information technology startups is just the best possible with all the risk necessary and impossible to remove, go ahead.
http://www.nytimes.com/2008/01/13/business/13digi.html?pagew...
At no time did I conclude that his project was either "overnight success" or "zero effort".
But I can understand the point of just one guy: A founder really should understand his business. So, that takes him into all the relevant topics in computing and outside. That's a lot of topics.
My main points about Plenty of Fish were just as I explained, and I never claimed either "overnight success" or "zero effort".
A few choice quotes from the first few paragraphs:
He developed software for his online dating site, Plenty of Fish, that operates almost completely on autopilot, leaving Mr. Frind plenty of free time. On average, he puts in about a 10-hour workweek.
Mr. Frind built the Plenty of Fish Web site in 2003 as nothing more than an exercise to help teach himself a new programming language, ASP.NET.
No mention of long hours promoting, begging users to sign up, tracking down weird bugs, or all the actual work that goes into building a business. Just a quick rundown of how easy it is to whip up a shitty website and become a millionaire overnight.
Now that you mention the claim of a 10 hour work week, I believe I did read that, but I didn't remember it or pay much attention to it because it sounded to me like just media fluff to 'tell a good story'.
Media fluff aside, there's no doubt that PoF is a good example of what was for a long time just one guy, two old Dell servers, and some nice revenue. So, such a thing, not the 10 hour claim, is possible. That's all I wanted from the PoF example.
Not to nitpick, but by looking at startup stories you're not likely to hear that. That sounds like more of a Small Business story to me.
The problem with long-term stories is that they're usually boring until the business sells or dies.
"Let's start with a distinction that should be obvious but is often overlooked: not every newly founded company is a startup. Millions of companies are started every year in the US. Only a tiny fraction are startups. Most are service businesses—restaurants, barbershops, plumbers, and so on. These are not startups, except in a few unusual cases. A barbershop isn't designed to grow fast. Whereas a search engine, for example, is."
A barbershop is a great example of a small business. A barbershop is obviously different in nature from a search engine because it's not designed for rapid growth.
Just look at Instagram -- it was created by some guy fishing for a way to game the system, and lo and behold, it worked out for him (after failing with some ridiculous whiskey startup idea). What Zuckerberg did for Instagram was self-serving charity: he essentially used a billion dollars worth of capital to perpetuate the startup bubble (think of how many MBAs are going to flock to California now hoping to become the next Instagram), which only helps Facebook in the long run (once the bubble pops, no one's going to be buying ads from them anymore).
Any reasonable businessperson would see a company like Instagram for what it is: a server with some data on it. UI? Number of accounts? That's all irrelevant: the revenue was exactly $0. Even SEO scammers selling private label goods off of Ali Baba are more financially viable than them!
The problem of defining 'what a startup should be' is that you end up in a situation analogous to a doctor treating a patient's symptoms rather than the underlying disease. The idea that your company needs to have explosive growth and be reachable by x number of people and have a valuation y dollars means that the CEO is usually running around spamming his product everywhere, taking out huge numbers of ads, and schmoozing with VCs instead of doing what he should be doing -- developing a financially viable product that customers want to use.
I think you mean technical person, because a business person saw them correctly and acted accordingly: a threat (and this is all about growth, and this is the reason of separation between startups and regular companies).
What you described (long-term sustainable growth) is the hallmark of a good small business. And there is nothing wrong with that! But it is a very different model from what we know as a "startup". After all, if "startup" could mean any small company, there would not be any reason to have the word at all! We could just say "small business" instead.
The two models are very different in every way apart from the size of the company. Having different words for them just makes sense. It's important not to see this as some judgement on either concept; rather, it's just using language to differentiate between two fundamentally different things.
I love the tech I see on HN, but I don't relate at all to the obsession with acquisitions, venture capital, workaholism, and status seeking.
The Micropreneur Academy forum is probably the closest thing we have at the moment.
And the vast, vast majority of startups do end up like that, not in a buyout or such.
I think I wouldn't call that a successful startup. When someone says "startup" to me that inherently means the seed of a large business. A software consulting business isn't a startup in my book. Even Bingo Card Creator, though it at least has the technological leverage, is in too small a space to really be a startup.
Selling out early or late doesn't change it, and if they transition from startup to small-medium sized business somewhere along the way, they could have been a startup that had a best case failure, but they would cease to be a start up. I'd worked at one of the latter. A good indicator is when you are given 65k stock options ... at a penny a share.
I'm sure that's a valid pitch. (And I'm sure the BCC has made more profit that most companies who pitch something like that)
April 2009, I quit full time, start working 20 hours a week, and work on the startup 40-50 hours/week
2009-2011, continue working on startup full time, with occasional part-time contracting (less than 40 hrs/mo).
March 2011, my cofounder quits, I give up soon afterwards. We had zero revenue, zero traction, and no plan.
I screw around with a couple of ideas, and try to understand how we wasted the last 3 years.
I contract some more, realize I can't go back to big corporate life, and start another startup. This time I decide I'll do something "easy", with a clear path to revenue. We're going to charge people early. First line of code gets written in September 2011. We have beta users in December 2011. We turn on payments in April 2012. We sign up 14 paying customers in the first month.
We grow steadily, and raise $1.5M in December 2012. There are now weeks that where we add more customers than we did in the first few months. We'd be profitable if we stopped hiring.
It's been incredibly difficult, stressful and tiring. You need tenacity, but not too much, as my three-year wander in the desert showed. You need to not give up in your goal to be successful, but be able to give up on individual strategies.
You need people to support you, and you need to repay their support. My then girlfriend, now wife nearly left me several times because early on I didn't know how to handle the stress, and I didn't know how to unplug and have a nice night to repay her for putting up with my stress and inattention for the rest of the week. I don't think I could be successful without her.
My complete failure on the first startup was caused by not having a clear plan for how the startup was going to succeed. We should have done a better job identifying who the customer is, how we were going to charge them, and how we were going to reach them. Additionally, the first startup had large amounts of technical risk. (It was using some advanced machine learning, when neither of us started knowing machine learning).
I'd call myself a machine learning expert now, but that definitely wasn't the case when I started. There's a saying, "in machine learning, you learn, and the computer doesn't".
The other major failure was that we didn't evaluate our progress, in terms of business metrics. Each month the product got better, and we understood the algorithms more, but no progress was made on traction of any kind, or customer development. You should read Lean Startup before you write a single line of code in your startup. We should have given up after 3 months, or even a year of no progress. Instead we wasted 3.
Unless you're curing cancer, all startups have market risk. For first time entrepreneurs, I'd recommend against things that have both market risk and technical risk. And if you have technical risk, you'd better be an expert at it, before you start.
I can't second this one enough. Our startup heavily involved video recording, which I thought was a solved problem. It turned out not to be at all.
I ended up learning a lot of really cool stuff about Flash's crazy edge case bugs (I should attach a microphone to a connection with a null hostname to get the activity levels? Sure. I should wait with attaching a camera until I've detected a greater than 0 activityLevel? Sure. I should sample connection speeds and run a regression analysis on that data to find the right bandwidth/quality settings? Cool, but seriously?) and the various flaws of the media servers out there (So I don't have access to the packet stream with Wowza, but in Red5 I need to rewrite the way audio and video packets are interleaved because when uploading high quality video on slow connections Flash delays video packets until the end of stream? No problem.)
In the end even though our startup wasn't about video but about interacting using video, we spent 90% of our time on the video part. That's a lot of energy I wish I could've spent on building the business instead.
I got into entrepreneurship because I was scared of having a life where I just made a living. I feel like there's something great inside me. I haven't fully tapped it, but it's there and I want to learn how to express more of it.
I felt alone for most of my life because most people are like Daniel, they just want to make a living. I never felt like there was anything wrong with them. Hell, they're normal. I felt like there was something wrong with ME for wanting more. For feeling like I can do something extraordinary.
Doing Mixergy interviews reminds me that I'm not odd. Or at least that I'm not the only one who's odd. My interviewees and my audience are like me. We want something more. We're learning from each other about how to do it.
Most people reading this can't relate to that. It's fine. Striving to 'Just make a living' is incredibly honorable and I hope you find the site that tells those stories.
I hope there's one person out there who gets it. If you're reading this. I'll see you on Mixergy.
Then you have the last group that tried everything and failed to know what that one thing is that could work.
You just have to wait.
I've been at this for twelve years, since I was in my teens. The struggle stories takes time to mature for that redemption.
His story culminates in presenting to President Obama this past week @ the Capital Factory (Austin, TX). Great guy and a story that has definitely inspired me.
The author is asking for stories about the long slog of an eventual breakout success of a scalable startup.
Always profitable, even through the doldrums. Decent (seven figure) pile of cash in the company account. Moderate pile of cash in mine.
Still have no idea what to do with it. It's a byproduct of creation.
I suppose this pointless little anecdote intends to shed light on the fact that we're not all in it for the money, and therefore not all stories are the same.
Some of us just need to struggle.