Archive for September, 2009
The Geek Squad: Brilliant Marketing
Posted by Jeff in entrepreneurship on September 24th, 2009
Robert Stephens was brilliant at marketing, and that made him an incredibly successful entrepreneur.
In the autumn of 1998, Stephens came to my high school to speak to my entrepreneurship class (a course which I forgot to mention in my previous post). He came in uniform: black slacks, white short-sleeve dress shirt, black tie, and cast-metal badge. He looked every part the geek, which was appropriate, since he was the founder and owner of the Geek Squad.
Prior to the sale of the company to Best Buy in 2002, the Geek Squad was an independent IT consulting and on-site repair service operating in the Minneapolis area. The Geek Squad agents — the computer techs — were known for technical prowess, attention to detail, and customer service. Of course, there were but a few dozen agents in the company, and the Geek Squad was but one of many firms in the area providing computer services, so skills alone might not have been enough.
What set the Geek Squad apart? Competence and marketing.
Competence #1: Hiring — Stephens hired only people without certifications (e.g., MCSE or A+) to be techs. His logic was along the lines that the most competent people would be passionate enough to be self-taught, and those people wouldn’t bother with certifications. They got the job done quickly and correctly.
Competence #2: Reputation — Robert was a frequent guest on local TV news shows, where he discussed technical issues making headlines around the country, such as the latest computer virus or web breakthrough. And the caption below his face? Always mentioned his company. Off camera, the Geek Squad was known as the go-to group for emergency computer service. When national music acts were in town and were having trouble with their computers, the promoters referred them to the Geek Squad.
Promotion #1: The Cars — The old Geek Squad used restored cars from the 1940s and 1950s, painted black and white to resemble the police cars of the era. The old squad cars were quite a sight, but to make sure people were actually looking at the cars, Stephens had the tire pressures set artificially low and told his agents to take corners extra fast, thus ensuring large amounts of attention-getting tire squealing.
Of course, 50-year-old cars with squealing tires don’t scale well, but Robert wanted the replacement cars to continue to have some cachet. The solution? Black-and-white VW “new” Beatles. Also, modern cars (and particularly electronic fuel injection) are much more user-friendly in the harsh Minnesota winter.
Promotion #2: The Business Cards — Most business cards receive a quick glance before being tossed or forgotten. To ensure a longer life for the Geek Squad cards, Robert had them die-cut into ovals, making the card look like a perfect physical copy of the logo. On the reverse side, he included a number of helpful computer-use tips of the type that would encourage people to keep the cards near their computers. Then, when trouble would strike, the tip-laden card — and the company’s phone number — would be close at hand.
Promotion #3: The Name — Let’s face it, “Geek Squad” is both catchy and descriptive. Who knows computers? Geeks. What group do you call when there’s a problem? A squad. Brilliant. An added bonus of being memorable and descriptive is that it was often easier to remember the Geek Squad’s name than that of competitors. Apparently, on more than one occasion, a person called 411 looking for computer help with only a vague sense of the name of a competitor — say, the Repair Nerds. “Geek Squad” was such a powerful brand that the caller latched onto it instead of the original target company.
Promotion #4: The Uniform — Stereotypes can be used to one’s advantage, as shown by the Geek Squad uniform. I don’t recall Robert wearing taped black plastic glasses, but everything else was there, straight out of the 1950s: black slacks, white short-sleeve dress shirt, and narrow black tie. On top of that, since they were agents in a squad, they carried genuine-looking cast-metal badges. Stephens even went through the trouble of getting the badges made by a company that makes real law-enforcement badges. Details matter.
Was the service offered by the Geek Squad vastly superior to that of competitors? Probably not. It was very good, but equal service was available elsewhere. What set the Geek Squad apart from its competition was its brand: catchy, consistent, fun, and extremely well-executed.
In fact, one might argue that the service in the current Best Buy-operated incarnation is downright mediocre, but the brand is so strong that it has survived even a massive setback in quality. Impressive.
Going for it
About six and a half years ago, a man named David Roux came to speak at Rose-Hulman. I was an undergrad at the time, in my junior year, and I was probably more concerned with an upcoming snowboarding trip to Steamboat Springs than a lecture from some unfamiliar old guy. However, his main point sunk in: Don’t be a worker bee. Start. Lead. Explore. Create. Be an entrepreneur.
As of today, I am officially abandoning my job hunt. I have found what I was looking for; I had it all along. The problem was a lack of complete commitment.
I have been doing entrepreneurial things since I was a child. Mowing lawns at first, later doing IT consulting and computer repair. While in undergrad, I dabbled in the world of web development by building Bonneville Club, which served as an invaluable lab for me to learn about server administration, community building, people management, and revenue generation. Later, I experienced the thrill of being web-famous with a couple of popular blog posts and millions of visitors to my webcomic.
The business card from my IT consulting "company" during high school, a decade ago.
I valued my time at Medtronic after undergrad. I had wonderful co-workers, a company that treated its employees very well, and a salary higher than many see in their lifetimes. But I wasn’t satisfied.
“I realize this seems odd advice. If they make your life so good that you don’t want to leave, why not work there? Because, in effect, you’re probably getting a local maximum. You need a certain activation energy to start a startup. So an employer who’s fairly pleasant to work for can lull you into staying indefinitely, even if it would be a net win for you to leave.”
When I went to grad school, I chose to study entrepreneurship in the Management Science and Engineering program. I took courses on starting companies. I attended lectures by famous entrepreneurs. I talked with Silicon Valley venture capitalists and CEOs. I idolized my successful-entrepreneur professors. I watched my friends start and build businesses.
There was, I believe, a bit of jealousy. If my friends could do it, why not me? I mean, I was smart, too. Why couldn’t I experience the dizzying highs and crushing lows? Why couldn’t I build amazing products? Why couldn’t I achieve financial freedom? Why not?
I have come to realize that there were two things holding me back: fear and social expectations. For a time I used money or a lack of ideas as excuses, but a detailed examination of business case studies shows that deficiencies in those areas rarely represented insurmountable obstacles. No, the fear of the unknown kept me locked in place, and that kept me in line with society. Why give up a good job at a solid company in the pursuit of a crazy dream? What’s more, society tends to fear change and uncertainty and ostracize those who dare challenge the status quo. To many, the thought of venturing off on one’s own is pure madness.
But without change there cannot be progress. Who will move the world if not me?
“If you want to do it, do it. Starting a startup is not the great mystery it seems from outside. It’s not something you have to know about ‘business’ to do. Build something users love, and spend less than you make. How hard is that?”
– Paul Graham
In some ways, the economic collapse was the best thing that could have happened for me. It made my job search difficult to the point of impossibility. In hindsight, I don’t know why I was looking for a job at an established company instead of heading out on my own. Clearly, my heart wasn’t in the hunt. The challenge was worsened by my desire to switch into a more business-oriented role and away from my technical roots. I had good discussions with a few companies, and interviews with some others, but they seemed loath to help me make that transition. Some went as far as to offer me technical roles developing software, but such capitulation would be, in my mind, career suicide. Another job as a software engineer for somebody else would nullify my entire graduate education and permanently cement me in my pigeonhole. I would rather abandon high-tech entirely than write software in a cube for somebody else. Oh, and I don’t think I’m a very good programmer.
“You‘ve got all these cops thinking you‘re a lawyer. And you got all these lawyers thinking you‘re some kind of cop. You‘ve got everybody fooled, don’t you?“
— from the film “Michael Clayton”
On the other hand, writing software for myself is entirely different. Despite my not being particularly good at it, writing software for my own ends is deeply satisfying. I love the act of creation. I love the instant gratification. I love the communion between me and my machine.
Thus, my startup is a software startup. Of my many interests — hockey, photography, baking, etc. — software is the one most amenable to company-building. Who cares if the prototype code is crap? If it works well enough to get me to the next stage, where I might be able to hire a competent coder to replace my hacker self, then the mission has been accomplished.
Nesota LLC world headquarters
My intent is to give this my all. When I turn 30 in three years, I want to be either rich or penniless. The outcome doesn’t matter so much to me as long as it’s not the mushy middle; that would be indicative of a failure. I want to know that I gave it my full effort. I don’t want to half-ass it and spend the next decade wondering what could have been.
Hopes and dreams
I’m not rich. I’m not famous. I have limited capital, a car with 204k miles on it, and a two-year-old computer.
But I have ambition. I’m going for it.
(cross-posted at Keacher.com)
Challenges
Posted by Jeff in photography, programming on September 12th, 2009
The deblurring of images, subject of Nesota’s upcoming product, is an extremely difficult problem. How difficult? Let’s give it a look.
Conceptually, it isn’t too bad: given an observed blurry image y, find the corresponding unobserved (latent) sharp image x. The complexity stems from the noise in the problem (and there’s always noise), the challenge in deciding when an image is “sharp,” and the overall vagueness of the problem.
The problem is usually modeled using an equation like
y = x ⊗ h + n
where y is the observed blurry image, x is the unobserved sharp image (the recovery of which is our goal), n is noise, ⊗ is the convolution operator, and h describes the blur (commonly known as the Point Spread Function, or PSF). Since we’re solving for x, and we know only y, the problem is clearly ill-posed: we have three unknowns and only one equation. What to do?
The problem can be helped somewhat by imposing constraints on the variables. Here’s an example. For simplicity, assume that all of the variables are scalars and * is the multiplication operator. If we are told that
41 = x * h + n
and nothing more, then there are many valid solutions. For example, a valid solution is x=7, h=3, and n=20. Another equally valid solution could be x=41, h=1, and n=0. However, if we are told instead that
41 = x * h + n
s.t. x is even, 2 < h < 5, and n ∈ {0,1}
then we can clearly see that the only valid solution satisfying the constraints is x=10, h=4, and n=1.
Similarly, the challenge in solving the deblurring problem is imposing the proper constraints on the variables. In the image deblurring problem, the variables are typically represented as matrices, which may each have millions of elements, which means that there are, essentially, millions of unknowns. A brute-force, exhaustive search of the solution space — trying every possible combination of values — is completely infeasible. We need some constraints.
Fortunately, we do know a few things about the sharp image, PSF, and noise that can get us pointed in the right direction. First, the image values are bounded. On computers, in files like JPEGs and PNGs, every pixel, for every channel (red, green, and blue), has an integer value between 0 and 255, inclusive; that is, there are 8 bits per pixel (2^8 = 256), and 3 channels, leading to 24 bits of data per pixel, or 24-bit color. That’s one constraint: all of the pixels in our blurry and sharp images need to have values between 0 and 255, inclusive.
A second constraint, this time on the PSF, is that the PSF is energy-conserving. In other words, when the PSF blurs the image, it doesn’t add or remove any energy to the pixel, so instead of a single bright pixel, you might instead get several dim pixels that sum to the same value as the bright pixel. This tells us two things: first, the range of element values in the PSF is between 0 and 1, inclusive; and second, the sum of all of the elements in the PSF must equal exactly 1.
Constraints on the noise term can be a bit tricky, and tend to be chosen for simplicity. Fortunately, the model tends not to be overly sensitive to the accuracy of the noise (noisy noise!), so a Gaussian or Poisson distribution is often chosen, with 0 mean and a standard deviation chosen based on empirical observation of known images. The noise term has a lot to absorb: optical imperfections, inconsistencies across the frame, sensor noise, quantization noise, compression noise, and more.
From there, however, the problem gets really tricky. How do we know when we’ve found the sharp image? How do we solve a system with so many variables? The plot thickens…