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Which is better: Many customers at low price-point or few at high price?

2012-05-01T14:00:58Z

The results of a serendipitous live experiment were recently published as guest posts on this blog. Sacha demonstrated the benefits of selling many copies of an eBook at a low price, while Jarrod pointed out the advantages of higher prices, bringing in more revenue with 1/6th the number of units sold.

The ensuing discussion swirled around the merits of selling more units (i.e. maximizing reach) versus selling more expensive units (i.e. maximizing per-unit profitability). This is a choice that every startup founder must make, so I’d like to dig in deeper.

To clarify the discussion, let’s use a simpler model:

Companies A and B both sell products with recurring monthly revenue, and both brought in $10,000 in revenue last month.
Company A has 1,000 customers each paying $10/mo.
Company B has 10 customers each paying $1,000/mo.

Which is better?

Oops, bad question. How about: Which company would you rather own? Or: What primary problem should each company be working to solve? Or: Under what conditions are each of these companies interesting? Or: Which company could raise money more easily?

Let’s focus on just one question: For which company would be easier to raise money?

Wait! That’s shitty! Why the obsession with raising money, what if you don’t want a huge company, what if you want to bootstrap, don’t you know raising money isn’t a measure of correctness or success, …

I agree! But “raise money or not” is also a decision everyone must make, and it turns out that exploring that question will end up answering all the other ones. So let’s play!

Market size

Suppose the total addressable market is small. In that case, A can’t keep growing forever, so its revenue is limited, which is a bad spot. B can extract more money from the limited pool of customers, so that’s better. Except, of course, investors don’t like small markets!

In a large market, B isn’t necessarily bad, but A shows far more potential. Over time companies at small price points are able to increase prices and otherwise extract more money from various customer segments, which means A has a bigger revenue potential.

Perhaps most importantly, A demonstrates that there is a large market at all. If you’ve already found 1,000 customers, there’s 10,000, and likely 100,000. If you’ve only found 10, there might be 10,000 out there, but if so, you don’t have supporting evidence. Riskier.

Speaking of risk…

Market risk

Many companies die because they can’t find enough people to pay. Many more die that way than die because the product sucks or doesn’t have enough features or because they don’t have a staff designer.

There’s a million variables — can you locate potential customers, can you bring them to your website, can you get them to read and click, can you get them to sign up, can you get them to agree to your price. A million variables means it’s hard to get it right.

Therefore, an investor is always impressed with a company like A who has made irrefutable progress on this particular front. Having 1,000 people paying you any amount of money whatsoever goes a long way. It’s a lot harder to get 1,000 paying customers than to add three features, because the latter is a matter of time and money whereas the former is largely out of your control.

Getting 10 people to pay you — even a large amount — is actually not that hard. If a co-founder has a rolodex in the industry — extremely common — then it would be surprising not to find 10 people. That doesn’t prove you have a repeatable, scalable method for finding customers, nor that there are a lot more potential customers out there.

Market risk is most startups’ biggest risk. One interesting way of reducing that risk is to build a company like B where you just don’t need to sell very much to achieve your goals. That’s awesome because the risk is low when the bar is low. That’s not intended as an “insult” — in fact I believe far more companies should have this attitude.

Time heals many wounds (but not all)

Over the time scale of “years,” you can count on certain trends.

For example, the average cost of customer acquisition diminishes. Why? Because you get organized around marketing metrics, because your campaigns get optimized, because your landing pages and drip campaigns become stronger, because word of mouth produces sales “for free,” and so forth.

Another is that average revenue per customer increases. Why? Because new pricing tiers better segment customers, prices go up as reputation grows, you create add-on products and services, you create new revenue through business development, and so forth.

What’s not true is that you always unlock big growth drivers. Indeed, many companies get stuck at a certain growth rate which, while positive, eats too much money during its slow crawl to cash-flow-positiveness, and by the same math doesn’t generate interesting profits after that. Once profitable, at least that sort of company is creating jobs and still could unlock something someday, but of course an investor in general isn’t interested in that outcome.

So back to our two companies. Company A has demonstrated that some growth is possible, and where there’s 1,000 customers from a shoestring budget there’s likely several other growth drivers out there; anyway, one is unlocked. Which is more than you can say for B. So, along one of the dimensions which doesn’t automatically improve with time, A wins.

That’s why, even if A isn’t doing well in other areas, that’s not as important. Suppose you argue that $10/mo isn’t enough money to be interesting — perhaps, but average revenue increases, so that’s not a long-term problem. Suppose you discover that it costs $60 to acquire a new $10/mo customer which is too much to be sustainable — perhaps, but that cost diminishes over time, so it’s not a long-term problem.

Investors are of course more interested in where you could be in two years than where you are right now. They’re more worried about the problems which don’t naturally get corrected over time.

Pivotability

Nowadays everyone agrees that it’s both likely and healthy for an early-stage startup to be on the lookout for an intelligent pivot.

Actually, more than “on the lookout,” you should be actively probing the market, which means interviewing customers and non-customers alike, attending industry events to have real conversations (not quipping to each other on Twitter), exploring the metrics of your website, your marketing, and product features, and so on.

One of the most common answers to “what made you successful” is “we decided to stop X and do Y.” Therefore, actively collecting the data on what’s actually happening, what customers actually will pay for, where the valuable hole in the market actually is — this is one of the most valuable things you can do, and the company which does it best is increasing its chance of success.

Given no other information about the companies, company A clearly has access to far more market data. They have 100x the quantity and range of customers to interview and analyze. They probably have a correspondingly large amount of website traffic to mine. They can subdivide their user population and try four ideas at once, iterating quicker to better information.

Lean Startup tells us that the speed at which theories can be tested is directly proportional to learning; the company who can do that faster and more accurately has a significant advantage.

I posit that this is true regardless of whether you’re taking investment.

A flurry of arguments in favor of B

So it’s clear that in general an investor will prefer A to B. But B is preferable in many cases, so let’s even the score.

If the cost of support is high, A will kill profitability and B wins.

If the cost of customer acquisition is 10x the monthly revenue or monthly revenue is 1/100th of where it should be to sustain the operations of the company, then the argument of “it gets better over time” doesn’t work, because although it gets incrementally better, it’s hard to justify orders of magnitude of improvement.

If the human cost of scaling A is higher than B, then at scale B might be much more profitable.

If you’re keeping the company small, it’s almost always cheaper and more fun to run it like B. You spend less on marketing/advertising/acquisition. Less time training customers. You have more time to make customers love you forever and therefore less churn and a happier general existence. In product development you have the delightful job of serving handful people with homogeneous needs rather than appeasing the disparate needs of thousands people who can’t agree on anything. Pretty much everything about it is nicer!

If the market is small, it’s hard to get more than a few customers, so you need a business model like B that extracts the most amount of money from the limited available pool.

But “freemium” is not Company A

I often see founders and investors alike using many of the above arguments to argue why a company with 100,000 free users is more valuable than a company with 1,000 paying customers. I disagree.

While it’s true that the potential for the company with vast numbers of freebie customers is indeed there, there’s just too many examples of startups with great products, great marketing, huge growth, large customer bases, where they just could not convert enough of the freebies to paid, and even after conversion, not paying enough.

Of course if there is a conversion rate, you can start applying the above logic again. Conversions rates increase over time, etc., so as long as the absolute number of paying numbers is interesting and the growth rate is large, you’re back to good. Better than good, in fact, because you have more levers to play with in terms of increasing conversions, offering different products, pivoting, etc..

Which is right for you?

Hopefully the detail above should be sufficient for you to decide which is appropriate for you.

If I had to boil it down to a sentence it would be:

If you want happiness and fulfillment from a small company, strive for B; if you want to maximize growth, influence, and financial value, strive for A.

Now leave a comment about your choice! Did you have other considerations as well?

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When You Create Value It Doesn't Mean You Have To Capture Every Bit Of That Value

2012-04-28T00:33:00Z

As I discussed in my Hacking Society post, one of the things I'm thinking a lot about these days is how to measure value that isn't directly monetized. There's a related aspect to all of this, as well: recognizing that when you create value, you don't have to monetize all of it directly yourself. Historically, in economics, they've talked about things like "externalities" and "spillovers" when discussing parts of the economic value chain that can't be controlled or monetized directly. However, it seems like a growing number of economists are realizing that this undersells what's happening. Externalities and spillovers often feel like a small thing -- a tangential bit tossed off to the side. But when you're dealing with information and digital goods, it's important to recognize that these things can be a major part of the market, and may not be controllable at all. And that may be a good thing.

In the discussion we had about Craigslist, one of the points was that while Craigslist itself only "captures" a small part of the value it's unleashed, that's not necessarily bad. First, it's good because much of that value to go out to the users of Craigslist themselves. That's why they appreciate and use Craigslist in the first place. If Craigslist tried to capture all of that value itself, people would stop using Craigslist. Now some may argue it becomes a different situation when you have third parties monetizing some of that value, but I disagree. When you look at the most successful companies in the world, they're often platforms -- they create value and capture some of it, but also allow much of that value to be monetized by others.

Look at Microsoft, Apple, Google and Facebook. All of them created a massive amount of value -- and all have become phenomenally successful companies -- but all of them did so by also letting others monetize large portions of the value they created. It's how you build a more long-lasting ecosystem from which you can continue to profit from over time. If you seek to capture all of the value yourself, you don't last very long.

I got to thinking about this more, after hearing the CEO of The Economist (who, one would hope, would understand these economic concepts) complaining about Flipboard capturing some of the value The Economist creates, and declaring it a "competitor" to The Economist's own digital and app ambitions.

“But you’re heading down a route we’ve seen before – giving the opportunity to extract value to somebody else in an area that should be our own – so Flipboard is problematic.”

Of course, that ignores the fact that Flipboard -- an aggregator app -- provides its own value as well. People don't use Flipboard just because it includes content from The Economist. They use it because of the overall experience and the fact that it aggregates content from lots of different sources in one place. As much as The Economist, or any publication, might like to "own" the reader, that's not necessarily what the reader wants. Letting others "extract" some of that "value" can actually be a really good thing. Flipboard provides a useful service for The Economist in not only experimenting with new ways to aggregate and present content -- from which The Economist can learn -- but also in potentially expanding The Economist's audience as well, feeding much greater value back into that ecosystem.

Yes, companies need to look at the overall market and see where it is they can extract value -- but you have to wonder about those who claim eminent domain over certain parts of the marketplace. Letting others extract some (and perhaps lots) of that value can have tremendous benefits for those who do so.

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Founder's Dilemmas: Equity Splits

2012-04-24T15:36:00Z

The following is an excerpt from HBS Professor Noam Wasserman’s new book, The Founder's Dilemmas: Anticipating and Avoiding the Pitfalls That Can Sink a Startup. Noam is one of a rare breed of business academics: he studies entrepreneurship using a rigorous empirical approach. The book taps Noam’s analyses of data on 10,000 founders, plus the personal stories of Evan Williams of Twitter, Tim Westergren of Pandora, and two dozen other founders.

As an example of the kind of insight that this data makes possible, take a look at this diagram, which is one of my favorites in the whole book:
Noam calls this the Rich vs King tradeoff, and it's a remarkable finding. On average, the founders who keep the most control over their company make the least amount of money. As with any data-based result, this raises more questions than it answers. For example, most entrepreneurs know that the most successful entrepreneurs - from Bill Gates to Jeff Bezos - kept tight control over their companies. We therefore seek to emulate their approach, to our own detriment, because we're often emulating the wrong things. Having the real facts helps us ask better questions. We should be asking not "how much control did Bill Gates seek?" but rather "what else is exceptional about his decisions that allowed him to escape the more common fate?" If you're interested in answering questions like this, read on.

I was lucky enough to get to read a version of the book when it was still in draft form. Now that the final version has come out, I'm excited to share a bit of it with you. At the time, I was asked to give an official endorsement of the book. Here's what I said:

"If you're starting a new company, you probably already know that a crazy variety of landmines await you. What if you had a map that showed exactly where they are and how to avoid them? Having seen these dilemmas derail countless startups, I wish every entrepreneur and prospective founder would read this book." - Eric

The following is an exclusive excerpt which sets up a common pitfall regarding equity splits. In Noam’s dataset, 73% of founding teams split equity within a month of founding, a striking number given the big uncertainties early in the life of any startup. The majority of those teams set the equity in stone by failing to allow for future adjustments to equity stakes if there are major changes within the team or the startup.

After this excerpt, the book outlines specific solutions that help founders avoid this pitfall.

Setting the early equity split in stone is one of the biggest mistakes founders can make. With their confidence in their startup and themselves, their passion for their work and their mission, and their desire not to harm the fragile dynamic within the nascent founding team, cofounders tend to plan for the best that can happen. They assume that their early, high levels of commitment will last long into the future, rather than waning as the challenges of founding begin to sap their passion for the idea and for each other. They assume that no adverse events will change the composition of the team.They also tend to take a very short-term view of the factors that should affect equity splits. They assume that the tasks that they are performing during the early stage of startup development are the same tasks that will be performed during the next and very different stages. They assume that their skills will remain as valuable to the startup as they are right now. They overestimate the amount of value that they will build in the first months compared to the value they hope to build over the subsequent years, and thus overweight their past contributions compared to the future contributions that will be required of them. Each founder places more value on his or her own contributions than on the contributions of the other cofounders,knowing the cost and extent of his or own efforts in a way that he or she cannot know the cost and extent of others’ efforts.

But such a best-case approach is hazardous. Uncertainties abound. At the company level, founders learn about the flaws in their initial plans and adjust the startup’s strategy, business plan,and business model. Professor Scott Shane reports that “almost half(49.6 percent) of new firm founders indicated that their business ideas [had] changed between the time they first identified them and the time when they were surveyed about them.” Such adjustments can cause major changes in the obstacles that the startup faces, the skills needed to address those obstacles, and thus the roles that each founder (or perhaps a new founder or a nonfounder) will have to play in building the startup.

At the individual level, as the strategy and business model shift,the skills of some founders become more important than the skills of others and roles often shift. As each founder learns about the demands of building a startup, reflects on his or her motivations,and sees how well his or her abilities address the startup’s needs, his or her commitment to the startup may change. The founders also come to understand each other’s abilities and commitment at a far deeper level than was possible at the beginning. Yet founders tend to overestimate how much value they will build during those early days, which can cause even bigger problems when a cofounder’scontributions wane later on.

A founder’s personal life may also affect his or her commitment and contributions. At Ockham Technologies, all of the founders were aware of the imminent arrival of idea-person Ken’s first child. However, even Ken was unsure how this would affect his willingness to quit his full-time job and focus on building Ockham.Extreme and unexpected health problems can catch all parties by surprise. For instance, while Microsoft was still a private company, cofounder Paul Allen was diagnosed with Hodgkin’s lymphoma,which caused him to quit the company, leaving Bill Gates as the sole active founder during the crucial three years before it became a public company.

In such ways, even the most comfortable equity split can be thrown into disarray. For instance, when Robin Chase and her partner, Antje, founded the car-sharing startup Zipcar, they agreed with a quick handshake to split the equity 50–50. The team believed it had avoided destructive tension over the equity split and could now focus on building the startup. “We shook across the table,50–50,” Robin recalls, “and I thought ‘great.’” Robin had heard about other teams that had faltered because of tough equity-split negotiations, and she breathed a sigh of relief that she and Antjehad avoided such problems. Robin poured her heart and soul into the startup, making major contributions to its growth, and was fully expecting Antje to do the same. Antje, however, remained at her full-time job and, by the summer, was expecting her second child. Robin wondered when her partner would be able to become more involved, but, in the end, Antje never joined full-time. Knowing that Antje still owned the same percentage as she did ate away at Robin, who later reflected, “That was a really stupid handshake, because who knows what skill sets and what milestones and what achievements are going to be valuable as you move ahead. That first handshake caused a huge amount of angst over the next year and a half.” Eventually Antje left the company altogether while continuing as a shareholder.

The cost to fix such problems can be very high, ranging from Robin Chase’s “angst” to more tangible financial costs. At govWorks.com, founders Kaleil and Tom had a cofounder, Chieh,who put up $19,000, worked “after hours” for five months (he had kept his day job instead of joining govWorks full-time), and then dropped out. When the remaining cofounders were about to close their first round of financing, their potential funder, Mayfield, was not willing to close until Kaleil and Tom bought Chieh out and reclaimed his equity. The VCs were willing to do a $410,000 “sweetheart deal” to facilitate the buyout. However, Chieh wanted $800,000. Amid the pressure to close the round, Kaleiland Tom ended up settling with Chieh for $700,000, making up the $290,000 out of their own pockets. Kaleil felt he was “beingextorted.” Although the risks of this kind of outcome are real,teams often fail to address them proactively. In my dataset, half of the teams had neglected to include any dynamic elements (vesting, buyout terms, and the like) in their equity agreements, sentencing themselves to the same risks faced by the Zipcar and govWorks.com teams.

How should founders deal with such developments? In short, by assuming when they do the initial split that things will change, even if the specific changes cannot be foreseen, and therefore structuring a dynamic equity split rather than the static splits used at Zipcar, govWorks, and many other startups. As important as it is to get the initial equity split right—by matching it as closely as possible thefounders’ past contributions, opportunity costs, future contributions, and motivations—it is equally important to keep it right; that is, to be able to adjust the split as circumstances change.

Before naming your startup, read this.

2012-04-23T13:28:35Z

Comments

How Disruption Works: Job Loss Isn't Really Job Loss

2012-04-06T14:30:00Z

One of the key points in understanding how disruption works is to recognize that as old industries fail, new industries grow up to take their place. For a true free market to work, failure has to be not just accepted, but embraced. Tragically, in the crony capitalist system we have today, large incumbents go running to the government as soon as they're disrupted, whining about how the disruption is not the normal workings of disruptive innovation, but rather "the end of the world" and a sign of clear evil. It's why you hear talk of "too big to fail" and all sorts of efforts to paint new innovations as illegal, rather than just disruptive competition. Yet, as we've seen over time, disruptive innovation may move jobs around and cause certain sectors to diminish, but it tends to open just as many, if not more, opportunities elsewhere over time. I don't think I've ever seen that displayed quite as clearly in graphic form as in a chart that LinkedIn recently released, looking at what parts of the industry have been growing and which parts have been shrinking over the past few years: This chart caught the attention of Paul Smalera, who specifically noted that newspapers are at the very bottom, but online publishing is right near the top on the growth side -- a near perfect showing of how jobs shift over time. He notes the classic Innovator's Dilemma issue with news companies, where they thought they were in the business of selling newspapers, and that held back their ability to innovate:

They have been trapped in a terrible mindset that they are in the business of selling newspapers. The leap from paper to digital may be vast, but to newspaper publishers, it seemed like vaulting to a different business entirely, one they were loathe to get into. No matter what kind of lip service newspapers paid to the digital transformation, the most prominent paywall model out there, that of the New York Times, still protects print subscriptions with a tiered digital pricing strategy – one so annoying that it motivated its former digital design director to complain publicly about the entire signup process.

The lesson online media companies have taken from newspapers’ slow, public death is to move beyond the idea of selling the product. Online sites are selling their audience. It’s a simple twist of the equation, but one that changes everything about how a media company is run. A CEO who has realized that her audience – her customers – is the most important thing the company has will stop at nothing to give those customers what they want. Anything to make them feel as if they’re getting value from the company. And although she’ll monetize their aggregate value with advertisers and marketers, she’ll also protect them from underhanded sales pitches or confusing pricing strategies that infuriate the web-savvy.

This is a really good point on multiple levels. Beyond the innovator's dilemma (and the key point of figuring out what the real product is), Smalera is also debunking one of the popular myths of the internet era: when you're selling a user's attention, companies will naturally abuse their users. What he notes is that companies that do this don't end up lasting through the long haul, because users get annoyed and go elsewhere. Even though it's become a common pejorative statement among neo-luddites to mock the idea that the "users is the product," one thing that is true when that happens is that the companies need to treat their users right, or they have a crappy product that they can't sell.

Similarly, Mathew Ingram uses this to discuss why it's so difficult for legacy businesses to adapt, noting that it's difficult to change business models on the fly. Not only do you have to make big bets on new things, but you also have to keep the legacy business running while at the same time trying to undercut it with the new thing. It's why so many companies fail the innovator's dilemma test. Unless you have incredibly visionary leadership who can push a company through with a strong and clear vision of why the company must move in that direction, the magnetic appeal of trying to prop up increasingly obsolete businesses is just too strong.

But, the failure comes not because of some new "threat" or because of some kind of disgraceful activity (no matter how much legacy players try to describe it that way), but because corporate leadership chose to let others innovate, rather than supporting a plan of out-innovating themselves. Very, very few companies are willing to cannibalize their own business models -- but the failure to do that just means that someone else cannibalizes it for you.

And it goes way beyond news. The chart above shows some other key areas of disruption as well. That clump of retail, automotive, construction, banking, telecommunications, pharmaceuticals and real estate represents prime feeding ground for the next decade of disruption -- much of which has already started. You don't necessarily see the corresponding growth points on the opposite side of the chart, but as with newspapers and online publishing, give it a few years, and those new jobs and industries will make their way up the chart, as the legacy players continue to shrivel up (and whine all the way down).

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Killing Your Startup By Listening to Customers

2012-02-27T13:30:03Z

The art of entrepreneurship and the science of Customer Development is not just getting out of the building and listening to prospective customers. It’s understanding who to listen to and why.

Five Cups of Coffee
I got a call from Satish, one of my ex-students last week. He got my attention when he said, “following your customer development stuff is making my company fail.” The rest of the conversation sounded too confusing for me to figure out over the phone, so I invited him out to the ranch to chat.

When he arrived, Satish sounded like he had 5 cups of coffee. Normally when I have students over, we’d sit in the house and we’d look at the fields trying to catch a glimpse of a bobcat hunting. But in this case, I suggested we take a hike out to Potato Patch pond.

Potato Patch Pond
We took the trail behind the house down the hill, through the forest, and emerged into the bright sun in the lower valley. (Like many parts of the ranch this valley has its own micro-climate and today was one of those days when it was ten degrees warmer than up at the house.)

As we walked up the valley Satish kept up a running dialog catching me up on six years of family, classmates and how he started his consumer web company. It had recently rained and about every 50 feet we’d see another 3″ salamander ambling across the trail. When the valley dead-ended in the canyon, we climbed 30-foot up a set of stairs and emerged looking at the water. A “hanging pond” is always a surprise to visitors. All of a sudden Satish’s stream of words slowed to a trickle and just stopped. He stood at the end of the small dock for a while taking it all in. I dragged him away and we followed the trail through the woods, around the pond, through the shadows of the trees.

As we circled the pond I tried to both keep my eyes on the dirt trail while glancing sideways for pond turtles and red-legged frogs. When I’m out here alone it’s quiet enough to hear the wind through the trees, and after awhile the sound of your own heartbeat. We sat on the bench staring across the water, with the only noise coming from ducks tracing patterns on the flat water. Sitting there Satish described his experience.

We Did Everything Customers Asked For
“We did every thing you said, we got out of the building and talked to potential customers. We surveyed a ton of them online, ran A/B tests, brought a segment of those who used the product in-house for face-to-face meetings. ” Yep, sound good.

“Next, we built a minimum viable product.” Ok, still sounds good.

“And then we built everything our prospective customers asked for.” That took me aback. Everything? I asked? “Yes, we added all their feature requests and we priced the product just like they requested. We had a ton of people come to our website and a healthy number actually activated.” That’s great I said, “but what’s your pricing model?’ ”Freemium,” came the reply.

Oh, oh. I bet I knew the answer to the next question, but I asked it anyway. “So, what’s the problem?”

“Well everyone uses the product for awhile, but no one is upgrading to our paid product. We spent all this time building what customers asked for. And now most of the early users have stopped coming back.”

I looked at hard at Satish trying to remember where he had sat in my class. Then I asked, “Satish, what’s your business model?

What’s your business model?
“Business model? I guess I was just trying to get as many people to my site as I could and make them happy. Then I thought I could charge them for something later and sell advertising based on the users I had.”

I pushed a bit harder.

“Your strategy counted on a freemium-to-paid upgrade path. What experiments did you run that convinced you that this was the right pricing tactic? Your attrition numbers mean users weren’t engaged with the product. What did you do about it?”

“Did you think you were trying to get large networks of engaged users that can disrupt big markets? Large” is usually measured in millions of users. What experiments did you run that convinced you could get to that scale?”

I realized by the look in his eyes that none of this was making sense. “Well I got out of the building and listened to customers.”

The wind was picking up over the pond so I suggested we start walking.

We stopped at the overlook a top of the waterfall, after the recent rain I had to shout over the noise of the rushing water. I offered that it sounded like he had done a great job listening to customers. And better, he had translated what he had heard into experiments and tests to acquire more users and get a higher percentage of those to activate.

But he was missing the bigger picture. The idea of the tests he ran wasn’t just to get data – it was to get insight. All of those activities – talking to customers, A/B testing, etc. needed to fit into his business model – how his company will find a repeatable and scalable business model and ultimately make money. And this is the step he had missed.

Customer Development = The pursuit of customer understanding
Part of Customer Development is understanding which customers make sense for your business. The goal of listening to customers is not please every one of them. It’s to figure out which customer segment served his needs – both short and long term. And giving your product away, as he was discovering, is often a going out of business strategy.

The work he had done acquiring and activating customers were just one part of the entire buisness model.

As we started the long climb up the driveway, I suggested his fix might be simpler than he thought. He needed to start thinking about what a repeatable and scalable business model looked like.

I offered that getting acquiring users and then making money by finding payers assumed a multi-sided market (users/payers). But a freemium model assumed a single-sided market – one where the users became the payers.

He really needed to think through his Revenue Model (the strategy his company uses to generate cash from each customer segment). And how was he going to use Pricing, (the tactics of what he charged in each customer segment) to achieve that Revenue Model. Freemium was just one of many tactics. Single or multi-sided market? And which customers did he want to help him get there?

My guess was that he was going to end up firing a bunch of his customers – and that was OK.

As we sat back in the living room, I gave him a copy of The Startup Owners Manual and we watched a bobcat catch a gopher.

Lessons Learned

Getting out of the building is a great first step

Listening to potential customers is even better

Getting users to visit your site and try your product feels great

Your job is not to make every possible customer happy

Pick the customer segments and pricing tactics that drive your business model

Filed under: Business Model versus Business Plan, Customer Development

Can-do Thinking Makes Risk Management Impossible

2012-01-10T14:57:03Z

“Can-do thinking makes risk management impossible. Since acknowledging real risk is defeatism, the risk management function in a can-do organization is restricted to dealing with those smallish risks that can be mitigated by quick action. That means you confront all the risks except the ones that...

Visit my blog for the full story, links and lots more content on agile development and agile project management...

The New and Updated Running Lean Book

2012-01-02T04:24:31Z

I just submitted my final revisions to O’Reilly for the printed version of Running Lean which will come out in March 2012. While I had originally intended to just “tidy up” the PDF version for print, I realized earlier this year that a complete rewrite might be necessary which is exactly what I ended up doing.

Why rewrite the book?

A book like large software is never finished, only released.

The PDF version of Running Lean was targeted primarily at people like me: technical founders building web-based products. I was running my first company and on my fifth product at the time. I had been inspired by Steve Blank’s book: The Four Steps to the Epiphany and the early works on the Lean Startup methodology by Eric Ries, and was rigorously applying and testing these principles on my latest product.

My goal was to create an actionable guide for other entrepreneurs taking these principles to practice within the context of web-based products. I wrote and self-published the PDF version iteratively using the same methodology outlined in the book.

However, since the PDF version came out in January 2011, the audience for the book grew beyond my prototypical early adopter, and I was repeatedly met with two kinds of feedback:

“I can see how these techniques worked for your business, but they won’t work for me because I am building X.”
“Even though I am building X, these techniques have greatly helped my business with only slight modifications.”

(where X ranged from software to hardware, B2C to B2B, and high tech to low tech).

I was curious and decided to explore further.

In the past year, I have actively sought opportunities to expose and test the ideas in the book with a wide range of businesses by way of running workshops, creating a newsletter, taking on mentor positions at several accelerators, and working closely with other entrepreneurs. I still remember being nervous the first time I delivered a workshop to a room full of biotech entrepreneurs. But each time, the results were positively encouraging.

Why traditional publishing?

My goal for the book never involved making a run for a bestseller list and/or pivoting to become a speaker/consultant – I still have the product bug. Rather, my goal was building a platform to further the conversation on entrepreneurship where the book would be one of many products.

A non-fiction book is a souvenir, just a vessel for the ideas themselves. You don’t want the ideas to get stuck in the book… you want them to spread.
-Seth Godin

As of this writing, I’ve sold just over 15,000 copies of the book. While I’d always been prepared to self-publish the book and had even started researching print-on-demand options, I was contacted by a major publisher in December 2010. Not only had they already reviewed the latest version out at the time, but they were interested in publishing the book as is.

I entertained the thought of using traditional publishing as a channel to potentially reach a different audience and spoke to a few other publishers. But what sealed the deal for me was hearing Eric Ries’ vision for creating an official Lean Startup series of books. It not only made sense for furthering the Lean Startup movement but also aligned well with my original goal.

So what’s new in this version?

The printed version of Running Lean aims to broaden the audience beyond web-based products. Even though a lot of these ideas came out of the high-tech startup world, I believe now that the principles they embody are universally applicable to any startup or product.

This is reflected in a completely new layout for the book – one that delineates meta-principles from tactics:

Other notable highlights

More concrete case-studies
I replaced the Lean Canvas meta case-study (which some people found confusing) with a more complete example that follows throughout the book from ideation to exit. In addition, I’ve supplemented the text with several other smaller case studies from a wide range of products (high-tech to no-tech) that illustrate the universal applicability of these principles.

More field-tested techniques
The book outlines additional techniques for maximizing learning from customers such as:
- how to get customers to an interview
- how to tell when your customers are lying to you
- how to get your customers to want to pay

Covers patterns for other business models
While I wrote Running Lean originally with a Software-as-a-Service context (which readily extends to a wide range of other types of products), I was frequently asked how one might adapt it to two other models in particular: a network effects product, and a multisided (marketplace) product. I cover both of these in the book.

Updated with the latest thinking on Lean Startups
Finally, since I wrote the first version, Eric Ries published his book, The Lean Startup. Along with being the authoritative guide on Lean Startups (buy it now if you haven’t yet), the book also introduces several new and powerful concepts like Innovation Accounting and Engines of Growth that I have assimilated into the printed version.

Where do I get it?

The book will be published by O’Reilly and will be available in both print and eBook formats in March 2012.

Pre-order the book here*.

* As this is a major revision going through the publishing cycle, this version is not an automatic upgrade from the PDF version.

Why not? (Updated based on comments below)

Yes, I wrote the PDF version iteratively in 2-week cycles but I declared the book released (final) with version 7. If you were an early access customer, you should have received an email from me dated February 7, 2010 stating just that.

There have been no incremental updates made to the book since then and no promise for updates made to people who bought the book after that date.

From a timeline perspective, it was not until late summer (once Eric and O’Reilly were involved) that I even considered doing a rewrite for the reasons I outlined above. Because more than 20% of the book has changed and more than a year will have passed between versions, O’Reilly and I have decided to officially label this a Second Edition which will hopefully serve to clarify the postion of this update.

Thanks for your continued support and here’s to your success in 2012!

The Startup Team

2011-12-13T13:30:56Z

Individuals play the game, but teams beat the odds
SEAL Team saying

Over the last 40 years Technology investors have learned that the success of startups are not just about the technology but “it’s about the team.”

We spent a year screwing it up in our Lean LaunchPad classes until we figured out it was about having the right team.

Startup Team Lessons Learned
During the last 12 months we’ve taught 42 entrepreneurial teams with 147 students at Stanford, Berkeley, Columbia and the National Science Foundation. (As many teams as most startup incubators.)

Get into the Class
When I first started teaching hands-on, project/team entrepreneurship classes we’d take anyone who would apply. After awhile it became clear that by not providing an interview process we were doing these students a disservice. A good number of them just wanted an overview of what a startup was like – an entrepreneurial appreciation class (and we offer some great ones.) But some of our students hadn’t yet developed a passion for entrepreneurship and had no burning idea that they wanted to bring to market. Yet in class they’d be thrown into a “made-up in the first week” startup team and got dragged along as a spear-carrier for someone else’s vision.

Step One – Set a Bar
So as a first step we made students formally apply and interview for the Lean LaunchPad class. We were looking for entrepreneurs who had great ideas and interest in making those ideas really happen. We’d hold mixers before the first class and the students would form their teams during week one of the class.

But we found we were wasting a week or more as the teams formed and their ideas gelled.

Step Two – Apply As A Team
So next time we taught, we had the students apply to the class as a team. We hold information sessions a month or more before the classes. Here students with preformed teams could come and have an interview with the teaching team and get admitted. Or those looking to find other students to join their team could mix and market their ideas or join others and then interview for a spot. This process moved the team logistics out of class time and provided us with more time for teaching.

But we had been selecting teams for admission on the basis of whether they had the best ideas. We should have known better. In the classroom, as in startups, the best ideas in the hands of a B team is worse than a B idea in the hands of a world class team.

Here’s why.

Step Three – Hacker/Hardware, Hustler, Designer, Visionary
As we taught our Lean LaunchPad classes we painfully relearned the lesson that team composition matters as much or more than the product idea. And that teams matter as much in entrepreneurial classes as they do in startups.

In a perfect world you build your vision and your customers would run to buy your first product exactly as you spec’d and built it. We now know that this ‘build it and they will come” is a prayer rather than a business strategy. In reality, a startup is a temporary organization designed to search for a repeatable and scalable business model. This means the brilliant idea you started with will change as you iterate and pivot your business model until you find product/market fit.

The above paragraph is worth reading a few times.

It basically says that a startup team needs to be capable of making sudden and rapid shifts – because it will be wrong a lot. Startups are inherently chaos. Conditions on the ground will change so rapidly that the original well-thought-out business plan becomes irrelevant.

And finding product/market fit in that chaos requires a team with a combination of skills.

What skills? Well it depends on the industry you’re in, but generally great technology skills (hacking/hardware/science) great hustling skills (to search for the business model, customers and market,) great user facing design (if you’re a web/mobile app,) and by having long term vision and product sense. Most people are good at one or maybe two of these, but it’s extremely rare to find someone who can wear all the hats.

It’s this combination of skills is why most startups are founded by a team, not just one person.

University Silos
While building these teams are hard in the real world, imagine how hard it is in a university with classes organized as silos. Business School classes were only open to business school students, Engineering School classes were only open to engineering school students, etc. No classes could be cross-listed. This meant that you couldn’t offer students an accurate simulation of what a startup team would look like. (In our business school classes we had students with great ideas but lacking the technical skills to implement it. And some of our engineering teams could have benefited from a role-model to follow as a hustler.)

So the next time we taught, we managed to ensure that the class was cross-listed and that the student teams had to have a mix of both business and engineering backgrounds.

I think we’ve finally got the team composition right – relearning all the lessons investors already knew.

But now on to the next goal – getting our mentor program correct.

Lessons Learned

Finding product/market fit in startup chaos requires a team with a combination of skills

Hacker/Hardware, Hustler, Designer, Visionary

At times an A+ market (huge demand, unmet need) may trump all

Getting the Mentors right is the next step

Filed under: Customer Development, Family/Career/Culture, Lean LaunchPad, Teaching

What’s a Better Way to Research a Market: Surveys or Experiments?

2011-11-29T12:01:41Z

Photo by Seattle Municipal Archives

I received the following question from a reader a few weeks back:

I’m considering creating a mobile app and I want to know quick/effective ways to validate some of my assumptions. Is it more effective to put out small experiments that test your assumptions, or are surveys of the possible users a better approach?

My answer: it depends on what you’re trying to test.

In general a survey is going to give you decent results for little effort. A survey takes 20 minutes to put together (SurveyGizmo or SurveyMonkey), email it, and you get some info. It’s a simple approach that doesn’t take a lot of time.

However, it’s nowhere near as accurate as putting out experiments. Experiments that ask someone to buy something, sign up for a list, or perform some kind of behavior are the only real way to know if something works. But these kinds of things take so much longer to put together that you have to balance this level of effort with the value they provide.

If you had unlimited time I would always recommend experiments. But surveys save you time, so you’ll inevitably have to rely on them or you’ll never start building your app.

Two things you can’t get from surveys: actual conversion rates and pricing info. You can ask “would you sign up for this list” or “would you pay $x for this” but these are useless questions.

If you need this kind of knowledge, do an experiment. For most other information, surveys can be a solid, time saving approach.

I’m interested to hear your thoughts in the comments.

John Seddon on Systems Thinking in IT [45min video] [Øredev 2010]

2011-11-28T17:52:08Z

Comments

Case Study: The Nordstrom Innovation Lab

2011-10-25T13:57:00Z

Today's case study answers a bunch of questions all at once about Lean Startup principles: can they be used inside a Fortune 500 company? can they be used to sell physical low-tech products? can they be used in a retail store? I have been confidently answering questions like these non-stop for the past few months. I do believe the answer is yes. But, as the saying goes, seeing is believing. And now you won't have to take my word for it.

Nordstrom is currently ranked #254 on the Fortune 500 (yes, I looked it up) with over $9 billion in revenues. Scrappy startup they are not. And yet they face the same competitive pressures that are causing every modern company to take a long, hard look at the process they use to innovate. Anyone who has read The Innovator's Dilemma knows just how hard it is for a company that has been successful to invest in potentially disruptive innovations.

I have been talking to JB Brown, the manager of the Nordstrom Innovation Lab about publishing a case study. At the same time, Nordstrom had sent a camera crew to document the Lab at work. When I saw the rough cut of the videos they were producing, I knew they would be a powerful teaching tool. It's one thing to talk about "rapid experimentation" and "validated learning" as abstract concepts. It's quite another to see them in action, in a real-world setting. Proving his understanding of minimum viable product, JB suggested that we start small, by posting a "case study MVP." That's how this post came to be.

Below, you'll find two videos: one about the lab, and one containing a case study of the team at work. Watch them both. If you have questions, JB has generously agreed to make himself available to answer them in a future post. Just leave your question as a comment to this post. If there's sufficient interest, we'll expand this MVP.

"A Lean Startup Inside a Fortune 500 Company"

"We Really Don't Know What the Features Are Yet..."

Here are some highlights that I found especially interesting:

One-week iterations. One of the hardest things about corporate innovation is breaking through the slowness that is the default speed for most initiatives. The Nordstrom Innovation Lab solves this problem by working in one-week increments. In the second video above, you'll see them build an entire new product in one week end-to-end.
Genchi gembutsu. This is one of my favorite concepts from the Toyota Production System. It translates roughly as "go and see for yourself" - it's the Toyota version of "get out of the building." By talking face-to-face with customers, salespeople, and managers in a physical store, the innovation team is able to identify an opportunity that they can execute against extremely quickly. But they go beyond simply "getting out of the building" - they actually set up shop physically in a retail store for the entire week. They build products, test new features, and get feedback all out in the open. You really have to see it to believe it.
Simple, rapid, experiments. I hear all the time that developing for iOS, with its myriad approval delays and deployment obstacles means that you can't use rapid development techniques on that platform. Yet in the video you'll see this team overcome that bias with a little ingenuity. They simply brought two iPads with them. While the app is in development, the sales team is using one iPad, and the developers are working on another. At every break, the sales team swaps iPads with the developers - always using the latest version of the app. (The same technique works with paper prototypes, too.)

Have questions for JB and the rest of the Nordstrom Innovation Lab team? Post them as comments.

A decision without tradeoffs...

2011-11-26T10:35:00Z

isn't a decision.

The art of good decision making is looking forward to and celebrating the tradeoffs, not pretending they don't exist.

How the iPhone Got Tail Fins – Part 2 of 2

2011-10-20T12:30:08Z

Read part 1 of this post for background.

By the early 1920’s General Motors realized that Ford, which was now selling the Model T for $290, had an unbeatable monopoly on low-cost automobile manufacturing. Other manufacturers had experimented with selling cars based on an image and brand. (The most notable was an ad by the Jordan Car company.) But General Motors was about to take consumer marketing of cars to an entirely new level.

Market Segmentation General Motors had turned the independent car companies acquired by its founder Billy Durant into product divisions. But in a stroke of genius GM transformed these divisions into a weapon that Ford couldn’t match. With the rallying cry “a car for every purse and purpose,” GM positioned its car divisions (Chevrolet, Pontiac, Oldsmobile, Buick and Cadillac) so they would cover five price segments – from low-price to luxury. It targeted each of its brands (and models inside those brands) to a distinct economic segment of the population. Chevy was directly aimed at Ford – the volume car for the working masses. Pontiac came next, then Oldsmobile, then Buick. The top-of- the-line Cadillac offered luxury and prestige announcing you had finally arrived at the top of the conspicuous consumption heap. Consumers could announce their status and lives had improved by upgrading their brands.

GM had one more trick to make this happen. Within each brand, the top of the line was just a bit less expensive than the lowest priced model of the next expensive brand. The goal was to convince the consumer to spend a little more to trade up to a more prestigious brand.

Market segmentation by price was something no other automotive manufacturer had ever done. While other car companies could compete with one of GM’s divisions, few had GM’s capital and resources to compete simultaneously with the onslaught of car models from all five divisions.

Planned Obsolescence While market segmentation allowed GM to use its divisions to reach a wider market than Ford or Chrysler, this didn’t solve the problem of market saturation. By the late 1920’s, most everyone in the U.S. had a car. And cars lasted 6 to 8 years. Even worse, the market was now filled with used cars that provided even lower cost basic transportation. Sloan, the General Motors CEO, faced two seemingly unsolvable challenges:

How do you get consumers to abandon their perfectly fine cars and buy a new one?
How do you turn a product that competed on price and features into a need?

In another stroke of genius, GM invented the annual model change. Sloan borrowed this idea from fashion where styles changed every year and applied it to automobiles starting in the 1920s. General Motors would change the external appearance of cars every year. Sloan preferred to call it “dynamic obsolescence.”

Styling and design became an integral part of GM’s strategy. Sloan hired Harley Earl to set up GM’s in-house styling staff. Earl would run it from 1927 to 1958.

Before Earl, cars were designed by in-house body-engineers who focused on practical issues like function, costs, features, etc. Each exterior component was designed separately to be functional – radiator, bumpers, hood, passenger compartment, etc. Some companies used 3^rd party bodymakers to set the style , but GM was the first to take car design away from the engineers and give it to the stylists.

The concept of yearly “improvements”, whether styling or incremental technology improvements, every model year gave GM an unbeatable edge in the market. (Henry Ford hated the idea. He had built Ford on economies of scale – the Ford Model T lasted for 19 years.) Smaller car makers could not afford the constant engineering and styling changes they had to make to keep competitive. GM would shut down all their manufacturing plants for a few months and literally rip out the tooling, jigs and dies in every plant and replace them with the equipment needed to make the next year’s model.

GM had figured out how to take a product which solved a problem – cheap transportation – and transform it into a need. It was marketing magic that wasn’t to be equaled until the next century.

By the mid-1950′s every other car company was struggling to keep up.

Mass Marketing Starting in the 1920’s and continuing for the next half century, automobile advertising hit its stride. Ads emphasized brand identification and appealed to consumers’ hunger for prestige and status. Advertising agencies created catchy slogans and jingles, and celebrities endorsed their favorite brands. General Motors turned market segmentation and the annual model year changeovers into national events. As the press speculated about new features, the company’s added to the mystique by guarding the new designs with military secrecy. Consumers counted the days until the new models were “unveiled” at their dealers.

Results
For fifty years, until the Japanese imports of the 1970’s, Americans talked about the brand and model year of your car – was it a ’58 Chevy, ’65 Mustang, or 58 Eldorado? Each had its particular cachet, status and admirers. People had heated arguments about who made the best brand.

The car had become part of your personal identity while it became a symbol of 20^thCentury America.

After Sloan took over General Motors its share of U.S cars sold skyrocketed from 12 per cent in 1920, until it passed Ford in 1930, and when Sloan retired as GM’s CEO in 1956 half the cars sold in the U.S. were made by GM. It would keep that 50% share for another 10 years. (Today GM’s share of cars total sold in the U.S. has declined to 19%.)

How the iPhone Got Tail Fins
Over the last five years Apple has adopted the GM playbook from the 1920′s – take a product, which originally solved a problem – cheap communication – and turn it into a need.

In doing so Apple did to Nokia and RIM what General Motors did to Ford. In both cases, innovation in marketing completely negated these firms’ strengths in reducing costs. The iPhone transformed the cell phone from a device for cheap communication into a touchstone about the user’s image. Just like cars in the 20th century, the iPhone connected with its customers emotionally and viscerally as it became a symbol of who you are.

—-

The desire to line up to buy the newest iPhone when your old one works just fine was just one more part of Steve Jobs’ genius – it’s how the iPhone got tail fins.

It’s one more reason why Steve Jobs will be remembered as the 21st century version of Alfred P. Sloan.

Filed under: Big Companies versus Startups: Durant versus Sloan, Technology

How the iPhone Got Tail Fins – Part 1 of 2

2011-10-18T12:30:45Z

It was the most advanced consumer product of the century. The industry started with its innovators located in different cities over a wide region. But within 20 years it would be concentrated in a single entrepreneurial startup cluster. At first it was a craft business, then it was driven by relentless technology innovation and then a price war as economies of scale drove efficiencies in production. When the market was finally saturated the industry reinvented itself again – one company discovered how to turn commodity products into “needs.”

They opened retail outlets across the country and figured out how to convince consumers to flock to buy the newest “gotta have it” version and abandon the perfectly functional last year’s model.

No, it’s not Apple and the iPhone.

It was General Motors and the auto industry.

In the Beginning
At the beginning of the 20^th century the auto industry was still a small hand-crafted manufacturing business. Cars were assembled from outsourced components by crews of skilled mechanics and unskilled helpers. They were sold at high prices and profits through nonexclusive distributors for cash on delivery. But by 1901, Ransom Olds invented the basic concept of the assembly line and in the next decade was quickly followed by other innovators who opened large scale manufacturing plants in Detroit – Henry Packard, Henry Leland’s Cadillac, and Henry Ford with the Model A.

The Detroit area quickly became the place to be if you were making cars, parts for cars, or were a skilled machinist. By 1913 Ford’s first conveyor belt-driven moving assembly line and standardized interchangeable parts forever cemented Detroit as the home of 20^th century auto manufacturing.

Feature Wars
The automobile industry was founded and run by technologists: Henry Ford, James Packard, Charles Kettering, Henry Leland, the Dodge Brothers, Ransom Olds. The first twenty-five years of the century were a blur of technology innovation – moving assembly line, steel bodies, quick dry paint, electric starters, etc. These men built a product that solved a problem – private transportation first for the elite, and then (Ford’s inspiration) – transportation for the masses.

Market Saturation
Ford tried to escape the never-ending technology feature wars by becoming the low cost manufacturer. Fords River Rouge manufacturing complex – 93 buildings in a 1 by 1.5 mile manufacturing complex, with 100,000 workers – vertically integrated and optimized mass production.

By 1923, through a series of continuous process improvements, Ford had used the cost advantages of economies of scale to drive down the price of the Model T automobile to $290.

When the 1920’s began there were close to a 100 car manufacturers, but the relentless drive for low cost production forced most of them out of business as they lacked capital to scale. For a brief moment, half the cars in the world were now Fords. To make matters worse, the long service life of Ford and GM cars (8 years for Fords Model T, 6 years for everyone else) retarded sales of new cars. In 20 years, U.S. car ownership had risen from 0 to 80% of American families – the market was approaching saturation.

Now cars would have to be sold almost entirely to people who already owned a car.

The Crazy Entrepreneur
After success as a leading manufacturer of horse-drawn carriages, Billy Durant was one of the few who saw the writing on the wall and got into the car business. Although he wasn’t a technologist, he was an entrepreneur with a great eye for acquiring car companies run by technologists. His keen insight was that several carmakers combined under one company umbrella would have more growth potential than one brand on its own. Like most founders, he was great at searching for a business model but terrible at in large company execution. When his board fired him, Durant bought a competing company called Chevrolet, built it larger than his last company, and used Chevy stock to buy out his old company – General Motors – and threw out the board. Yet a few years later under his brilliant but reckless leadership GM was again on the brink of financial disaster and his new board fired him. (Durant would die penniless managing a bowling alley.)

Durant’s ultimate replacement – an accountant named Alfred P. Sloan – would turn GM into the leading and most admired company in the U.S.

Relentless
Over the next decade Sloan would implement a series of innovations which would last for over half a century. And catapult General Motors from the number 2 car company (with a ¼ of Ford’s sales) into the market leader for the next 100 years. Here’s what he did:

Distributed Accounting Unlike Ford, GM was originally a collection of separate companies. Distributed Accounting turned those fiefdoms into product divisions each of which, could be focused like Ford’s mass-produced lines. But Sloan went further. He figured out how to centralize financial oversight of decentralized product lines. His CFO created standardized division sales reports and flexible accounting, and allocated resources and bonuses to the GM divisions by a uniform set of rules. It allowed GM to be ruthlessly efficient internally as well with its dealers and suppliers. It got the division general managers to fall in line with corporate goals but allowed them to run their divisions freely. GM became the prototype of the modern multidivisional company.

Car Financing. Realizing that Ford would only accept cash for car purchases, in 1919 GM formed GMAC to provide new car buyers a way to finance their purchases through debt.

Consumer Research. Every since his days at Hyatt Roller Bearing, Sloan, and by extension GM, was relentless about getting out of the building – they had an entire department that studied consumers, dealers, suppliers. More importantly, Sloan led by example. He visited dealers and suppliers, listened to customers and was tied tightly to his head of R&D Charles Kettering.

All this would have made General Motors a well-run and well-managed company. But what they did next would make them the dominant company in the U.S. and eventually put tail-fins on the iPhone.

Part 2 explains it all.

Filed under: Big Companies versus Startups: Durant versus Sloan, Technology

Does Amazon Want to Monopolize The Entire Publishing Chain?

2011-10-13T10:20:28Z

The launch of Amazon's Kindle Fire at a price well below expectations has naturally focused people's attention on the e-book side of Amazon's operations, and the likely effect of the extended Kindle family on other publishers trying to go digital. But something else is happening at the other end of the publishing chain that could well disrupt the industry just as much, if not more: Amazon is becoming a major publisher in its own right.

Things began back in May 2009, when it launched AmazonEncore:

a new program whereby Amazon uses information such as customer reviews on Amazon websites to identify exceptional, overlooked books and authors that show potential for greater sales.

After this low-key start, Amazon added others imprints, including AmazonCrossing (foreign books in translation), Powered by Amazon (short books), Montlake Romance (romantic fiction), Thomas & Mercer (mysteries and thrillers) and, most recently, 47North (science fiction, fantasy and horror) - the last of these with some eye-catching authors:

47North launches with 15 books, including "The Mongoliad: Book One," the first in the ambitious, five-book, collaborative Foreworld series led by Neal Stephenson and Greg Bear. All of these books will be available to English readers in Kindle, print and audio formats at http://www.amazon.com, as well as at national and independent booksellers. 47North will publish original and previously published works, as well as out-of-print books.

Meanwhile, back in May this year, Amazon hired a publishing industry veteran to become VP, Publisher of Amazon Publishing’s New York office:

Amazon.com has taken its most aggressive step yet toward competing head-on with traditional publishers: It’s hired Larry Kirshbaum, a literary agent and the former CEO of Time Warner Publishing Group (now Hachette Book Group), to start a general trade imprint.

Until now, Amazon’s imprints have focused on genre fiction like mystery and romance. By hiring a high-profile industry veteran to focus on “quality books in literary and commercial fiction, business and general nonfiction”—and by releasing those books in both print and digital formats—Amazon is announcing itself as a serious competitor against the “big six” traditional trade publishing houses.

Put all these imprints together, plus Amazon's main sales sites around the world and the Kindle e-readers range, and you have a fully-integrated global publishing strategy.

It's hard to see how traditional publishers can respond. They may have impressive back catalogs, and established links with leading authors, but Amazon has the distribution network and growing success in e-book publishing. Above all, the trade publishing houses seem to lack Amazon's ambition: it looks like it doesn't just want to make money from the entire publishing chain, it wants be the entire publishing chain.

Follow me @glynmoody on Twitter or identi.ca, and on Google+

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Announcing Step2 -- Our New Platform For Helping Creators Succeed

2011-10-12T16:20:34Z

Today we're extremely excited to announce the launch of Step2, our discussion platform for helping creators, fans, techies, business folks and anyone else work together to help creators figure out ways to better succeed with their efforts. It's been nearly three years since I first did my MidemNet presentation that discussed the idea of Connecting with Fans + a Reason to Buy = Business Model -- better known as CwF+RtB=$$$. Since that time, I've spent plenty of time writing, speaking, consulting and thinking about this concept and have tried to outline it in as much detail as possible. Still, I can't even begin to say how many times I've had content creators -- be they musicians, filmmakers, authors, software developers, photographers, poets, painters, etc. -- reach out and ask what should they do to better connect with fans? What should they do to come up with better reasons to buy? I've tried to help them whenever possible to the extent that I can, but each situation is unique. Nothing in CwF+RtB was supposed to about "here's the exact path to success." It was a set of principles, and each person/organization could apply it appropriately to their circumstance.

In thinking about this, we realized that what's really missing out there is a true community to help people figure this stuff out. There's really no great place for a content creator to ask people how can they better connect with a fan base. There's really no great place out there for an artist to compare different store hosting platforms to see which ones might serve their needs better. There's really no great place out there for someone to figure out just how should they set up this business model/online store/crowdfunding campaign. And there's no great place for fans to reach out and help the creators they love as well with these same sorts of questions.

So we built one.

There's a famous internet meme out there that began with a South Park episode many years ago, which has become known as the "Profit!" meme, which goes something like this:

Step 1: Do something
Step 2: ??????
Step 3: Profit!

At times, I know that's how many content creators feel about the range of opportunities that the digital age presents them. So, our Step2 platform is hopefully designed to help creators make those question marks in their own "Step 2" a bit more clear and useful.

So how can Step2 be used? Well, that's partly up to the community to decide! But here are some suggestions:

Content Creators:

Ask the community how to better succeed -- whether it's to better connect with fans or to come up with unique and compelling business model ideas.
Discuss challenges or choices you're facing and get feedback. What platforms make sense? Should you focus on touring or build a local fan base? Should you self-publish or try to get a publishing deal? Can you really crowdfund this movie? etc.
Share your experiences as a case study. To get feedback and to help others learn from and be inspired by your experiences. In a little while we'll be posting about a contest we're launching in conjunction with the Step2 launch, where we're offering up a total of $10,000 to people for sharing their case studies. For a few great examples of case studies, check out:
1. Amanda Palmer discussing her recent experiences with Kickstarter in funding a new project in conjunction with her husband, Neil Gaiman.
2. Or, check out Andy Richards of the indie band Uniform Motion (whom we've written about a few times), discussing how his transparency about their revenue may have given fans additional reasons to buy, complete with detailed stats about how his transparency resulted in traffic and sales.
3. Or you can jump over to Zoe Keating's discussion over the question of whether or not doing art for purely strategic reasons is evil... while she also shares a bit of the secret of her success.

Fans:

Share your own case studies as a fan. Show artists how it feels to have an artist treat you well, and highlight cool examples of artists that have connected with you. Inspire more artists.
Want to help out your favorite artist? Start a discussion about cool things they're already doing and encourage more people to check them out.
See someone you like who you think could do better? Make some suggestions about ways they could do even better.
See someone you like doing something you don't like? Maybe present some alternative ideas

Everyone:

This is a community project. Even if you don't know some of those participating, you'll be amazed at how gratifying it is to try to help people succeed with their work. While I haven't had time to help as many content creators as I would have liked, every time I'm able to spend some time helping artists, it's always been a very rewarding experience.
Help people recognize that there's a world of opportunity out there, and there are all sorts of great ways to embrace it and to succeed. Talking to folks who succeed today, you almost inevitably hear a variation on the theme that they saw someone else succeeding and were inspired to know that they could do that too.

To be clear: while we often talk about music, this is about all sorts of creators. Music, movies, videos, software, photographs, poetry, web pages, companies, blogs, magazines... whatever. Jump in and start discussing, sharing and spreading ideas.

Special Thanks!:

First off a special thanks to our awesome sponsors for this project, from whom you'll be hearing more as Step2 moves forward. TopSpin provides an amazing platform for content creators to connect with fans and give them a reason to buy. Its platform is used by big name artists like Eminem, Lady Gaga, the Beastie Boys and Paul McCartney, as well as tons of up and coming artists. And it's not just for music. They're powering sites for the likes of filmmaker Kevin Smith and are working with authors as well. We'll be seeing more details and case studies from folks associated with TopSpin in the near future. Then we have the Future of Music Coalition, who has been doing all sorts of wonderful things helping musicians deal with a changing market. Their latest project (again, which you'll be hearing more about) is the massive artist revenue streams project, in which they're gathering data from tons of musicians to better understand all revenue streams for artists these days. SongKick is an amazing new platform that is really doing cool things for the touring industry, and has some amazing insight into that important revenue stream for musicians, which we'll try to delve into on Step2. And last, but certainly not least, is Bandzoogle, a website platform for content creators that makes it easy for creators to build extremely powerful (and profitable) websites. As we recently noted, artists using Bandzoogle are making a lot of money, and we're looking forward to finding out more about how they do that.

Also, a special thanks to the crew here at Floor64 for the hard work in putting all this together and iterating on the original idea and turning it into a reality. Finally (and perhaps most importantly) an extra special thanks for the community of folks out there who have bandied about many of the ideas about how to connect with fans, and how to build cooler, better business models that inspired us to put together this platform.

So go ahead, jump in, join some existing discussions, start some new discussions, and let's help create and document as many success stories as we can.

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Counterintuitive: How Netflix Letting You Keep Movies Longer Decreases The Number Of DVDs It Needs

2011-10-08T02:39:00Z

It's always fun to recognize how some initially counterintuitive logic makes sense. A new paper looking at Netflix's (er... Qwikster's) early decision that it would let people keep movies as long as they wanted, discovered that this policy didn't just help Netflix from a marketing perspective, but also meant that Netflix had to buy fewer DVDs than if it had imposed time limits and late fees. This seems counterintuitive. After all, if people can keep DVDs forever, there's greater uncertainty, and Netflix could, theoretically, send out a disc and never see it again. So you might think it would need to stock up in order to account for these huge chunks of time that people might keep DVDs.

The problem with that thinking is that it's only looking at the "market" for a single DVD, rather than the larger market of all of Netflix's DVDs, and the kind of demand patterns it would expect. The researchers looked at that, and noted that by letting people keep DVDs longer, it actually slows down the rate at which they take out new DVDs, which decreases the amount of DVDs Netflix needs. In other words, if there's a time limit, people would return DVDs faster, meaning that Netflix would have to send another one out faster. This problem becomes especially noticeable for "hot" movies, like new releases:

To understand how Netflix actually profits from uncertainty, it is helpful to imagine a handful of idealized Netflix customers, as Bassamboo and his colleagues do in their paper. The only thing all the customers have in common is that when a hot new movie comes out, they all want it. If Netflix imposed late fees on its customers, the company could be sure that every customer who wanted a particular new release would return their last-viewed movie, and automatically be sent that new release, within a narrow window of a few days.

Bassamboo and his colleagues discovered that for a hypothetical Netflix-like service with late fees, the company would have to stock as many copies of a new release as it has customers. Given that all those customers would probably only rent it once, the company would be hard-pressed to either remain profitable or offer a compelling subscription fee.

On the other hand, when Netflix allows customers to keep DVDs indefinitely, the point in time at which they return old discs and automatically request a hot new release is staggered. Some customers are going to return a disc the day a new release comes out, while others will take a few days or even weeks to return their last movie and request the new one. The longer customers wait to request that next disc, the more times Netflix can rent out individual copies of its new releases. It is this re-use of discs, or “multiplexing,” that makes the Netflix model possible.

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The 10x Product Launch

2011-10-04T12:43:23Z

You’ve painstakingly defined and built an MVP through 100+ customer interviews. You’ve collected thousands of emails from potential prospects through a teaser page. You’re ready to launch. But…

The engineer in you is worried about some real technical risks. You’re pushing the envelope using a new type of database – is the database partitioned correctly, will it scale, should you wait and run more tests first?

The marketer in you is worried about your pricing and positioning – can you justify charging for your MVP, are you delivering enough value, have you picked the right price, maybe you should wait to add a few more features, or defer charging to later?

A popular solution is launching as a “private beta” – allowing you to incrementally rollout your product, keep early customer expectations at bay, and defer the pricing question under the guise of gaining more learning first. While this approach certainly appeases our inner fears, it is often the cop-out approach.

The purpose of the MVP is getting your product in front of customers to start the process of learning but not all learning is equal. You need to prioritize learning around the riskiest parts of your product first.

For most products, technical risk ain’t what’s riskiest.

Launching a new product can be daunting because you have to simultaneously juggle multiple product, customer, and market risks. I’ve been fielding some of these tradeoffs lately with the upcoming launch of a new SaaS product – USERcycle, and devised the following 10x launch plan.

The 10x Product Launch Plan

Here’s the general idea:

Like the “private-beta”, the 10x launch uses a staged rollout. But unlike the private beta, it completely avoids any connotations around “being in beta”. You have to both demonstrate strong product conviction and be ready to rigorously test those convictions from day one.

Additionally, the staged rollouts use a logarithmic step function (10x) that affords the right prioritization of risk at each stage.

What is the right prioritization of risk?

The Lean Canvas below charts the path I use for systematically tackling the 3 types of risks:

Product Risk – Getting the product right

1. First make sure you have a problem worth solving.
2. Then define the smallest possible solution (MVP).
3. Build and validate your MVP at small scale (demonstrate UVP).
4. Then verify it at large scale.

Customer Risk – Building a path to customers

1. First identify who has the pain.
2. Then narrow down to early adopters who really want your product now.
3. It’s okay to start with outbound channels.
4. But gradually build/develop scalable inbound channels – the earlier the better.

Market Risk – Building a viable business

1. Identify competition through existing alternatives and pick a price for your solution.
2. Test pricing first by measuring what customers say (verbal commitments).
3. Then by what they do.
4. Optimize your cost structure to make the business model work.

Putting 10x in Action

Stage 1: Use interviews to recruit 10 early adopter customers

Use problem interviews to find a problem worth solving and identify your prototypical early adopter.
Put up a “problem focussed” teaser page and start collecting email addresses.
Use solution interviews to define your MVP and recruit your first 10 “early adopter” customers (not users) – they pay you from day one. If you nail the right problem, this shouldn’t be difficult. Make a bold promise, keep pricing simple, and back it up with a high-touch concierge MVP model and/or money-back guarantee.
Build your MVP and validate that is delivers on your Unique Value Proposition.

What’s happening here?

The first objective is finding motivated early adopters not on-the-fence users.
Early adopters are as visionary as you but from the problem perspective.
Customer interviews are a great way for qualifying early adopters.
Plan on talking to 100 prospects to find the right 10 early adopters.
Starting with just 10 customers defers technical risk for testing market risk.
First key metrics: activation, retention (and revenue).

Stage 2: Use email list to find next 100 customers

Use your 10 early adopters to help find the next batch of customers (they pay you too).
Supplement the rest by setting up more solution interviews using your email list.
Collect customer testimonials / case-studies.
Start building a marketing website.

What’s happening here?

Exercise full AARRR user lifecycle (adding referral) to validate compelling UVP.
Test early channels for user acquisition.
Use refined positioning and social proof to build a compelling marketing website.
Plan on 1,000 person email list to yield 100 customers.

Stage 3: Use marketing website to acquire next 1,000 customers

Use your marketing website to sign-up users.
Use your learning to define multiple pricing plans including a freemium option if one makes sense.
Manage the full user lifecycle from visitor to sign-up to paid.

What’s happening here?

Strong early adopter testimonials should help drive latter stage customers.
Usage patterns of existing customers help define optimal pricing plans.
Move towards a more automated self-serve model.
Start tackling scaling risks.

Stage 4: Build your engine of growth for next 10,000 customers

Start testing other customer acquisition channels.
Optimize cost structure.
Optimize AARRR funnel.

What’s happening here?

Product/Market Fit
Shift from finding a plan that works to accelerating that plan

Why 10x works?

Maximize learning (about what’s riskiest) per unit time.

You don’t need a lot of users to learn. Just a few good customers.

If you can’t convert a prospect in a 20 minute face-to-face meeting, it’s much harder to convert an unaware visitor in 8 seconds on your landing page.

Pricing is not only part of the product but defines your customers.

Start building a path to customers from day one – start direct to maximize learning before automating.

Disclaimer

This 10x Product Launch strategy is only partially implemented at this stage with the USERcycle launch. USERcycle is a B2B SaaS product but I believe this launch strategy should work as well for a B2C product as long as you stay on the left-hand side for a while i.e. acquire users in steps of 100, 1,000, 10,000, 100,000, 1,000,000, etc.

Whatever comes out of this experiment, I will share my learning along the way. In the meantime, please share your comments below…

Mastering Gamification by Gabe Zichermann [video]

2011-09-30T15:53:01Z

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