Fast boat, fast river

Paul Graham has a simple definition of a startup: an organization designed to grow fast. Steve Blank adheres to a different one: an organization formed to search for a repeatable and scalable business model.

They’re both right, in a way. And that has important implications for entrepreneurs

Many people think a startup is a small business. It’s not. A small business is a small business, and if you want to change that, you’ll have to follow both Paul and Steve’s advice: start searching for a sustainable business model that can grow fast.

Paul’s view

Let’s talk about Paul’s view first. He explains that while tech companies aren’t necessarily startups—Dell and Microsoft aren’t growing rapidly—startups might necessarily be tech companies. That’s because fast growth happens either from a big market shift, or from a dramatic lubrication of a market. Technology causes both huge shifts and copious amounts of lubrication.

  • Tectonic changes in the market: Consider Google or Dropbox. They grew fast because of a huge, irresistible shift—the use of the web, or the willingness of the average person to store data in the cloud. There are plenty of other reasons they grew, but they were part of a rapidly expanding total addressable market. The market they targeted came out of nowhere, and grew very, very fast. If startups are boats on a river, then these ones are going fast because the river’s a rushing torrent.
  • Reduction of friction in the market: Now consider Über or Groupon. There’s nothing necessarily disruptive about taxi services or coupon clipping. Those are slow rivers. But both companies found ways to lubricate the inherent friction in their markets: smartphone-equipped limos; or social sharing with a threshold incentive. These are the fast boats.

Put another way, startups move fast downriver, either because they’re on a really fast river, or because they have a motorboat and everyone else is in a canoe. Graham thinks (and I agree) that to achieve fast growth, most of the time you need a low-cost, short-cycle-time mechanism. And that’s usually software, because humans make bad processes. As Andreesen said, software eats everything. People retire; software gets upgraded.

Steve’s view

Okay, on to the other definition. Startups are searching for a scalable and repeatable business model. To me, that means it’s sustainable without the direct involvement of the people who created it, because founders don’t scale.

A startup is not a lifestyle business. A startup does not mean consulting. It does not mean bespoke.

Etsy is sustainable; one-off quirky knitted sweaters are not. Etsy is software; sweaters are slow, messy, hard-to-scale wool. Sustainable, to me, means that as the business grows, the incremental cost of acquiring additional revenues or customers descends towards zero.

A few months ago, I wrote about a hairstylist who’s setting out on her own. She’s a small business owner. She can learn plenty from Lean methodologies about how to improve her business, just as Fortune 500 companies can improve their competitiveness by using Lean approaches. But she’s not a startup by either Steve or Paul’s definition.

Since Paul mentioned a barber shop as an example of a not-startup, I wondered, “what would a hairstylist need to do to become a startup?” They’d have to be searching for a sustainable business model that could grow fast, probably because of a new market or a lubricant that changes the economics of an existing one in an important way.

Consider some of the ways a hairstylist might try to launch a startup, based on their domain expertise. They could focus on a market that they feel is growing quickly; or on a technology that makes new products possible.

Your source of growth drives your metrics

The source of your growth will influence the kinds of metrics you measure, and which you consider riskiest, and how much of your product or service needs to be built before you can test it. Some of these business models are SaaS; some are e-commerce; some are user-generated content. Each makes money in different ways: subscriptions; transactions; advertising. And all of that drives the One Metric That Matters for these companies.

Growing market (fast river)

If you choose to innovate by focusing on a growing market (fast river), then most of your risk is about whether you can capture that market. You’ll need a really good go-to-market strategy, because you’re not really doing anything new (you’re still cutting hair, just not in the traditional walk-in hair salon way.) You’ll care about exclusivity, partnerships, and existing competitors going after the same blue ocean.

Exclusivity means you’re the only one on the fast river. Partnerships mean that others already on the river help you get there. And competitors reduce your advantage, since they have the same fast waterway as you. The longer you can stay on a fast river, the better—but these days, it’s a fair bet that competitors will quickly copy you. Worse, several Internet giants (Google, Facebook, Twitter, etc.) are really, really good at fast rivers, since they run the underlying infrastructure. They shape the riverbed, and can divert the river’s course or slow the river to their advantage—think Twitter changing its APIs, or Facebook blocking an app’s access to its graph.

(It should be noted that neither home visits nor AirBnB haircuts are growing fast enough to qualify for Paul’s “designed for rapid growth.” That kind of growth takes something truly new, and often exploding because of network effects: the phone system, the Internet, credit cards, television, the printing press.)

Disruptive technology (fast boat)

If you choose to innovate by focusing on a disruptive technology (the fast boat in this analogy), you’re going to care more about whether you can build and run it; whether it will work and easily replace existing solutions; and whether it will really go as fast as you think it will.

The “can you build it?” question is true only of genuinely innovative technology, and often your adoption will come from patents or the barriers to entry that you create because of your invention.  Your risk is that your Arduino/Dyson/Kinect Frankenscissors might not work.

Invention is a special segment of the startup world, and its value comes from an ability to demand high margins because of the advantage the product conveys to those who use you. For example, a chip manufacturer that increases network performance tenfold charges far more than the cost of making a chip, because of the value it conveys to network infrastructure that uses it.

The “will it work?” question is about substitution. If people won’t consider your offering a viable substitute, it’s no good. If Über cars weren’t widely available at launch, they wouldn’t be a viable alternative to taxis—which is why Über paid drivers $30 an hour to sit idle when they first launched. They basically rented a city’s population of limos until their demand took off. A good rule of thumb is that something must be ten times better than the alternative. Humans have intertia, and incumbents have inertia, and you need to overcome both.

The “speed” question is about being able to achieve the volume and cycle time you expect. Let’s say you think you can do a perfect haircut in 30 seconds because of your new hair-cutting invention, which will give you a 60-fold increase in productivity. You’re still running a salon. Your business hasn’t changed (much.) But there’s real risk that some other element of your business model (say, reservation management) becomes a bottleneck that prevents growth.

Both at once

If you’re doing both (new idea in a new market—fast boat on a fast river) you’ve got even more risk, because you have to focus on market fit and product fit. The best companies do this:

  • Microsoft’s Windows was a motorboat, and the home PC was a fast river.
  • Credit cards were a motorboat, and the rise of consumer banking was a fast river.
  • Google’s Pagerank was a motorboat, and the rise of the consumer web was a fast river.

But it’s taken an amazing amount of dexterity for these companies to stay around, and they’ve had to adjust constantly. Microsoft nearly steered their motorboat into the shore when the Web happened, and it took a draconian intervention by Bill Gates to get them back on course. David Allen explains this history in his consequences of state interference and non-interference.

Coming upon this scene about two years ago, in late 1995, Bill Gates found that his Microsoft was caught flat-footed. The company’s cash flows were tied to desktop computing, but there was a fundamental shift underway, toward networked computing. Remarkably, among many such performances by the man, he turned his leviathan virtually “on a dime” and steamed it off in relentless and vigorous pursuit of the Internet.

In other words: Beware the founder claiming to have a fast boat on a fast river.

Startups aren’t easy

It should be obvious that I’m not suggesting anyone go launch Airbnb for haircuts and the other business models I’ve mentioned here. These are bad examples. That was precisely the point of Paul’s post:

…if you want to start a startup, you’re probably going to have to think of something fairly novel. A startup has to make something it can deliver to a large market, and ideas of that type are so valuable that all the obvious ones are already taken.

That space of ideas has been so thoroughly picked over that a startup generally has to work on something everyone else has overlooked.

The issue here isn’t that a hairstylist couldn’t launch a startup. It’s that the realm of hairstylist-related innovations is relatively small, and unlikely to yield something fast-growing in a big market. That’s why good ideas are scarce, and investors snap them up for what seem like unreasonable valuations. A speedboat on a fast river is a rare thing indeed, and they all want to get on board.

So consider this corollary: Invest in the founder who’s found a fast boat on a fast river, and whose idea seems daft at first and obvious in hindsight.

A conscious decision

Many entrepreneurs delude themselves into thinking they’re building startups, when in fact they’re building businesses. There’s nothing wrong with building businesses. In fact, it’s amazing. The hairstylist isn’t a startup founder, she’s a small business owner, and that’s fine. She has many of the same problems, but she isn’t girding herself for fast growth or searching for a sustainable, repeatable model.

What a lot of entrepreneurs who run lifestyle businesses don’t get is this: if they become a startup they’re quitting their job. They’re shutting down the current business (or finding someone to run it for them as a cash cow) and launching an entirely new one. None of the companies in my nonsense example above are a hairstylist—they’re a reservation platform, or a haircutting machine, or an iPhone app.

Until they mentally “quit” their lifestyle-oriented, slow-growth, unsustainable, unrepeatable jobs, they’ll never turn their businesses into startups. And that’s one reason why it’s so hard for small business owners to become startup founders.

They need to change jobs.

Siliconangle at Strata

Last week was Strata, O’Reilly’s conference on Big Data, ubiquitous computing, and new interfaces. While most of the discussion focused on the event itself—and the widespread adoption of Big Data—I got a chance to talk Lean Analytics with the Silicon Angle crew who were covering the event.

The 7 Myths of Lean and How Analytics Can Help

I recently did a presentation on the 7 myths of Lean Startup and how analytics can help. You’ll find it embedded below, since I’ve shared it on Slideshare.

It was a fun presentation, the first time I’ve given it (since I often redo my presentations each time!) and I got some great feedback. Briefly, here are the 7 myths:

  1. Lean = Cheap. Sure it’s cheaper to start companies but it still costs money to scale them. The lesson is simply this: know when to hack (do something quick, cut corners, cheaply) and know when to scale.
  2. Lean = Small. You need a big vision to win. I’ve said that before. And you use Lean Startup best practices and analytics to zig zag your way towards that vision.
  3. Lean = Crappy. An MVP is meant to be a minimalistic version of your product, but it also has to be viable. The key is that an MVP has to provide you with meaningful learning and insights, and it also has to provide the value you’ve promised customers. There’s no “shitty” in MVP and I use Sincerely, Inc. as a great example of building smart MVPs.
  4. Pivot is a bad word. I did an entire presentation just on pivots and brought some of that into this presentation. The key to a pivot is that it’s a shift in one aspect of your startup’s focus based on validated learning.
  5. Lean is only for consumer startups. Lean Startup has gained most of its adoption amongst consumer startups, but it applies across the board. I shared some quick examples from consumer products companies, a church, a restaurant and more. Many of these examples are in the book.
  6. Lean = Easy. We all know startups are hard. Lean Startup helps mitigate risk and clear the path a bit more, but it’s not easy. And that flows into the final myth…
  7. Lean = Auto win. Simply by following the Lean Startup steps (or Lean Analytics methodologies) doesn’t guarantee success. You can’t walk through the process and expect to win. It takes guts, luck, brains and much, more more.

I hope you find the presentation helpful. I also shared some thoughts about how I believe metrics can be the common language used by entrepreneurs and investors to bring them together more often than not and keep them on the same side of the table. It’s clear that entrepreneurs are concerned about reporting numbers to investors, and it’s clear investors want more numbers.

Metrics –used properly– can cut through a lot of bullshit on both sides, which I think is a good thing if everyone is willing to participate. If you have any questions about the presentation or what I rambled on about during my talk, please let me know!

Analytics Lessons Learned: Free e-book with 13 case studies

The book is coming soon! It will be available in March from a variety of places.

You can pre-order it on Amazon so you get it as soon as it’s ready. We hope you’ll do that!

Analytics Lessons LearnedIn the meantime, we wanted to share some great stories from the book (and some that aren’t in the book), so we’ve put together an e-book called Analytics Lessons Learned.

The e-book is free! Just sign-up to get it below.

The e-book includes case studies from a variety of companies including Airbnb, SEOmoz, Backupify, Sincerely, Swiffer and EMI. The companies are at various stages — some are still building an MVP, others are large, multi-billion dollar corporations. And we even have a church in there! Yup, Kingsway Church, thanks to the amazing work of Dr. Ernie Prabhakar, is converting and applying Lean principles and Lean Analytics to how they operate. We were first connected to Ernie through his blog where he talks about how churches need to get more practical and analytical to succeed.

The book, Lean Analytics, has over 30 case studies, so this is just a taste of what we’ve been working on. But we’re confident you’ll find a lot of value in these stories, and look forward to your feedback.

So with that, please check out Analytics Lessons Learned by signing up below. Thank you!

* Signing up adds you to our email newsletter list. We’ll send you the e-book immediately, and only send occasional emails after that.

Lean Analytics workshop at the Lean Startup Conference

Yesterday, Alistair and I did our first workshop at the Lean Startup Conference. The event itself was fantastic. I thought the content from the speakers was incredible.

The workshop was a fairly deep dive into the content of the book. The process of converting the book to slides started with Alistair making nearly 400 slides. We condensed that down to 166 slides, which is still a lot of content, but we felt it was manageable. We didn’t get through all of it, but that’s OK. The interaction with participants was great. We got some amazing, important questions and lots of insightful and meaningful feedback. So thank you to everyone that attended.

We’ve uploaded the presentation to Slideshare and included it below. Hopefully it helps those that attended with remembering what we talked about, and for those of you that weren’t there it’s going to give you a great sneak peek into the book.

As well, it’s now possible to pre-order the book from Amazon: Get Lean Analytics now!

When you pre-order the book it will be delivered to you as soon as the book is released (which should be in March/April 2013.) Thank you!

An Introduction to Lean Analytics Webinar

Recently, I did a webinar through O’Reilly on Lean Analytics. It was an introductory guide, covering a lot of what we’ll be including in the book. I got some great questions as well, which validated some of what Alistair and I have been thinking about content-wise for the book; where we need to include more information and address specific concerns people have. For example, I got asked a few times about how Lean Startup and Lean Analytics applies to enterprise startups and companies. I also got asked how to know if you’ve hit product-market fit.

The presentation is now on Slideshare and embedded below:

As well, you can get a recording of the event here: (requires registration) The webinar follows the basic structure of the book (although at a much higher level.)

Incidentally, you can get the Early Release here:

The Early Release does get updated as we write more content and submit it to O’Reilly. Right now it’s quite short, but you can expect an update that has ~60% of the book (unedited) soon. So if you get the Early Release, you will get updates and more content and you’ll have a pretty good idea of what the final version will look like. Having said that, Alistair and I are still writing tons, editing and iterating.

What’s in a name?

As we’ve shared the idea of Lean Analytics, we’ve obsessed—as most authors do—with naming. When I co-wrote Complete Web Monitoring a few years ago, I talked to a friend of mine, author Mitch Joel, about its initial name: Watching websites. Ultimately, my co-author Sean and I decided that name would be misinterpreted as a book on online video streaming, and went with the more descriptive (but less sexy) title Complete Web Monitoring. When Mitch heard this, he shook his head in dismay: he thought that by clarifying what the book was, we’d dramatically reduced its audience to a particular subset.

Every author wants an Airport Book. This is the kind of book that fills the racks in an airport bookstore. It makes you feel smarter for having bought it. It’s packed with little gems you can share at conferences. And it’s often got a compelling title: Made To StickSwitchLean Startup. One-word titles, with few syllables, that have a verb in them, do well.

It turns out there is, and isn’t, a lot of research behind a successful title. There’s plenty of data on book sales, of course—so much that publisher Lulu even has a title-scorer app that uses research on bestsellers to predict (in a tongue-in-cheek way) what chance a title has of becoming a bestseller.

The advent of the electronic book, and its accompanying electronic bookstore, helps collect data on what people browse, and can give a publisher early indications of success in real time.

Electronic bookstores have also polarized purchasing: getting featured in online stores is key to success, as is getting mentioned by the Oprah of your particular industry (or, for that matter, Oprah.) Unfortunately, the choice of title, cover art, and other aspects of a book remain somewhat of a dark art for traditional publishers. This New York Times piece explains it in detail.

Most in the industry seem to see consumer taste as a mystery that is inevitable and even appealing, akin to the uncontrollable highs and lows of falling in love or gambling.

Eric Simonoff, a literary agent at Janklow & Nesbit Associates, said that whenever he discusses the book industry with people in other industries, “they’re stunned because it’s so unpredictable, because the profit margins are so small, the cycles are so incredibly long, and because of the almost total lack of market research.”

As analytics types, we don’t like this. My biggest concern is the bubble in which we live and write. Consider another book in O’Reilly’s Lean series, Ash Maurya’s Running Lean. I’ve told plenty of people about it; it’s doing really well, and Ash is in high demand as a speaker and subject matter expert. When a potential reader comes from the startup world, they get the title immediately. But outside our world? They think it’s a book on jogging to lose weight.

No, seriously: if you asked a million random people what the book “Running Lean” was about, what do you think they’d say? Here’s a post from a car tuning forum.

In our case, many people I’ve talked to in the business world (that is, in established businesses that are well past finding their product/market fit) think “Lean Analytics” is about doing web analytics on a shoestring budget, or about Business Intelligence with a minimum of technology. One even thought it was about lifelogging to shed pounds by tracking weight. None of those topics will leap off airport shelves. This presents us with a dilemma:

  • If we target a market narrowly with a title that resonates, we’ll get good adoption within that market.
  • But if we over-target the branding, we limit our ability to reach a broader audience.

It’s a tough balance to strike. It’s one we hope to understand through analysis and experimentation, but even then, this is difficult: we mostly know how to survey startup types. Tim Ferris did some in-store testing before choosing his title (making many of us wonder how many hours he squeezes into four hours.)

He took a book about the same size, put a bunch of different covers on the books, put them in the new non-fiction book section, then just sat back and observed people for the next few hours, watching their reactions. An overwhelming percentage, something like 300% more people picked up The Four Hour Work Week title than the others.

Ferriss and his writing team came up with 12 alternate names. To break the deadlock and to help finalize and write the great book title they eventually came up with, Timothy Ferris ran a Google Adwords campaign. ” He bought ads for relevant keywords for all twelve potential book titles and tracked which titles performed the best. The clickthrough rate for The 4 Hour Work Week was by far the highest, so that is what his book is called.”

As far as using Google Adwords to write a great book title, Ferriss proved it’s possible and as Zeigler reports, “a smart and novel approach to write a great book title. “Google Adwords is a cheap and real time focus group.”

Ben and I have a number of ideas for titles that might work. But they’re just ideas—hypotheses to be tested. We’ll try a variety of titles with different audiences and see what works, because that’s what analytical types do when confronted with uncertainty. Not sure whether we’ll camp out in bookstores, but ads and surveys seem like a good start.

On that note, we have a survey going right now with 5 name options. Previously we had many more, and ran a survey on new sign-ups for the book. After 70 or so survey completions, we took the five highest ranked names and updated the survey.

Please take a look here: help us name our book!

The survey takes no more than a minute to complete, and will be one of the data points we use in picking a final name for the book. Thank you!

1,000 (How we’re validating the opportunity for Lean Analytics book)

When Alistair and I first started promoting Lean Analytics, we set ourselves a target of adding 1,000 subscribers to our mailing list by the end of August. At this stage of promoting the book, the “Number of subscribers” is our One Metric That Matters, and one thousand is our line in the sand.

Some might consider this a vanity metric, but it’s not—for us, it’s a measurement of interest in the book and its subject matter. It’s also an indication of our ability to contact a number of people with survey questions, additional content, and more so that the book meets the expectations of our intended audience.

Sure, the number goes up continuously (unless we fail miserably and more people unsubscribe than sign-up), and it’s not a ratio or rate (which we’ve said is important for a good metric.) But ultimately it was a good measure for testing our initial MVP (which is basically the website + the content we’ve produced on the site and through the mailing list.)

So why 1,000?

Like any line in the sand, it’s a combination of guesswork, aspirations, and judgement around what is challenging to reach, but attainable at the same time. We also spoke with other authors about how well they did building up their mailing lists, and we have our own experience doing this for other businesses, so we had some rough benchmarks to compare against. It’s also an indicator of things like survey completion and pre-orders that could help us break even.

Drawing a line in the sand is really important. Without that line, you can’t tell if you’re making adequate progress at a fast enough pace to meet your goals. The line also tells you how much effort to invest in your current course and direction, whether to double down, or whether to try something else.

If we had hit 100,000 subscribers in a couple of months, we would have known we were onto something. We’d be able to convince our families that we really needed to skip important vacations in order to write; or start scheduling book tours in advance; or charging more for speaking engagements. Similarly, if we had hit only 100 subscribers, we would have known it was a failure.

Most startups fall into the murky middle—the metrics they’re tracking are neither home runs nor dismal failures. Picking a target helps define success and failure, and gives you the opportunity to be honest with yourself. Are things going well or not? Should I continue or not?

This is a big part of succeeding with Lean Analytics. Draw a line in the sand (and remember, it’s in the sand, so it’s moveable), run some experiments, measure your results, and learn from them. Focus on actionable goals that derive from the metrics that you are tracking.

So how did we do?

Unfortunately, we missed our target. By the end of August we had 906 subscribers. We were off by about 10%. Not bad, but disappointing nonetheless. In evaluating the result versus our target, Alistair and I asked a pretty important question, “Do we think there’s enough interest in Lean Analytics to make the book a success?” And if there is enough interest, why didn’t we hit our target or surpass it? The number alone isn’t enough to give us the answers; but it’s a good starting point for the discussion.

Alistair and I concluded the following:

  • The qualitative feedback we’ve received since announcing the book has been very strong. A lot of it has come from our peers (which you have to discount a bit), but a lot of it has come from strangers too. That means (a) we’re reaching into new audiences we haven’t tapped into yet; and (b) there’s unbiased interest there that’s meaningful.
  • Some of the attention has involved speaking engagements we’ve been invited to, which suggests that we’ll be able to spread the world through those organizations as well.
  • Our survey response rate was amazing. People who signed up really cared, and took the time to give us their thoughts. Response rates of 75% are an excellent sign of engagement.
  • We reviewed the 750+ survey responses we got (the survey pops up after you sign up for updates) and did a bit of lightweight quantitative analysis on people’s interest in Lean Analytics. This gave us good insight into what people care about (validating a number of our hypotheses.) It also helped us trim some things we didn’t want to do.
  • We could have done more to juice our subscription numbers, but we didn’t have the time. For example, we had plans for experimenting with paid advertising, which we didn’t get to (but probably will at some point.) And we also had to spend a lot of time writing the book (which takes away from marketing the book.)
  • Both of us were fairly confident we could have hit our target 1,000 subscribers had we put more effort in. At the same time, that effort was better spent on other things: writing the book (and in many ways changing what we had written and planned to write based on good qualitative feedback from existing subscribers), debating ideas, planning future marketing campaigns, etc.
  • The number we did hit is pretty close to the target we set out. Had we only hit a few hundred, panic would have sunk in. But we were close enough, considering the effort we put in, to justify continuing with the project.

As you can see, we’ve got a mix of qualitative and quantitative analysis going on. There’s a bit of guesswork, gut and intellectual honesty thrown into the mix and that’s common when evaluating almost any metric, particularly at an early stage. You’re not dealing solely in fact, but without any facts at all, you’re not giving yourself the right framework for learning and adapting quickly enough.

Side note: As of this moment, we’re at 945 subscribers. We’ve added 39 subscribers in September so far, which is ~3.25 subscribers per day. In August we had 142 subscribers, which is ~4.6 subscribers per day. Our rate of subscribers is dropping. That’s not surprising, but it’s a number that we’re keeping an eye on. September will provide a decent benchmark that we can then use to compare for future months.

Buyer Mindsets: Understanding How Customers Buy

As we write the book, there’s plenty we’re not including. For example, there are several things that affect what metrics you should look at: the kind of company you are, the stage you’re at, your audience, and how your buyers think about their purchases. But rather than go into detail on all of these, we’re just picking two; the others are falling on the editing room floor, which, in this case, means the blog.

Here’s something we aren’t putting in the book, but which is still interesting—and IMHO not talked about enough. It’s the way in which your customers are accustomed to buying a particular product category.

The metrics and KPIs a startup tracks will vary depending on the stage that the company is at, and the business model. A late-stage SaaS startup might care about minimizing churn and uptime, while an early-stage mobile gaming company may be obsessed with gameplay mechanics and time in game per day.

Three kinds of buying mindset

Who are your target customers? It sounds like an easy enough question, but it’s not. If you’re selling a big-ticket item to an enterprise buyer, you’ll be wading through purchasing and processes; by contrast, if you’re selling a cheap (or free!) product to an individual consumer, you’re looking at a quick, simple, highly impulsive purchasing process.

Marketers have names for these “buying mindsets.”[1]

A straight rebuy happens when the buyer is familiar with the product and the buying process, and has generally chosen the brand—booking a familiar flight using the normal carrier, for example.

An app store purchase, 1-click buying, or a recurring billing model is an example of a straight rebuy.

This is the kind of “loyal customer” behavior marketers crave. The purchase is nearly instinctive, and you care much more about whether their behavior deviates from expectations; how long the activity takes; and any signs that their loyalty might be waning. A user auto-renewing their annual service, or placing an e-commerce order from a known online merchant, is engaging in a straight rebuy.

A modified rebuy happens when the buyer is familiar with the product or service, but is reconsidering some aspect of their purchase. For example, they might be flying to a city their normal airline doesn’t serve: they have expectations, but are open to change and looking for cues.

A Dell buyer who’s selecting a new notebook model is in a “modified rebuy” mindset, comparing with constraints but still relying on familiarity.

Here, you care about ways of upselling or unseating an incumbent. Buyers are more engaged than when they’re simply doing things by habit, and you have a chance to change their behavior in ways that will help you. Someone switching photo-sharing or messaging services might be in this group.

Finally, a completely novel buy happens when someone is purchasing in an entirely unfamiliar category, or something with considerable impact or uncertainty—booking a family vacation online, or buying a house. They have little or no experience with this purchase, and you can create their buying criteria or introduce your brand to them.

When a prospect uses a comparative shopping site, or an independent ratings company like Consumer Reports, they’re making a completely novel buy.

This is generally the case when you’re a truly disruptive startup, trying to define a product category; or when making a one-time purchase towards which the buyer has little emotional attachment, such as a dishwasher.

For a completely new purchase, SEO/SEM and placement on ratings sites matter much more; you’re fighting for a customer in the court of public opinion, where you have far less control over (and visibility into) the purchasing process.

[1]  and have some additional lists of marketing terms.

The Lean Hair Salon

Yesterday, I had an interesting conversation with, of all people, my hairdresser. Those who know me realize there isn’t much hair to dress, so it was an unusual event to begin with. As it turns out, she’s just bought a one-person barbershop and this was her last week at her current employer’s shop.

In hushed tones, under the sound of scissors, she told me about her marketing plans: “I just got my business cards printed and I’m making a Facebook page. I don’t get Twitter.”

I gave her a few ideas:

  • Encourage people to post pictures of the cuts they liked to her page, where others can Like them, and each month give one person who does so a cut for free
  • Go see all the concierges of hotels in the area and ask them to come for a free cut, so they recommend it to visitors
  • Canvas movers on July 1 with a campaign since they just moved to the area (July 1 is moving day in Quebec.*)
  • Set up a Twitter search for “haircut” with a region of “Montreal” and respond to people when they mention it, and offer them a code by DM

She asked me how I was coming up with all these ideas. And I tried to explain to her (in halting French), “well, I’m thinking about what makes someone change salons. Their friend gets a good cut; they’re visiting from out of town; they just moved. And that’s the moment when you can change their minds.”

She replied, “these are great! I’m going to do them!”

I asked her, “all of them? but why?”

“Because they’re free!” she answered. “Even printing my business cards cost more than some of these.”

I agreed with her: “This is the change that businesses have undergone in the past decade. The price of marketing has gone down to almost zero, if you can just find a way to be in the right place at the right time with the right message. But most small businesses still think about marketing as fliers, a Yellow Pages ad, and some business cards.”

“So I should do all of them, right?” she asked excitedly.

And I shot her down. “No,” I said, “you’re going to try them. You need to measure whether they work. Better yet, go home, grab a few beers and a pad and paper, and figure out all the ways that someone finds out about you and decides to try you. Then, for each of those, figure out ways that you might join that conversation in a way that doesn’t suck.”

She paused for a while, forgetting to cut what’s left of my hair, and I could almost see the wheels turning.

Once she came out of her daze I said, “and then figure out how to measure it. You have a barber shop to staff—you’re the only employee. You need to kill the bad ideas fast, and find someone else—preferably a piece of software or a friend—to do the good ideas repeatedly. You’re not a hairstylist any more, you’re an entrepreneur, because you bought your own business.”

She was clearly starting to get it—although she was probably also reconsidering her decision to strike out on her own.

So I said, “this is the difference between an employee and an entrepreneur. You’re not in search of the perfect haircut, you’re in search of a sustainable way to grow your business and bring in revenue.”

It occurred to me at this point that most small business owners define themselves by the work they do within the business (cutting hair, mowing a lawn, driving a truck, running a lemonade stand) and not by the customer need they’re addressing (a neat appearance that gets them promoted, a lawn that complies with town by-laws, relocation, learning about business.)

A worker becomes an entrepreneur when they re-frame themselves. They’re no longer the cog in the machine—they’re the architect of the machine. The watchmaker, not the watch. And that means they start asking what the machine is for, how it can be improved, what else it can do, and which other machines satisfy the need.

“In the end, it may even be that your customers don’t want haircuts, they want something else—fashion consulting, pedicures, personal training, someone to talk to. Or maybe you should be a travelling stylist who does work on demand for hotels. How would you find out about that and figure out what other needs customers have that you can help with? And how could you use those to become unique, or more efficient, or more profitable?”

The conversation reminded me that lean principles apply to everything, and are increasingly relevant to small businesses. Today’s one-person company has tools at its disposal that the Fortune 500 only dreamed of a decade ago. Entrepreneurs can make data-driven decisions, run experiments, segment customers, and iterate.

They just need to stop thinking of themselves as part of the machine, and start seeing themselves as its designer.


* 4% of the population moves on that day. No, there aren’t any trucks available. Go ahead, mock us.