I cannot give you a one-size-fits-all plan or a step-by-step set of instructions—the kind you get when you buy IKEA furniture. But I will share with you some of my favorite and most effective tactics to help you take full advantage of our tools, so you can avoid some market punches and perhaps punch back a few times. I will follow this chapter with one final example that illustrates all our tools and tactics in action.
Ready? Let’s go.
Tactic 1: Think Globally, Test Locally
If the phrase “Think globally, test locally” has a familiar ring to it, it’s because it was inspired by the popular “Think globally, act locally” slogan (and bumper sticker) commonly associated with ecologically minded people and organizations. In our case, the objective is not to save the whales or protect the ozone layer, but to save our time and protect our valuable resources by making early contact with the local market instead of wasting time in Thoughtland making premature grandiose plans for worldwide sales and distribution of our product.
“Think globally, test locally” means that you can have global plans for your product, but before you spend any time developing and executing those ambitious international plans, you should validate your idea on a much smaller and easier-to-reach subset of your target market. Make that initial market your town, your neighborhood, your workplace, or your school. The closer and more easily accessible it is, the better.
Go ahead and spend a few minutes daydreaming that your unique idea for a pizza restaurant will become the next California Pizza Kitchen—a chain with hundreds of locations in several countries. But don’t waste time making plans for global-market conquest until you have achieved consistent success with one location.
The words globally and locally suggest geography, but the “test locally” principle applies to more than just physical distance or geographic regions. It applies to any market with multiple conceptual groupings or industry standards, each of which requires additional investment to reach and address. If your market is smartphone users, for example, where those users physically live is less important than what smartphone platform they use (e.g., Apple iOS, Google Android). Many mobile app developers double or triple their up-front investment and waste months of engineering and marketing time to develop and launch their new app on multiple mobile platforms at the same time—only to learn that Google Android users are just as uninterested in their app as Apple iOS users. Validate your idea on one platform at first—the one that is technically or conceptually closest to you—before you set out to conquer the rest.
If you are a mobile app developer and you are most comfortable and experienced with the Google Android operating system, then that’s your local “neighborhood.” Android users thousands of miles away are easier for you to reach than iOS users living next door. So begin by pretotyping and testing your new app idea on the Android market. If your pretotyping experiments indicate that the app is likely to be successful with those users, then you can start thinking about developing versions for other platforms.
Early in my career, blinded by dreams of global success, I consistently ignored the “test locally” tactic and ended up paying a hefty price for it. In one of the companies I cofounded, for example, we hired sales teams to cover Europe and Asia Pacific before we had achieved consistent and repeatable sales success and user adoption in the US. To support each new country, we had to translate, customize, and test multiple versions of our product and documentation for that country. All of this cost us a lot of time and money and was a huge distraction. I can’t blame the company’s eventual failure on that one decision, but it certainly did not help.
But what if there is no local market for your idea? What if you live, say, in Montana, and your idea is solar-powered surfboards? In that case, I suggest that you move to southern California or Hawaii, look for a new idea, or come up with creative ways to bridge that distance (e.g., partner with someone who has ready access to surfers).
“Test locally” is one of my favorite tactics, because it’s the best way to quickly get yourself and your idea out of Thoughtland and into contact with the market. With this tactic, we take hypozooming and go a step further. We don’t just zoom into a small test market, we zoom into a small and local test market.
Remember how in the Relabel pretotype example for Second-Day Sushi we zoomed in all the way to within a few hundred feet of our current location? Not just California, not just Palo Alto, not even just Stanford University, but to the very same building where the students were at the time. By doing that, we were able to come up with a pretotyping experiment that we could execute easily and right away.
Say It with Numbers: Distance to Data
You can—and should—measure how well you are following the “think globally, test locally” tactic by calculating your Distance to Data (or DTD). If you plan to collect your data in the physical world (e.g., at a store, on a street corner, or in a club meeting), you can measure DTD using your favorite unit for distance (e.g., meters, miles, furlongs) and then try to minimize it. By keeping initial market-validation efforts as local as possible, you save valuable time and money, which allows you to run more experiments or test more ideas. You’ll be surprised how much good YODA is often available right in your neighborhood or other nearby areas. Let me give you an example.
Linda has an idea for a $19 device to make those visits to the coin laundry more efficient—and less depressing. She calls her gizmo LaundroDone. Toss LaundroDone into the washing machine or dryer along with your clothes, and when the machine completes the cycle and stops spinning, the device sends a text to your phone to let you know that your clothes are ready. Thanks to LaundroDone, Linda explains, she doesn’t have to wait around at the coin laundry, sitting on plastic chairs and fending off romantic advances by pajama-wearing Romeos down to their last pair of (hopefully) clean underwear. She can escape the depressing glare of those fluorescent lights and the nauseating potpourri of odors from detergent and fabric softeners. Thanks to the LaundroDone, she can wait in the safety and comfort of her car, listening to Coldplay, until she gets the alert that her clothes are ready.
Linda comes up with a brilliant way to test her idea using a combination Mechanical Turk and Facade pretotypes, and she is eager to put it into action and collect her first YODA. She believes that the best market for her idea is large coin laundries in major metropolitan areas (big cities like New York or Los Angeles), and that’s where she wants to run her tests.
But Linda lives in a tiny residential community in rural southern California. There’s only one coin laundry in town that, in Linda’s own words, “gives me the creeps and is a magnet for weirdos.” Even though the creepy coin laundry is what motivated Linda to invent the LaundroDone, she does not want to set foot back in there if she can avoid it. Instead, Linda plans to drive 120 miles to Los Angeles, book a hotel room, and spend a couple of days running her tests in several La-La Land coin laundries. Nothing wrong with this plan, but does she really have to drive that far to collect some of her first YODA?
By applying the “test locally” tactic and using the Distance to Data metric as a guide, Linda identifies a midsized town with several not too creepy coin laundries that is less than 20 miles away. It’s not as local as her hometown, but at least it’s in the same county. By staying relatively close to home, she saves herself a 200-mile round-trip and hotel costs—time and money that she can use to run more tests. Makes sense, doesn’t it?
What happens, though, when your product idea is meant to be marketed, acquired, or used online? In that case you can replace units of physical distance with virtual ones such as emails, web posts, or web pages. Instead of counting physical steps, you count digital steps. It’s easier than you think. Let me illustrate with another example.
A few years ago I came up with an idea for an audio tone-control device to make poorly recorded music sound richer and less harsh. I identified the target market as audiophiles—people who spend a lot of money on audio equipment in search of sonic nirvana.
These days, most audiophiles make their purchases online because brick-and-mortar audio stores are becoming as rare as bookstores. So my plan was to market and sell my audio device online, and I designed my pretotypes and tests accordingly.
I wanted to follow the “test locally” tactic. But what does “local” mean online? In my case, I identified my virtual neighborhood as the internet audio forum that I visited regularly and to which I actively contributed with my own posts and audio product reviews. I was one of the first members of the forum, and I was on good terms with the forum’s founder, so I figured that if I asked him nicely, he would let me write a post introducing my device to see if any forum members were interested in buying it. In this case, my DTD was three digital steps:
Writing one email to the forum moderator
Writing one post to introduce my product
Creating a basic website with one landing page to collect some skin in the game (emails, deposits, etc.) from potential customers
Because I was already a member of the forum and on friendly terms with its moderator, I was able to keep things in my “online neighborhood” and get my pretotype up and running very quickly.
Keep “think globally, test locally” in mind when you craft your first xyz hypotheses. Don’t just zoom in on a specific market; zoom in to where you are now. And speaking of now . . .
Tactic 2: Testing Now Beats Testing Later
“Testing now beats testing later” does not require much explanation. The message is clear: don’t delay testing. Take your idea—and your butt—out of Thoughtland and into the market as soon as possible. After you’ve identified your initial Market Engagement Hypothesis, expressed it in XYZ Hypothesis format, hypozoomed into xyz hypotheses, and designed a pretotyping experiment, it’s time to move from abstract thinking to concrete testing.
But most of us are reluctant to leave the comfort of Thoughtland. We dwell in it for months, sometimes years, thinking and talking about our idea, writing and revising our multiyear international business plan—even though we don’t have a single piece of YODA that validates our idea. Why do we do that?
I’ve been stuck in Thoughtland myself many times, so I feel qualified to posit an answer: fear! More precisely fear of rejection, the fear of finding out that there is no market interest for your beloved idea. Most people don’t like to admit having this fear, but their actions indicate otherwise. I am no Sigmund Freud, but lingering in Thoughtland and postponing market contact might be a way to subconsciously avoid that potentially painful first contact with the market.
I’ve often compared the fear of the pain, humiliation, and disappointment that can come from market rejection to the fear of romantic rejection. I get it, rejections—romantic or otherwise—are very unpleasant and psychologically difficult. But faint heart never won fair lady—or market share.
There’s no escaping the Law of Market Failure. Most of your ideas will be rejected by the market—and it will hurt. But the tools and tactics in this book will make this unpleasant yet unavoidable part of the process less painful, quicker, and easier to take. So don’t delay. If your idea is going to be rejected, better to find out now rather than later.
Over the years, I’ve worked with hundreds of teams on thousands of new product ideas, and I’ve noticed the following patterns:
Teams that spent too much time in Thoughtland working with opinions and OPD and spent months writing business plans usually failed.
Teams that rushed their product to market with minimal planning and testing usually failed.
Teams that rushed to test the market usually succeeded.
In other words, you don’t want to spend too much time in Thoughtland, but you also don’t want to rush a finished product to market. Instead, take that eagerness to launch your product into the market, and use it to first test the market.
Say It with Numbers: Hours to Data
Hours to Data (or HTD) is a measure of how many hours it will take you to execute a pretotyping experiment and collect some high-quality YODA. The HTD for our initial Second-Day Sushi pretotyping experiment, for example, was just two hours—that’s all it took to print some labels and slap them on the boxes on display (and it helped that it was close to lunchtime).
All things being equal, the shorter the HTD, the better. When I assign a pretotyping experiment to students, I typically set an HTD limit of forty-eight hours—and offer bonus points if they can prove that they got their YODA even more quickly. In one of my classes, while I was in the middle of explaining a pretotyping assignment, one of the students raised her hand, waved a $5 bill, and yelled, “Three minutes to data! How’s that?”
Before I had a chance to reply, she explained, “Our team’s idea is a bicycle-cleaning and tune-up service. For $5 we will thoroughly clean your bike. For $10, we will also check the brakes, the shifters, lube the chain, and inflate the tires.” Murmurs of approval from other students in the class. “So,” she continued, “I sent an email message with the offer to our class and—”
At that point a student sitting behind her stood up and said, “I saw the message and gave her the $5 just now. I want to be first in line, because with all this rain my bike is filthy and muddy.”
I couldn’t help smiling. I started to clap, and the rest of the class soon joined in. It was just one data point, but this student definitely understood the basic principle and spirit of Hours to Data. As you can imagine, by coming in with an HTD of 0.05 (three minutes is 0.05 hour) she recalibrated the expectations of everyone in the class (including me) and set a new standard. The competition was on.
Note: Originally, I used a different name for this metric. I called it Time to Data. But I eventually changed it to Hours to Data in order to recalibrate expectations and increase the sense of urgency. It worked incredibly well. In both my classes and projects with corporate clients, the time it took teams to get their first YODA shrunk from a few days to a few hours.
This name change, by the way, is an example of what psychologists call priming (or anchoring). By using hours as the basic unit of measure, I primed people to think in terms of hours and not days or weeks—and that’s exactly what they did.
Tactic 3: Think Cheap, Cheaper, Cheapest
If you follow the techniques in this book, you will be able to collect high-quality YODA not only faster, but also much more cheaply than you could with other market-research approaches, possibly 10, 100, or even 1,000 times cheaper. Many of the companies I work with are accustomed to allocating months and hundreds of thousands of dollars for market research, so when they come up with a pretotyping experiment budget in “only” the tens of thousands, they are thrilled—but I am not. I tell them that going from hundreds of thousands to tens of thousands is good progress, but that they can probably get the same YODA for mere thousands or even just hundreds.
Most ideas for new products can be properly tested with very little money—some with virtually no money. I like it best when “pizza for the team lunch” is the most expensive item in the pretotyping budget.
I urge you not to settle on the first or second pretotyping experiment idea you come up with. Ask yourself, “Is this the best that we can do?” More often than not, you will come up with a cheaper way to test your idea that does not sacrifice YODA quality. Then try to do even better than that. The “think cheap, cheaper, cheapest” tactic was inspired by the following story.
Henry Kissinger was a demanding boss. When he was Nixon’s national security advisor, Kissinger asked one of his staff members to write a position paper for him. The staffer spent several days working on the document. When he thought that it was good enough, he presented it to his boss, who thanked him and said that he would read it later that evening.
The next day Kissinger called the staffer in, handed the paper back, and asked him, “Is this the best that you can do?”
Surprised and a bit embarrassed, the staffer said that he could probably do better. He canceled all of his other plans and spent several days focused
on rewriting the paper.
Kissinger’s response to the revised version was the same: “Is this the best that you can do?”
The staffer was stunned and felt humiliated, but he asked for another chance and swore that he would do much better this time. A few days later, he delivered the third version of the paper to his boss.
Before the staffer left, Kissinger asked him, “Is this really the best that you can do?”
“Yes, sir. It is really the best I can do,” the staffer answered.
“Good. Now I will read it,” replied Kissinger.
Since I was not present, I cannot vouch for the veracity or accuracy of this story, but I like Kissinger’s approach, because it’s rare that our first solution is the best, most effective, or most efficient one.
In Google’s early days, when the fledgling company’s resources were stretched to the limit, many requests for an increased budget were often turned down with the phrase “Creativity loves constraints.” And guess what? Most of the time people found a way to make the available budget work.
If you stir up your creative juices, you will usually discover a way to test your idea that is cheaper than your initial one. If you originally allocated a budget of $1,000 for your experiments, challenge yourself to find a way to reduce it to $100. And if you succeed at that, see if you can push it down to $10 or, even better, zero.
Say It with Numbers: Dollars to Data
Dollars to Data ($TD) does not require much explanation, and feel free to replace dollars with the appropriate currency for the project: dollars, euros, yuan, bitcoin, donuts . . . Hey, wait a minute. Donuts? Yes, donuts. This metric does not have to be based on a conventional currency. If your project is staffed by volunteers and you reward them with breakfast donuts, then Donuts to Data is a reasonable metric to use.
The Right It Page 15