Crossing the Chasm: Marketing and Selling Disruptive Products to Mainstream Customers

by Geoffrey A. Moore

To cross the chasm you need a use case that poses equally challenging problems for the status quo solutions on a recurring basis. In the case of VMware its chasm-crossing use case showed up in the testing phase of the software development life cycle.

VMware came to the rescue. Not only could you reuse hardware you already had; you also could “save” your specialized testing environment so that you could load it back up in a jiffy. This meant a single hardware farm could simulate any number of production use cases, and it was available more or less upon demand.

it was that use case that allowed VMware to cross the chasm.

Once the systems administrator’s needs had been handled, focus shifted to the IT operations manager. The word had gone out—we have to do more with less—how can we save money on hardware? Answer, “virtualize” the PCs we have. It turned out the unutilized capacity was staggering—as much as 90 percent! It was like someone backed up a truck and started unloading free PCs. Any wonder VMware grew like a weed during this period?

The key lesson for us here is that, despite the magnitude of this dream and its relevance to VPs of operations and CIOs everywhere, it was the lowly systems administrator with the niche market problem of simulating production environments for software testing who was the hero of our chasm-crossing venture.

The fundamental principle for crossing the chasm is to target a specific niche market as your point of attack and focus all your resources on achieving the dominant leadership position in that segment as quickly as possible.

First you divide up the universe of possible customers into market segments. Then you evaluate each segment for its attractiveness. After the targets get narrowed down to a very small number, the “finalists,” then you develop estimates of such factors as the market niches’ size, their accessibility to distribution, and the degree to which they are well defended by competitors. Then you pick one and go after it. What’s so hard?

Now, these are smart people, and a lot of them have been to business school, and they know all about market segmentation—so it is not for lack of intellect or knowledge that their market segmentation strategies suffer. Rather, they suffer from a built-in hesitancy and lack of confidence related to the paralyzing effects of having to make a high-risk, low-data decision.

We are either going to get it right, or we are going to lose a substantial portion, perhaps even all, of the equity value in our venture. In sum, there’s a lot riding on this kind of decision, and severe punishment for making it badly.

Moreover, since we are introducing a discontinuous innovation into that market, no one has any direct experience with which to predict what will happen. The market we will enter, by definition, will not have experienced our type of product before.

And the people who have experienced our product before, the visionaries, are so different in psychographic profile from our new target customers—the pragmatists—that we must be very careful about extrapolating our results to date. We are, in other words, in a high-risk, low-data state.

There are precious few paradigms for how to proceed when you cannot examine market share data, indeed cannot even conduct an informed interview with an existing customer of the type you are now seeking to win over. In short, you are on your own.

Now, the biggest mistake one can make in this state is to turn to numeric information as a source of refuge or reassurance.

We all know about lies, damned lies, and statistics, but for numeric marketing data we need to open up a whole new class of prevarication. This stuff is like sausage—your appetite for it...

And once a number gets quoted in the press, then God help us—because it has become real. You know it is real because pretty soon you see new numbers cropping up, with claims for their legitimacy based on their being derivations of these other “established” numbers.

And yet, that is what some people try to do. As soon as the numbers get up in a chart—or better yet, a graph—as soon as they thus become blessed with some specious authenticity, they become the drivers in high-risk, low-data situations because these people are so anxious to have data. That’s when you hear them saying things like “It will be a billion-dollar market in 2016. If we only get five percent of that market . . .” When you hear that sort of stuff, exit gracefully, holding on to your wallet.

The only proper response to this situation is to acknowledge the lack of data as a condition of the process. To be sure, you can fight back against this ignorance by gathering highly focused data yourself. But you cannot expect to transform a low-data situation into a high-data situation quickly. And given that you must act quickly, you need to approach the decision from a different vantage point.

You need to understand that informed intuition, rather than analytical reason, is the most trustworthy decision-making tool to use.

there are situations in which it is simply more effective to substitute right-brain tactics for left-brain ones.

The key is to understand how intuition—specifically, informed intuition—actually works. Unlike numerical analysis, it does not rely on processing a statistically significant sample of data in order to achieve a given level of confidence. Rather, it involves conclusions based on isolating a few high-quality images—really, data fragments—that it takes to be archetypes of a broader and more complex reality. These images simply stand out from the swarm of mental material that rattles around in our heads. They are the ones that are memorable. So the first rule of working with an image is: If you can’t remember it, don’t try, because it’s not worth it. Or, to put this in the positive form: Only work with memorable images.

so in marketing can whole target populations become imagined as Gen X, Gen Y, Goths, geeks, Beibers, Dinks (Double Income, No Kids), or Henrys (High Earners, Not Rich Yet). These are all just images—stand-ins for a greater reality—picked out from a much larger set of candidate images on the grounds that they really “click” with the sum total of an informed person’s experience. Each is in effect a “poster child.”

Now, visionaries, pragmatists, and conservatives represent a set of images analogous to Goth or geek—albeit at a higher level of abstraction.

For each of these labels also represents characteristic market behaviors—specifically, in relation to adopting a discontinuous innovation—from which we can predict the success or failure of marketing tactics.

Markets as categories are impersonal, abstract things: the smartphone market, the gigabit router market, the office automation market, and so on. Neither the names nor the descriptions of markets evoke any memorable images—they do not elicit the cooperation of one’s intuitive faculties. In fact, these are not “markets” at all in our sense of the term—they do not refer to populations of customers, but rather sets of competitors.

Target customer characterization is a formal process for making up these images, getting them out of individual heads and in front of a market development decision-making group. The idea is to create as many characterizations as possible, one for each different type of customer and application for the product. (It turns out that, as these start to accumulate, they begin to resemble one another so that, somewhere between twenty and fifty, you realize you are just repeating the same formulas with minor tweaks, and that in fact you have outlined eight to ten distinct alternatives.)

Once we have built a basic library of possible target customer profiles, we can then apply a set of techniques to reduce these “data” into a prioritized list of desirable target market segment opportunities.

The quotation marks around data are key, of course, because we are still operating...

(“With 3-D printing, we can change the way eyeglass frame manufacturing is conducted—instead of make and then distribute, we can distribute and then make! Just think of the reductions in inventory and the opportunities to mass customize!”).

Sample Scenario 1. HEADER INFORMATION. At the top of the page you need thumbnail information about the end user, the technical buyer, and the economic buyer of the offer. For business markets, the key data are: industry, geography, department, and job title. For consumer markets, they are demographic: age, sex, economic status, social group.

In this context our key header information is: Economic buyer: The client who ultimately pays for the lighting fixture. End user: The interior designer who will guide the client in making the choice. Technical buyer: The home maintenance provider or building contractor who will install the fixture.

the idea behind the header information is to focus the marketing and R&D teams on a specific instance of how the product would be bought and used. This is called a use case.

2. A DAY IN THE LIFE (BEFORE) The idea here is to describe a situation in which the user is stuck, with significant consequences for the economic buyer. The elements you need to capture are five: • Scene or situation: Focus on the moment of frustration. What is going on? What is the user about to attempt? • Desired outcome: What is the user trying to accomplish? Why is this important? • Attempted approach: Without the new product, how does the user go about the task? • Interfering factors: What goes wrong? How and why does it go wrong? • Economic consequences: So what? What is the impact of the user failing to accomplish the task productively?

3. A DAY IN THE LIFE (AFTER) Now the idea is to take on the exact same situation, along with the exact same desired outcome, but to replay the scenario with the new technology in place.

Here you need to capture just three elements: • New approach: With the new product how does the end user go about the task? • Enabling factors: What is it about the new approach that allows the user to get unstuck and be productive? • Economic rewards: What are the costs avoided or benefits gained?