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Often, when I ask product managers or designers who their user is, they will respond with something like, “moms” or “salespeople.” They are wrong.

Let me give you an example. Think of all the moms that you know. You can start with your own, if you like. Then maybe think of some famous moms. Angelina Jolie is both famous and a mom.

What are the chances that you could build a feature that would be an absolute must-have for both your own mom and Angelina Jolie? Probably not great, as shown in Figure 2.1.

FIGURE 2.1 A very small selection of moms.

It’s not that there are no products in the world that might be used by both your mom and Angelina Jolie. The problem is that “moms” is simply too big and diverse a group to be able to target, especially for a new product or feature. After all, the only thing that all moms have in common is the fact that they have, at some point in their lives, acquired a child, which means that finding a problem or goal shared by all moms is nearly impossible.

Building for moms is almost the equivalent of building for everybody, and trying to find something that pleases everybody will typically end up pleasing nobody.

This is important, because the most common reason I see for the failure of new products is a fundamental misunderstanding of the buyer. Startups, longing to be Facebook, aim for a broad audience of “everybody,” forgetting that Facebook started out as a product for Harvard students, which is a pretty specific market, when you think about it.

Product teams at large companies run into the same issue. They aim for big markets because only a big market will move the needle enough to justify spending all that money building something new. But even products from large companies that try to launch to a giant, undifferentiated audience can fail. And yes, I know you think that Apple ships its new, perfect products to everybody, but a) they have the cash reserves of a mid-sized country, so they can afford a few flops (anybody remember Ping?), and b) they only ship their product to everybody you know, and everybody you know is a smaller subset of humanity than you think it is.

Products for a very specific audience with a common problem or goal are far more likely to gain traction early because they can absolutely corner their particular market. Even a very small market can be a great starting point for a product if you capture almost everybody in it, and small markets don’t always stay small. Remember, Harvard students are a pretty small market. After a year in business, Facebook was still only letting in people with .edu email addresses, which meant that it was still focused on students (see Figure 2.2). It wasn’t until 2006 that the company let in anybody over 13. That was more than two years after it launched.

It takes awhile to get to something that really is for practically everybody, and it’s useful to stay focused until you figure out if you’re serving a real user need.

FIGURE 2.2 Thefacebook circa 2005.

The point of all this is that you have to accept that the real user profile for most brand new products is much, much narrower than moms. Or salespeople. Or millennials.

Here’s a real life example. I worked with a company that made financial software for small businesses. It wanted to help other companies with zero to ten employees understand their finances better.

The problem was, when we went out to interview their customers, we kept hearing very different needs. Some customers absolutely needed better cost of goods sold (COGS) reporting. Some desperately wanted the ability to split out bank deposits. Some needed an integration with eBay. It went on and on. After talking to about a dozen people, we didn’t see any patterns across the entire group. Any feature we added would have been useful to, at most, a third of the users we’d interviewed. That made it very hard to prioritize new features.

What we did see, however, were patterns within certain groups. Consultants needed different features than eBay sellers did, but consultants often needed the same features as other consultants. Once we determined the more specific different user segments, patterns started to emerge. Since we couldn’t build something for everybody, the next thing we needed to do was pick one of the common groups and focus.

After a series of conversations with users, we saw the strongest patterns among a very specific group of users—eBay sellers who bought and resold items and didn’t have any employees. By focusing on the needs of this particular market, we found it much easier to make good product decisions, because we could predict which features would appeal to our narrowly targeted users.

Every new feature we added was far more likely to make the majority of this user group happy, and growth ended up better because of it. The product became more popular among a very large group of people with a very specific problem. It wasn’t as popular with the other groups, but it’s often better for your product to be fabulous for one group of people rather than mediocre for a lot of people, especially when you’re trying to grow quickly.

In order to accurately predict who will use your product and which features they will pay for, you need to identify the traits shared by a group of people that draw them toward the thing you’re selling. It’s usually a certain behavior or a problem that this group of people has. It’s never something as common as “having children” or “driving a car.”

Let’s say you have a product that you think is useful for accountants. Try answering the following questions:

• Where do these accountants work? Do they work for a large company? For themselves?

• Do they have a lot of different customers or just a few?

• Do the people for whom they do accounting have a specific type of business, or are they individuals?

• Do they focus mostly on helping people pay taxes or avoid them?

• Are they all struggling with a particular problem or failing to reach a specific goal?

• Is there something that is taking them a lot more time or costing them a lot more money than it should?

In other words, what are the common patterns that make this person uniquely likely to buy your product?

EXERCISE