‘Our Users Are Everyone’: Designing Mass-Market Products for Large User Audiences

When a design serves a large and varied population of users, stakeholders sometimes direct that the design must target “everyone.” This approach may feel more inclusive than focusing on certain categories of people, and is especially attractive for organizations that have a strong need to attract more customers or users.

But avoiding any definitions of the target audience actually leads to a less usable experience for most people. Without an understanding of who the users are, you risk getting biased research findings and incoherent design choices.

You don’t always need precise categories of user characteristics, but you do need some idea of who will be using the design, and what they’ll try to do with it.

Designing for Anyone Is like Packing for a Trip to Anywhere

Before you pack for a trip you probably gather at least a little bit of information about:

• How long you plan to stay
• What kinds of activities you’ll be doing
• What the weather will be like at your destination

Imagine trying to prepare for a trip if you had no idea whether you’re heading for a weekend jaunt to a luxury resort or a six-week expedition to Antarctica. How could you possibly bring the right supplies for a great trip if you have no context for what you’ll need?

The exact same principle applies to design. Ensuring our users have a great experience doesn’t necessarily mean we need to define everything about them. But we do need to define a lot about the trip they’re about to embark on: what activities will they be doing, and what content and features will they need to make those activities successful and enjoyable?

Testing with Anyone Is Not Testing with Everyone

One big problem with failing to define your users occurs when you evaluate the design. If you plan a research study with no restrictions on who can participate, you could easily end up with all your participants being quite similar to each other. This is no problem if your system is only intended to serve one type of user, but if you’re aiming for a mass-market audience, you can miss out on a lot of insights and opportunities.

Imagine you’re designing the website for a city-transportation system used by both local commuters and tourists. If you plan a usability study with 10 people and let anyone participate, you could easily end up with 9 commuters and 1 tourist. (Or even worse: 10 commuters, if you recruit a convenience sample of users who live close to your office.) You might learn a lot about commuters but very little about your other important audience — tourists who encounter unique challenges due to their lack of familiarity with the local geography.

You can learn a lot from doing usability testing with just 5 users. But if your audience includes a range of people who have fundamentally different tasks, needs, and expectations, then 5 users will not be enough. Instead you will need 4–5 test participants from each major type of user. (You can often get away with slightly fewer users in each group if there is still some overlap between the tasks done by each group.) Before you can find those people, you must have some idea of how to distinguish different types of users.

Getting past ‘Everyone’: Strategies for Meaningful Descriptions of Large Audiences

A natural approach for describing a large group of people is to turn to demographic facts such as age, gender, occupation, and income. When recruiting participants for user research, it’s definitely good to have some demographic diversity. But these facts don’t usually describe what you should really be focused on — those distinctions among your target users which actually affect how they will interact with your design. Travelers on a city-transportation system could be divided into groups by age — such as 16–24, 25­–55, and older than 55. This type of diversity will probably reveal some differences because people at different stages of life tend to have different schedules. But we could still miss out on the perspective of people who are just visiting or who have recently moved to the area and aren’t yet familiar with the city.

Designers and researchers need to understand how people behave. So the best way to organize information for them is to group people according to their actual behavior, not just their demographic categories.

With a large audience it may seem overwhelming to try to describe the full range of user behavior. For example, different people may use a transportation system to travel between hundreds of different locations, for an endless number of reasons such as job interviews, parties, dates, school, doctors’ appointments, work, and so on. The trick is to organize all these different usage scenarios according to what parts of them are actually likely to make people interact differently with the system.

If you design for large audiences, frequency of use is a good starting point for identifying meaningful distinctions between different types of users.

Frequency of Use Often Distinguishes Different Groups

Often, frequent users behave differently than occasional users. But these important differences are easily overlooked if you think only about how ‘everyone’ acts. By dividing your audience into distinct groups of frequent and infrequent users, you can begin to detect important patterns and trends.

Imagine you work on an application with a huge population of users. Chances are some people use the application more than others. Variations in frequency of use is both a cause and an effect of important differences between types of users:

1. Frequent use causes familiarity with the interface and quick completion of repeated tasks.
2. Frequent use is an effect of needs and goals: people use it more because the tasks or content are important to them.

And vice versa — infrequent use implies less familiarity and less importance to the user. Of course, there are exceptions: some usage scenarios are infrequent but very important (such as buying a house), while some interfaces may remain a mystery even to people who use them every day. But for many designs, grouping people according to how frequently they perform a task or interact with a system will reveal valuable insights about their needs and challenges.

Even if you need to serve both frequent and infrequent users, it’s still important to distinguish between them, so you can understand and support the cluster of behaviors associated with each group.

If you want to increase the overall size of your audience, then it’s imperative to define extremely infrequent users as a distinct group, because these are your potential future customers. Ideally you should have some specific information about which new markets you hope to expand into; but even a group defined as ‘people who don’t currently use our product’ helps design and research by forcing consideration of users who aren’t already familiar with the design.

Besides usage frequency, there are many other ways to segment a large audience into more specific groups:

Applying User Categories to Improve UX Outcomes

When you’ve identified important traits for your audience, you can apply them in several ways:

• Data driven: review analytics or survey data to estimate cutoff points which divide clusters of users. For example, you might find that 10% of users visit daily, 70% visit weekly, and 20% visit less often.
• Simple cutoffs: even if you don’t have quantitative data, pick a cutoff point based on anecdotal user comments — such as, people who visit at least once a week are frequent users, anyone who visits less than once a week is an infrequent user. Your groups may not exactly match the real distribution, but you’ll still be much better off than if you just throw up your hands and treat all users as though they are all the same.

More important than finding the exact cutoff point between groups is to make sure they become part of your research and design planning. Depending on the depth of the difference between the groups and the implications for usage and your business, you might consider the groups sufficiently distinct to require separate usability studies with different tasks. Or, with less-important distinctions, you could simply make sure to include people from each relevant group when you recruit participants for a study, so you can observe any differences in what they expect and how they behave. Share the categories with your design team and make them visible in brainstorming and planning sessions (for example, by creating personas to represent each category).

While it may seem overwhelming at first glance, identifying meaningful segments from a very large audience doesn’t have to be complicated. Even a little bit of effort in this area can yield substantial improvements in the outcome of your research and design efforts.