It is an honest question: how smart are your users? The answer may surprise you: it doesn’t matter. They can be geniuses or morons, but if you don’t engage their intelligence, you can’t depend on their brain power.
Far more important than their IQ (which is a questionable measure in any case) is their Effective Intelligence: the fraction of their intelligence they can (or are motivated to) apply to a task.
Take, for example, a good driver. They are a worse driver when texting or when drunk. (We don’t want to think about the drunk driver who is texting.) An extreme example you say? Perhaps, but only by degree. A person who wins a game of Scrabble one evening may be late for work because they forgot to set their alarm clock. How could the same person make such a dumb mistake? Call it concentration, or focus, we use more of our brain when engaged and need support when we are distracted.
So, what does a S.T.U.P.I.D. user look like?
“Fear is the mind killer”, Frank Herbert wrote. Our minds are malleable and easily affected by their context. The effect of stress on the brain is well known, if not well understood. People under stress take less time to consider a decision thoroughly, and they choose from the options presented to them rather than consider alternatives. Stress is often due to social pressures. Car salespeople know to not let a customer consider an offer overnight, but pressure them to buy right away.
Tiredness is one of the largest causes of industrial and motor vehicle accidents. Interfaces used by tired people should take into account their lowered sense of self-awareness and number of details that the user is likely to miss. A classic example of an interface used by sleepy people, the iPhone alarm clock is typically set right before bed. Unfortunately, it doesn’t ring if the phone is set to vibrate, the default state for many people. When a user sets the alarm, it would be useful to override the vibrate feature, or at least remind them that it won’t ring.
Training for enterprise applications is more often discussed then enacted. Users are thrown at an application with a manual and a Quick Reference Card. Applications that are not designed around the user’s workflow have to explain their conceptual model while they are being used: “where” things are stored, how to make changes, who to send things to.
Complex systems that are used infrequently are a particular problem. In the design of the automated external defibrillator, it is assumed the user may have no knowledge of the science or training on the device, and will be using it in a chaotic, stressful environment. The frequency of use should drive design. Yearly processes, like doing your taxes, should assume that the users have never done it before. In rarely used interfaces, customization is likely to be less useful, but a comparison to previous year’s entries is very useful as they remind the user what they did before.
More important than the user’s mental model of an application is their mental attitude toward the task. Someone sitting in the front passenger seat of a car may have the same field of view as the driver, but unless they are focused on it, they will not remember the path driven. Nothing reduces effective intelligence faster than doing a boring task against one’s will. When a user is passive, complexity becomes insurmountable. Games aimed at casual gamers know to keep the interaction model simple, using a flat navigation and avoiding “modes” (e.g. edit vs view).
User centered design is a powerful approach because it recognizes that there are many reasons people use a system. Airline booking sites are used to buy tickets, but also to see if the family can afford to go on vacation. The designer should recognize that they cannot solve every problem, but should give users the tools to help themselves, to work independently of the application’s intended method. In internal enterprise systems, the top user request is often “export to Excel”. This often reflects that the system does not meet the user’s needs. Excel empowers the user to do ‘out of the box’ actions. It is the API to the real world.
People are multi-tasking more than ever, whether it is simply listening to music while driving or playing Farmville while watching TV. Effective multi-tasking has been shown to be a myth, but it is a popular one. Paying “partial attention” to multiple activities has significant impact to your perception of an interface. Users are often said to be on “autopilot”, clicking on things by shape, rather than reading the text. An interface cannot rely on the user having a clear and consistent working memory across multiple screens. The task and details must be re-stated at each step to remind the user the step they are on and what they need to do. Frequent, automatic saving of user entered data is essential, especially as connections can time out.
Help S.T.U.P.I.D. users by designing S.M.A.R.T.
Start-ups often experience a shock when they emerge from the hothouse of heads-down development. Their intended customers barely have time to listen to their idea, let alone devote time to explore its features. The contrast between a small group of friends working intensely together on a single project with the varied needs and limited free time of their customers can be a disheartening experience.
Projects often fail not because the idea is bad, but because the value their service will provide is not easily understood. The question I ask my team is “What problem, from the user’s point of view, are you solving?” It has to be a problem the user knows they have. If the problem is not obvious to the user, in terms they understand, the solution doesn’t matter. Focusing on the problem keeps a project from drifting into fantasy requirements: solutions looking for a problem.
Design teams often use themselves as model users, but they are almost the perfect storm of differences between themselves and the users.
- They know the product exists and what it is supposed to do.
- They understand the internal concept, including its past and future ideas.
- They care, personally, about the product. Their success depends on it.
The user has none of these things. The user knows nothing about the product, doesn’t understand the concept, and doesn’t care.
What can be done to make S.T.U.P.I.D. users S.M.A.R.T?
Why are simple apps popular these days? It is not that people don’t like features, it’s because instant comprehensibility trumps powerful features. In the old search engine wars, Google may have had a better search algorithm, but they became known for having a simpler design. Yahoo and others tried to become portals, losing sight of the users primary goal. I advise people to “Design the mobile version first” to help them focus on the key user benefits.
The down side is that any successful project expands and adds features to address additional user needs. What starts out as “Writer for iPad” can end up as Microsoft Word. Simple is not always better, but keeping the new user in mind helps find the right balance.
An app is only as good as the user understands it. That starts with the name – is it cute or does it explain what it does? Is it “pidg.in” or “Automatic Mailbox”? The iPhone / iPad apps’s television ads were effective sales tools, but also trained a generation by simply showing them in use. Each step of a workflow is subject to delays and distractions. Ecommerce sites know to reduce links during the final checkout process. With complex transactions, the risk is greater that the user will have lost their focus. Remind the user what they are doing in big title text. Focus on delivering Clear and Consistent messaging and instructions, for example, adding side notes like Ally.com’s password guidance.
Standard design patterns are good, but they also throw the user into autopilot. It makes sense to break them for critical decisions. The hard part is determining what a critical decision point is. Observing user behavior, customer service records, and identifying risks to the user’s data are good clues. If something is simple enough that the users are mostly on autopilot, for example installing software, make the default action a single click.
The dark side of users on “autopilot” is that they will regularly make mistakes by not paying attention. Mistakes are generally not obvious to a system, but it is good practice to highlight destructive actions and enable recovery. Capture data in little steps. Saving form fields instead of form pages, prevents large data loss. It’s a good idea to highlight and ask for confirmation on big, destructive changes, like deleting a database. “Undo”, common on computers, but slow to come to the web, enables the user to recover from errors.
Gmail lets users undo moving a message to the trash.
Gmail also let you restore your contacts if you accidentally make a large, destructive change.
Test in realistic situations
There is an essential flaw in the two-way mirror usability test method. In the interest of copying the form of the lab-coated scientist, these rooms create an artificial aura of “science”. But as ethnographic research can tell you, real world usage is so different as to make the test questionable. It selects for a test population that is free in the middle of the day, motivated by $50, and M&Ms, puts them in an unfamiliar environment with a personal guide to focus on a specific task with no distractions. This is about as unrealistic as it gets.
In reality, the same person may have a child on their lap and only 10 minutes to look up a flight. The fact that an ecommerce session may expire after a few hours is trivial for some, but significant for people who only have a few hours a day to use the computer. “Universal Design” is a great approach, because methods to help specific disabilities tend to be useful to the general public.
Testing should go beyond the user interface and cover the basic business model. The Apple iTunes video download “rental” is for 24 hours. Unfortunately, people tend to watch movies at the same time each day, for example, after the kids go to bed. If your kids wake up, you have to finish it earlier the next day. Would it have killed them to make the rental 27 hours, so parents could actually use it?
Design for the right level of Effective Intelligence
Effective intelligence obviously varies across situations. People are ingenious at figuring out things they really want, but the simplest task is insurmountable to the unmotivated. Both scenarios are solvable, but an application that makes the wrong assumptions about its users will fail. (Interestingly, this study suggests that easier-to-use design can affect the user’s perception of difficulty, and encourage them to complete the task.)
One should adapt their strategy to the user’s desire and the problem’s complexity. Here’s an unscientific matrix for effective intelligence with software interfaces.
This matrix compares the amount a user desires to complete the task versus the complexity of the task to that user type. Different user types will have different measures of complexity, so one might create several matrices.
Low Desire, Low Complexity – The goal here is to finish these tasks as fast as possible. Follow standard design conventions, seek to eliminate steps.
Low Desire, High Complexity Complex – Tasks that the user doesn’t want to do are a danger zone. Can the problem be reconsidered or eliminated?
High Desire, Low Complexity – The easiest quadrant.
High Desire, High Complexity – This is the most interesting quadrant. A self-training interface, (integrated help, training modules) can get the user started; they will often take it the rest of the way. Video games often have a “training” level to train the user on basic skills like moving around.
Effective Intelligence is a helpful concept in the design toolbox. User research and testing are the best ways to know your users, but knowing what may limit a user in reality helps design ways to make them smarter.
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