Based on extensive research, we've developed special Web usability guidelines for young children, teenagers, and senior citizens. Each of these age groups have specific characteristics that designers must understand to attract young or old users to their sites.
But what about people in the middle? We don't even have a real name for them — I usually just call people between 25 and 60 years old " mainstream users." This is by far the most important age group for several reasons:
There are more of them than in the young or old age groups. In the U.S., 49% of the population is between 25 and 60 years old (35% are younger and 16% are older).
Mainstream users have all the good jobs; they're the richest , and they spend the most money online.
Almost all B2B sites target this age group. This is especially true if we extend the "mainstream" definition to include people up to 65 years old; beyond that, we officially start calling them "seniors" in our usability research.
Virtually all intranet users fall within this group, especially if we extend the age range to 65.
I just finished analyzing the quantitative data from our study last month to update the course on Fundamental Guidelines for Web Usability. We have stunning new statistics for important Web behaviors like search and scrolling, as well as notable numbers to quantify user attention. All of these will be presented at my upcoming usability conference.
We also got insights into middle-aged users that I couldn't fit into my presentation. In programming the conference, I focus relentlessly on giving attendees "news you can use," so we cover only the most important findings for maximizing a website's business value. As you'll see, the following age-dependent data doesn't meet this criterion. It's interesting, but doesn't have a high-ROI factor. Luckily, cyberspace has fewer constraints than real-time events, so I can write a column about the purely fascinating (but not money-making) slides I had to cut. Here we go:
User Performance Data by Age
Between the ages of 25 and 60, the time users need to complete website tasks increases by 0.8% per year.
In other words, a 40-year-old user will take 8% longer than a 30-year-old user to accomplish the same task. And a 50-year-old user will require an additional 8% more time. (Mathematically inclined readers will note that this increase is linear, not exponential.)
This finding is statistically significant at the 5% level, given the 61 users in our study.
Does this mean that people in their 40s or 50s can't do their jobs? Not at all. There are many other ways in which people get better with age.
Individual differences swamp the tiny age-related difference in the 25- to 60-year-old group. Users are extraordinarily variable in their use of websites and intranets.
I have a 5-5-5 rule for task times while using websites: Across a broad range of studies, our data shows that
the slowest 5% of users are
about 5 times as slow
as the fastest 5% of users,
meaning that the slowest users need 400% more time to perform the same tasks. The 0.8% difference caused by each year of aging pales in comparison.
So, a fast 50-year-old will beat a slow 30-year-old every day — by several hundred percent.
Why Web Performance Declines With Age
Two factors cause the 0.8% increase in task time. For each additional year of age, users:
spend 0.5% more time on each page, and
visit 0.3% more pages per task.
In other words, the biggest factor is that older users need more time to understand pages, scan the text, and extract the information. A smaller — but still substantial — problem is that people have more trouble navigating websites as they age.
It's not surprising that users need more time to use websites as they age, even within the mainstream group of 25–60 year olds. The human aging process starts around age 25 and causes erosion of cognitive resources, loss of visual acuity, degraded reaction times, and reduced dexterity. People need more time for the same mental operations; they have less memory capacity and take longer to process the same perceptual input.
All of these elements of human performance impact the speed with which users can get something done on a website.
There's also a covariant: the age at which people started using the Web. Because the Web is relatively new, a 50-year-old might have started using it at age 40, whereas a 30-year-old might have started at age 20. In contrast, by 2050, a 50-year-old will have used the Web since age 5, and thus benefit from 45 years of experience. A 30-year-old user in 2050 will have only 25 years' Web experience. This added experience might eventually allow older users to catch up and somewhat reduce the 0.8% gap. Although we obviously can't predict the future, my guess is that the age penalty will drop to around 0.5%/year. Still, this doesn't matter much for your Web strategy over the next 10 years: the 0.8% level is where we're at and where we'll remain for some time.
Mainstream Aging vs. Senior Citizens
So, for each year that people age between 25 and 60, our current estimate is that they get 0.8% slower at using websites.
How does this compare with our research findings that senior citizens are 74% slower at using websites than mainstream users? A typical senior at 75 is 40 years older than a typical mainstream user at 35, so 0.8% per year should correspond to only a 32% slow-down for seniors.
The difference here is explained by the fact that aging starts early, but accelerates drastically around 60 years of age, and especially after 70 years. Curves of cognitive, perceptual, and motor-skill decline have a hockey-stick shape.
This is why there are separate usability guidelines for making websites usable for seniors. After 65 years of age or so, differences in user needs are so drastic that we require explicit steps to cater to them.
So, the 0.8%/year slow-down is valid only for the mainstream period of 25–60 years of age. For older users, performance declines faster.
Income and Website Performance
Within the 25–60 age group, there is a strong positive correlation between age and income: senior staff members tend to be paid more than junior staff members. I made my estimate of a 0.8% increase in task time per year after separating the effects of age and income. Thus, this is an effect of age on its own, controlling for income.
After separating out the effects of age, income showed a marginally significant affect (p=.09) on the Web performance of our study's 61 users.
After removing the age effect, the income effect is that people need 2.2% less time to use a website for every $10,000 increase in earnings.
Here, we must consider causality: it's not because people make more money that they are better at using websites. In fact, the explanation is just the opposite: it's because people are better at using websites that they get paid more. Or, more realistically, people with superior cognitive resources are faster at using websites, and bigger brains bring bigger bucks.
(Outside the laboratory, there might indeed be some tendency to better Web performance simply because people are rich: being able to afford a bigger monitor can definitely improve your website use because you can see more information without scrolling. In our study, however, all test participants used the same type computer, the same screen, and the same speed Internet connection, so rich users didn't have equipment advantages. Thus, that's not the reason for our finding.)
Implications of the 0.8%/Year Performance Decrease
What are the practical implications of these new research findings for designing websites? Not much. Although you need separate guidelines for seniors and truly young users, you don't need different usability guidelines for your 50-year-old vs. 30-year-old customers.
(Obviously, 50- and 30-year-old users are often interested in different content — they might have different taste in music, for example — but they don't need different interaction features to access their preferred content.)
Given the Web's current state, a few percentage points' difference is simply not enough to warrant special usability attention. You should focus on those usability issues that can almost double the business value of your site (or your intranet).
Usually, it's enough to test with 5 users because a handful of test sessions suffice to identify these huge design blunders. The fact that we needed 61 test users to discover the age differences within the mainstream range is a good indication that we're talking about a subtle effect that should be a secondary — or tertiary — consideration in practical design projects.
I do have two actionable conclusions for you:
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