Everyone’s a critic
A usability score from a panel of experts sounds like science. We trust that expertise without ever testing it, when the work itself can be checked.
01 · One number, please
The pull of a score
In 2019 I started an article about a method called PURE, and I never finished it. I wanted what everyone in my job wanted: one number that tells the people with the budget how good the product is, and whether it’s getting better.
The pull of that number is real. A score fits on a slide. A score can go up. And a score is cheaper than the alternative, which is putting the product in front of real people, watching where they get stuck, and doing it again after every change. Studies like that take weeks and money, so most teams run one a year, if that.
PURE promised a shortcut. I liked it then. Seven years later, I’ve read what it rests on, and I’d like to finish the article properly.
02 · How it works
A Tomatometer for usability
PURE stands for Practical Usability Rating by Experts. A team agrees on the five to ten tasks that matter most and the person who’d do them. Then a small panel of trained evaluators walks the happy path through each task and rates every step: 1 if it’s easy, 2 if it takes some thought, 3 if it’s hard. The steps add up to a task score, the tasks add up to a product score, and each gets a color, green through red. Lower is better.
When I first wrote about it, I compared it to the Tomatometer on Rotten Tomatoes: a panel of critics, a single score, a color you can read from across the room. I still think that’s the right comparison, and it’s worth following all the way through. On Rotten Tomatoes, the critics’ score and the audience score sit side by side, and the interesting movies are the ones where they disagree.
03 · The evidence
What the score rests on
PURE was introduced at CHI 2016, the main academic conference for human-computer interaction, as a case study in the extended abstracts, not as a full peer-reviewed paper. Four of its five authors worked at Intel Security, where the method was developed. The fifth runs MeasuringU, the firm that ran the study meant to validate it.
That study covered three software products. New evaluators, with about an hour of training, agreed with each other at a correlation of about 0.5 on their first try; Intel’s own team did better, between 0.6 and 0.88. The scores lined up with what users said about ease of use at about 0.5, and with the System Usability Scale at about 0.4 to 0.5. The paper calls that fair. It’s an honest word: a correlation of 0.5 means the expert score explains about a quarter of what users report. None of the write-ups says how many users took part.
Since then, the method has been taught by Nielsen Norman Group, where one of its authors went on to work, and written up by MeasuringU. I looked for an independent replication, by anyone who didn’t build or sell the method, and didn’t find one.
To their credit, its authors say much of this themselves. NN/g’s article calls PURE’s numbers less precise than measures based on user data, says it covers only ease of use, and warns that not everyone is qualified to do it. That last line is where the trouble starts.
04 · The evaluator effect
Critics disagree
PURE depends on experts agreeing about what’s hard. Usability research has been measuring how often they do for more than twenty-five years, and the answer is: not often.
In 2001, Morten Hertzum and Niels Ebbe Jacobsen reviewed eleven studies in which several evaluators looked at the same system with the same method. On average, any two of them agreed on between 5% and 65% of the problems they found. No method fixed it, experience didn’t fix it, and it held for severe problems as much as trivial ones. They wrote that relying on a single evaluator is highly questionable.
It holds even when experts watch the same people. In an early study, four evaluators watched the same four sessions, and no problem made all four of their top-ten lists. In a 2014 study, nineteen experienced professionals analyzed recordings of the same five users. The average professional reported about a third of all the problems the group found, and when two of them reported the same problem, up to 30% of the time one called it critical and the other called it minor.
PURE asks a panel to settle on one number per step, and three people in a room can do that. What the research says is that a different three people would very likely settle on a different number.
05 · Who counts as an expert
A receipt, not a test
So who’s qualified? In our industry, the most common answer is a certificate from Nielsen Norman Group.
Here’s what it is. To be UX Certified, you take five of NN/g’s live online courses, about thirty hours in all, and pass an exam after each one. The exams are online and unproctored: thirty questions, an hour, 80% to pass. Only people who attended the whole live course can sit its exam. NN/g puts the total at about $6,500, and its UX Master level, fifteen courses, at about $19,500.
NN/g states plainly that its certification is not accredited. It isn’t a degree, and nobody outside the company reviews it. It’s continuing education, sold and examined by the same company, about that company’s methods. That’s a perfectly good thing to buy if you want to learn. It isn’t evidence that the person holding it will rate a step the way the next certified person would, and the research says they mostly won’t.
None of this is a secret, and none of it is a scam: the prices, the requirements and the lack of accreditation are all published. The problem is the loop. A company teaches a method, certifies the people who learn it, and those people become the experts whose agreement the method depends on. Each piece points back at the others, and none of them points at a user.
06 · What we check instead
We can check
Here’s what bothers me most. We don’t test what we call expertise, and we trust it anyway.
Doctors earn trust through licenses because the results of their work arrive late, and you can’t try an operation before you agree to it. Design isn’t like that. What we make can be measured before anyone pays for it, and while they’re paying for it: whether a person finished the task, how long it took, whether the page loads on their phone, whether the text can be read, whether the price on the page matches the one Google shows. None of that needs a panel. It needs someone to look.
That’s why we build checking tools for designers. Our audits quote the page they read, so every finding can be checked by the person reading it. Our free tools show a page the way a screen reader, a shaky hand or aging eyes meet it. Our open numbers publish how this site is used, including the numbers that go against us. We know what good looks like, and so can anyone else who looks.
Our own tools hand out scores too, and we feel the same pull. On October 17, 2026, we ran Google’s Lighthouse on this essay, on a simulated phone, five times. It scored 100 for accessibility every time, and 97 or 98 for speed, depending on the run. Our check bookmark runs axe-core, the same engine inside Lighthouse’s accessibility score. Our shop audits report Lighthouse’s speed score, as Google’s PageSpeed Insights measures it. Our LLM view follows Lighthouse’s advice on how agents read a page.
A perfect score is lovely to look at, and it’s still a machine’s opinion of the parts a machine can see. When the UK government’s accessibility team built a page with 143 deliberate barriers and ran ten tools over it, the best one found 41% of them. So a 100 isn’t where we stop. It’s the floor: what a machine can check, it should check every time, so that people can spend their attention on what no machine can see.
That’s the difference between working with us and asking an AI assistant for a review. A prompt gets you an opinion, and a different prompt gets you a different one: the evaluator effect, with a faster critic. We don’t start with a prompt. We start with domain-driven design: we map how your business actually works, find the steps that happen the same way every time, and turn each one into a check that runs by itself, so the outcome is near certain instead of hoped for.
This site is built the same way. Before any change goes live, every label in every drawing is measured for contrast and size, more than a thousand of them; every line of text is held to the page’s rhythm in real browsers; every page must have its own share image; and nothing ships with a fact we haven’t confirmed. If one check fails, the change doesn’t go out, and nobody has to remember to look. I’ve been trying to replace account managers all my life, and this is how: not with someone who promises it’s fine, but with a check you can read for yourself.
Everyone’s a critic. You don’t have to take their word for it. You can check.
Sources
Where every number comes from
Read on October 16 and 17, 2026. NN/g says its prices change from time to time.
Report
Practical Usability Rating by Experts (PURE): A Pragmatic Approach for Scoring Product Usability·
CHI 2016 Extended Abstracts
Article
PURE MethodArticle
PUREPeer-reviewed study
The Evaluator Effect: A Chilling Fact About Usability Evaluation Methods·
International Journal of Human-Computer Interaction
Peer-reviewed study
The evaluator effect in usability studies: problem detection and severity judgments·
Proceedings of the Human Factors and Ergonomics Society
Peer-reviewed study
What you get is what you see: revisiting the evaluator effect in usability tests·
Behaviour & Information Technology
Reference
UX Certification·
Reference
UX Certification pricing·
Reference
UX Certification exams·
Guidance
Lighthouse accessibility scoreArticle
What we found when we tested tools on the world’s least-accessible webpage·
Accessibility in government blog