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Usability Testing

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1 min read

Avoiding bias in the oh-so-human world of user testing

"Dear Optimal WorkshopMy question is about biasing users with the wording of questions. It seems that my co-workers and I spend too much time debating the wording of task items in usability tests or questions on surveys. Do you have any 'best practices' for wordings that evoke unbiased feedback from users?" — Dominic

Dear Dominic, Oh I feel your pain! I once sat through a two hour meeting that was dominated by a discussion on the merits of question marks!It's funny how wanting to do right by users and clients can tangle us up like fine chains in an old jewellery box. In my mind, we risk provoking bias when any aspect of our research (from question wording to test environment) influences participants away from an authentic response. So there are important things to consider outside of the wording of questions as well. I'll share my favorite tips, and then follow it up with a must-read resource or two.

Balance your open and closed questions

The right balance of open and closed questions is essential to obtaining unbiased feedback from your users. Ask closed questions only when you want a very specific answer like 'How old are you?' or 'Are you employed?' and ask open questions when you want to gain an understanding of what they think or feel. For example, don’t ask the participant'Would you be pleased with that?' (closed question). Instead, ask 'How do you feel about that?' or even better 'How do you think that might work?' Same advice goes for surveys, and be sure to give participants enough space to respond properly — fifty characters isn’t going to cut it.

Avoid using words that are linked to an emotion

The above questions lead me to my next point — don’t use words like ‘happy’. Don’t ask if they like or dislike something. Planting emotion based words in a survey or usability test is an invite for them to tell you what they think you want to hear . No one wants to be seen as being disagreeable. If you word a question like this, chances are they will end up agreeing with the question itself, not the content or meaning behind it...does that make sense? Emotion based questions only serve to distract from the purpose of the testing — leave them at home.

Keep it simple and avoid jargon

No one wants to look stupid by not understanding the terms used in the question. If it’s too complicated, your user might just agree or tell you what they think you want to hear to avoid embarrassment. Another issue with jargon is that some terms may have multiple meanings which can trigger a biased reaction depending on the user’s understanding of the term. A friend of mine once participated in user testing where they were asked if what they were seeing made them feel ‘aroused’. From a psychology perspective, that means you’re awake and reacting to stimuli.

From the user's perspective? I’ll let you fill in the blanks on that one. Avoid using long, wordy sentences when asking questions or setting tasks in surveys and usability testing. I’ve seen plenty of instances of overly complicated questions that make the user tune out (trust me, you would too!). And because people don't tend to admit their attention has wandered during a task, you risk getting a response that lacks authenticity — maybe even one that aims to please (just a thought...).

Encourage participants to share their experiences (instead of tying them up in hypotheticals)

Instead of asking your user what they think they would do in a given scenario, ask them to share an example of a time when they actually did do it. Try asking questions along the lines of 'Can you tell me about a time when you….?' or 'How many times in the last 12 months have you...?' Asking them to recall an experience they had allows you to gain factual insights from your survey or usability test, not hypothetical maybes that are prone to bias.

Focus the conversation by asking questions in a logical order

If you ask usability testing or survey questions in an order that doesn’t quite follow a logical flow, the user may think that the order holds some sort of significance which in turn may change the way they respond. It’s a good idea to ensure that the questions tell a story and follow a logical progression for example the steps in a process — don’t ask me if I’d be interested in registering for a service if you haven’t introduced the concept yet (you’d be surprised how often this happens!). For further reading on this, be sure to check out this great article from usertesting.com.

More than words — the usability testing experience as a whole

Reducing bias by asking questions the right way is really just one part of the picture. You can also reduce bias by influencing the wider aspects of the user testing process, and ensuring the participant is comfortable and relaxed.

Don’t let the designer facilitate the testing

This isn’t always possible, but it’s a good idea to try to get someone else to facilitate the usability testing on your design (and choose to observe if you like). This will prevent you from bringing your own bias into the room, and participants will be more comfortable being honest when the designer isn't asking the questions. I've seen participants visibly relax when I've told them I'm not the designer of a particular website, when it's apparent they've arrived expecting that to be the case.

Minimize discomfort and give observers a role

The more comfortable your participants are, with both the tester and the observer, the more they can be themselves. There are labs out there with two-way mirrors to hide observers, but in all honesty the police interrogation room isn’t always the greatest look! I prefer to have the observer in the testing room, while being conscious that participants may instinctively be uncomfortable with being observed. I’ve seen observer guidelines that insist observers (in the room) stay completely silent the entire time, but I think that can be pretty creepy for participants! Here's what works best (in my humble opinion).

The facilitator leads the testing session, of course, but the observer is able to pipe up occasionally, mostly for clarification purposes, and certainly join in the welcoming, 'How's the weather?' chit chat before the session begins. In fact, when I observe usability testing, I like to be the one who collects the participant from the foyer. I’m the first person they see and it’s my job to make them feel welcome and comfortable, so when they find out I'll be observing, they know me already. Anything you can do to make the participant feel at home will increase the authenticity of their responses.

A note to finish

At the end of the day the reality is we’re all susceptible to bias. Despite your best efforts you’re never going to eradicate it completely, but just being aware of and understanding it goes a long way to reducing its impacts. Usability testing is, after all, something we design. I’ll leave you with this quote from Jeff Sauro's must-read article on 9 biases to watch out for in usability testing:

"We do the best we can to simulate a scenario that is as close to what users would actually do .... However, no amount of realism in the tasks, data, software or environment can change the fact that the whole thing is contrived. This doesn't mean it's not worth doing."

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1 min read

First click testing data: Correct first click lead to 3X higher task success

In 2009, Bob Bailey and Cari Wolfson published published findings that changed how we approach first click testing and usability testing. They analyzed 12 scenario-based user tests and found that if someone gets their first click right, they're about twice as likely to complete their task successfully. This finding was so compelling that we built First Click Testing (formerly Chalkmark) specifically to help teams test this.  But we'd never actually validated their research using our own data, until now.

Turns out, we're sitting on one of the world's largest databases of tree testing results. So we analyzed millions of task responses to see if the "first click predicts success" hypothesis holds up.

It does. Convincingly.

Users who get their first click correct are nearly three times more likely to complete their task successfully (70% vs 24% success rate).

Here's how we validated the original study, what our data shows, and why first clicks matter more than you might think.

Original first click testing study: 87% task success rate

Bob and Cari analyzed data from twelve usability studies on websites and products with varying amounts and types of content, a range of subject matter complexity, and distinct user interfaces. They found that people were about twice as likely to complete a task successfully if they got their first click right, than if they got it wrong:

If the first click was correct, the chances of getting the entire scenario correct was 87% if the first click was incorrect, the chances of eventually getting the scenario correct was only 46%.

Our Tree Testing data: First clicks predict 70% task success rate

We analyzed millions of tree testing responses in our database. We've found that people who get the first click correct are almost three times as likely to complete a task successfully:

If the first click was correct, the chances of getting the entire scenario correct was 70% if the first click was incorrect, the chances of eventually getting the scenario correct was 24%

To give you another perspective on the same data, here's the inverse:

If the first click was correct, the chances of getting the entire scenario incorrect was 30% if the first click was incorrect, the chances of getting the whole scenario incorrect was 76%

How Tree Testing measures first click success and task completion

Bob and Cari proved the usefulness of the methodology by linking two key metrics in scenario-based usability studies: first clicks and task success. First Click Testing doesn't measure task success — it's up to the researcher to determine as they're setting up the study what constitutes 'success', and then to interpret the results accordingly. Tree Testing (formerly Treejack) does measure task success — and first clicks.

In a tree test, participants are asked to complete a task by clicking though a text-only version of a website hierarchy, and then clicking 'I'd find it here' when they've chosen an answer. Each task in a tree test has a pre-determined correct answer — as was the case in Bob and Cari's usability studies — and every click is recorded, so we can see participant paths in detail.

Thus, every single time a person completes an individual tree testing task, we record both their first click and whether they are successful or not. When we came to test the 'correct first click leads to task success' hypothesis, we could therefore mine data from millions of task.

To illustrate this, have a look at the results for one task. The overall Task result, you see a score for success and directness, and a breakdown of whether each Success, Fail, or Skip was direct (they went straight to an answer), or indirect (they went back up the tree before they selected an answer):

Tree testing task results showing success and directness scores

In the pie tree for the same task, you can look in more detail at how many people went the wrong way from a label (each label representing one page of your website):

Pie tree visualization showing first click paths in tree testing

In the First Click tab, you get a percentage breakdown of which label people clicked first to complete the task:

First click data breakdown by label in tree testing

And in the Paths tab, you can view individual participant paths in detail (including first clicks), and can filter the table by direct and indirect success, fails, and skips (this table is only displaying direct success and direct fail paths):

Participant path analysis showing direct success and fail rates

How to run first click tests: Best practices for usability testing

First click analysis is one of the most predictive metrics in usability testing. Whether you're testing wireframes, landing pages, or information architecture, measuring first click success gives you early insight into whether your design will work.

This analysis reinforces something we already knew: first clicks matterIt is worth your time to get that first impression right. You have plenty of options for measuring the link between first clicks and task success in your scenario-based usability tests. From simply noting where your participants go during observations, to gathering quantitative first click data via online tools, you'll win either way. And if you want quantitative first click data, Optimal has you covered. First Click Testing works for wireframes and landing pages, while Tree Testing validates your information architecture.

To finish, here are a few invaluable insights from other researchers on getting the most from first click testing:

About this study

This analysis was conducted in 2015 using millions of task responses from Optimal’s First Click and Tree Testing tools. While the dataset predates recent UI trends, the underlying behavioral principle, that a correct first click strongly predicts task success, remains consistent with modern usability research.

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