#uxr

[attackcopterblog]

PRIMARY WEAPON SYSTEMS ANNOUNCES UXR MODULAR RIFLE ROLL OUT

Primary Weapon Systems has announced the much anticipated UXR Modular Rifles product roll out to dealers. Primary Weapon Systems state ” PWS (Primary Weapons Systems) is proud to announce that the newest product in the PWS portfolio, the UXR (User Xchange Rifle), is now shipping to dealers across the United States. This rifle, previously introduced to the public at SHOT Show 2024, allows for…

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[procrastinatingrockstar]

Heyo! If you have a minute, my internship is putting together a project and we'd like to know more about YOU! If you have the time, I'd love to know your thoughts!

How do you like to travel?

Thanks for taking our short survey. We're working on an app to help folks travel better and look forward to hearing your thoughts!

[andrea-c4c]

This is why it’s so important to talk to (a range of) people early on! 

[yahooaccessibility]

Dangers of Self-Reported Usability

By Danielle Lottridge, User Experience Researcher

Usability testing is a method for evaluating the ease-of-use of a product or feature by testing with with people, or “users” of a system. The goal of usability testing is to observe behavior during task flows, observe whether and how users complete flows, and note any conceptual misunderstandings that occur. Participants' reactions are important for other methods such as surveys and concept testing however in usability testing we care whether participants can get the task done. Usability testing provides direct feedback by observing how real people use a product. Usability testing tends to be structured as a one-on-one task-based interview where a facilitator prompts a participant to complete a series of tasks; for example, for an ecommerce website, we might test the usability of adding an item to the shopping cart and completing the checkout process.

One-on-one testing takes time and a facilitator. What if, to save time and money, we tried to have users report usability problems – would they be able to do it? Of course it depends! Participants who frequently participate in usability testing for services such as usertesting.com have a disproportinate amount of experience completing tasks and articulating any hiccups that they encounter along the way. They are more likely to be able to describe their mental model of what they expected and how what they encountered was different than what they expected. However, these participants have so much experience with different systems and design patterns that they may no longer be representative of the general population, but instead representative of the extremely tech savvy, or of amateur UX evaluators. Armed with this experience, these types of participants may encounter a different set of usability problems compared to the general population.

Figure 1. Sketch of Elements of a Mental Model

Image Credit https://openclipart.org/detail/187444/andrew-loomis-drawing-the-head-and-hands-potrace-43

Those with less awareness of their mental model and less experience articulating it won’t be able to report usability problems. A case in point: in a recent quantitative diary study with a few hundred participants in a gen pop sample, a market researcher measured agreement with the statement “This app is easy to use.”  Perhaps unsurprisingly, most participants reported the app was extremely easy to use! Behavioral data showed that participants were not able to complete basic tasks. Also, dozens spontaneously asked for instructions for the app. The behavioral data and requests for instructions directly contradict the self-report data. Why is this? Participants may’ve genuinely experienced the app as easy to use and didn’t realize that they weren’t able to complete basic tasks. Based on literature that says that Western people feel competent and don’t realize it when they aren’t [1], participants may feel confident in their abilities and thus don’t entertain the possibility that they weren’t able to figure out an interface. The bottom line is that self-reported usability data are easy and cheap to measure but most likely misleading. As we say in our group, bad data is worse than no data. Observing the behavior of representative participants is a gold standard in usability testing and should remain so.

[1] Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: how difficulties in recognizing one's own incompetence lead to inflated self-assessments. Journal of personality and social psychology, 77(6), 1121.

[yahooaccessibility]

Rapid Surveys to Support Design

By Frank Bentley, Senior Principal User Researcher

Often a design or product team will have a question in the course of their work where an immediate answer is needed in order to proceed. Perhaps they want to know if it's worth it to support a feature given people's current behaviors. Or perhaps they want to test some different icons for intelligibility. Ideally, they'd have answers in a few hours so that they could continue their work. Larger product teams might have multiple questions like this per week in the course of their work.

However traditional User Research activities take time. In-person studies have to be planned, participants need to be recruited and data needs to be analyzed. This can typically take a week or more. Large market research studies often take even longer and are very expensive. But product teams in agile environments need to work faster than these traditional methods can support.  

Over the past two years, we've developed a process for quickly designing, running and analyzing mid-scale surveys to support design and product questions within hours or a day at most. Frequently we can have a question one afternoon, run the survey that evening and have data by the morning of what a representative sample of Americans do. We can run dozens of these surveys every month to understand which use cases to support, where current frustrations lie and the intelligibility of designs. The key is to have a few focused questions and to deploy the survey using a large online survey platform (e.g. Survey Monkey or Amazon's MTurk) to a broad audience. These are not marketing-style attitudinal questions, but questions on actual behaviors that people engage in as a part of their everyday life, so that we can quickly quantify whether a use case is worth supporting. This method has helped us to learn that over 90% of Americans receive coupons and deals in their email and that 64% had used one in the past two weeks. We've also learned about the percentage of email users who turn off their notifications by platform and have tested a variety of icons for the Stationary feature of Yahoo Mail, finding one with 7x the recognition rate of the current design within hours of receiving the files from a designer.

Behavioral surveys like these help User Research to work at the speeds of agile teams and provide quick data about user behavior in the wild to designers and product managers to help set product strategy. And we've seen that the results are often within just a few percentage points of larger, much more expensive market research studies that can take months to fully execute. In a study using eight questions covering a range of user behaviors (everything from using coupons received in email to enabling mobile mail notifications to subscribing to particular video streaming sites), we observed an average error of only 3.6% with SurveyMonkey panels and 7.1% with MTurk panels compared to a gold-standard n=1000 market research panel. This is well within the margin of error needed for rapid feedback in the design process. If you have $100 (the approximate cost of a user study) and 2-3 hours, you can quickly get representative data from 150 participants and move design along at a rapid pace! Running multiple studies over time and triangulating findings can serve to further increase confidence in the results.

[yahooaccessibility]

Expanding the Notion of "User"

By Mike Shebanek, Senior Director of Accessibility

Starting today, you’ll notice some significant changes to our blog, both in design and in content, that better reflect who we are and what we do. I’d like to to tell you why we’re making these changes and what you can look forward to as you follow our blog.

One of the things that makes Yahoo’s approach to accessibility unique is that its Accessibility Team and its User Experience Research Team are integrated. That may sound like an obvious approach, but it hasn’t always been this way at Yahoo and we’ve come to find out it’s pretty unusual in the tech industry. In the all-too-rare organizations that actually have a dedicated Accessibility Team, they often report to the chief legal counsel, or are part of an administrative or compliance group. Other times they’re siloed in one division, which prevents them from being able to impact product development or customer support in another. Having a dedicated Accessibility Team and where that team is placed in an organization says a lot about a company’s values, and this is especially true of Yahoo.

In our case, we’re part of a team called User Research and Accessibility or UXRA for short. Our team supports the entire company – every division, every VP, every employee – and it is tasked with representing our users’ unique needs, requirements and points of view in every activity we undertake. We are not just “closely aligned” with our user research team – we are the same team! We share user study labs, training, techniques, findings and the same mission: to accurately represent all users. We work to ensure that users come first in whatever we do, and that this includes people with disabilities, of all ages, of all genders and of all abilities. So, whenever we perform a user study, take a survey, gather product feedback or identify requirements, people with disabilities are included along with everyone else. We can’t imagine any other way.

To better reflect this mission and to give you deeper insight into how we go about understanding and representing our users, you’ll be hearing more from our User Researchers in addition to our Accessibility Team members on this blog.  We have a lot of exciting things to share, and we hope it is informative and inspiring to you and our industry peers as we all continue to reach for greater inclusion.

[algoworks]

No direct access to users? You're not stuck.

From tapping internal teams to scanning app reviews and analytics, there are smart ways to gather real user insights without user interviews. These field-tested methods help you validate assumptions and build experiences that work. Which one do you rely on when users aren’t reachable?

For expert UX strategies, connect with us at: https://www.algoworks.com/ui-ux/

[dianas]

UTAUT is grounded in four main variables that explain how humans think about embracing a new technology: performance expectancy, effort expectancy, social influence, and facilitating conditions. Each one is a lens through which to look as we build, market, and use AI products.

https://every.to/learning-curve/the-psychology-of-viral-technologies