Too often under-represented groups do not have great digital experiences. And why is that? Because they are often excluded from the design process due to outdated, embedded ways of thinking about the research process.
More inclusive design in the world means more experiences that all people love regardless of ability, age, gender, ethnicity, or socioeconomic status. But to design inclusive products, you have to ensure you’re speaking to a diverse group of people and creating an inclusive UX research process. We all have different perspectives that change how we interact with the world around us. It’s our job as researchers to understand how we can create better experiences that take these aspects into account.
As we design new experiences, we can’t possibly take into account all of these components without inclusive research. But inclusive research is not a check-box on the path to launch but rather a fundamental change to systems, processes, and culture.
We’re all working quickly to meet the constant demands for research, balancing the needs of multiple stakeholders and teams, and keeping studies on schedule. But this means there often isn’t time to revisit our research tools and processes, especially if they’re working and successfully getting participants into the research room. But that’s precisely why we need to revisit them.
Not only do you need just to get participants in the room. You have to get the right participants to ensure you get the insights you need for an inclusive design process. If you’re still operating on old and out of date processes, you can’t achieve this.
We’ve been through this ourselves at AnswerLab with our Research Operations team. Instead of executing on research participant data our clients gave us, we started to examine our processes and advise our clients on how to ensure an inclusive and diverse recruit. To reform the old process, we started by looking at who was getting left out or ignored during typical research screening. A research screener is a questionnaire used to determine who we select as a participant for a research session. It asks questions about demographics, product usage, etc. to help you identify the participants who will help you answer your research questions.
Our team has standardized new ways of asking about demographics in our screeners to ensure we’re prioritizing participant comfort and getting more accurate, inclusive information. We recommend including a mix of participants with a range of genders, ethnicities, ages, income, education, and more in every study you conduct. Unless the study objectives or criteria of the participant requires something nuanced and specific, we recommend taking this approach for all studies.
To update old practices and habits, take a look at your current templates and processes, think about the bigger picture of who you're trying to reach and you might be getting left out, and hold yourself and your team accountable moving forward.
Typically, research organizations will have a screener template they start with for every study. Start by rethinking your template. Are you excluding participants because of older standards or out of date practices? For example, many recruiters screen out based on age, marital status, or education levels automatically. Are these practices critical to the goals of the study, or are they there simply because of outdated standards and opinions?
Form a team to help rethink your practices and develop better screeners. At AnswerLab, we created a set of internal employee taskforces to lead inclusivity initiatives with one focused on creating a new, more inclusive screener. By including various employee perspectives in the process, you’ll discover insights and opinions you might not have come to on your own.
Instead of thinking about what the “perfect” participant looks like, think about the unique perspectives you might be missing. Consider who you’re recruiting (or not recruiting) and why to help build a holistic case for why certain participants should be included. Perhaps there’s someone who doesn’t fit every piece of criteria exactly but can offer an opinion no one else would be able to. Recruit them.
Here’s the big one: accountability. Once you’ve made these decisions, swapped out questions, or changed your criteria for screening out respondents, you need to build a system to hold you and your team accountable for executing on these changes. As a part of our inclusivity journey, our team built a participant demographic tracker that allows us to see just how diverse our study populations are. It helps us identify if we’re over or under recruiting from certain groups and, subsequently, pivot to course-correct.
When possible, we keep our questions about gender open-ended so participants can answer in their own words. When open-ended isn’t possible, include expanded choices for gender in your screeners, for example, non-binary and prefer not to state. These options not only give you a more accurate understanding of your participants, but also prevent them from feeling excluded by the question choices.
In every study, we strive to recruit a group of participants whose ethnic makeup matches the U.S. Census data. Our new standards are to recruit no more than 1/3 from any one ethnicity and no more than 1/6 from any one geography, as opposed to leaning on the more general, but ambiguous instruction to “recruit a mix.” Regardless of the study’s size, our percentages of participants will always match the country’s demographics unless the study objectives ask otherwise. When working internationally, we adjust our practices to match the local market. Download our latest resource to see examples of how we re-wrote our screener question on ethnicity.
Participants over 55+ are often excluded from research due to outdated notions of tech-savviness, but we believe reaching this age group is critical to creating experiences that work for everyone. People of all ages are using technology more than they used to, and the percentage of the population who are 55 or older has grown in recent years. Prioritize getting a mix of participants across ages 18+ unless your study objectives focus on a specific age group.
Include a mix of household income levels to make sure you’re reaching a diverse group of participants with different socioeconomic circumstances. Screening out based on household income comes from outdated industry standards of who your “target customer” is. In some cases, a focus on specific income brackets, including low-income populations and high net worth individuals, is necessary to uncover specific customer needs.
This is a tricky one. During trying economic times, many potential participants may have been laid off or furloughed temporarily. We now often include those laid off or looking for work in studies where we previously may have only recruited employed participants. This serves as a good reminder to always re-think the “standards” of recruiting that might not make sense given the current landscape.
It’s very important to ask if participants need any accommodations to participate in a study, whether conducted in-person or remotely. These accommodations might include assistive technology such as screen readers, in-person accessibility needs, or remote walk-ins to ensure a seamless and timely session experience. Make sure your researcher is prepared to adjust the session questions or prototypes if necessary to accommodate these participants’ needs.
Marital status is an age-old recruiting question we believe doesn’t tell you very much anymore. Whether someone is married or not doesn’t indicate how they’re going to interact with a product or experience in the same way it used to, and collecting this information comes from out-dated social norms. By asking this question in our screener, it seemed like a way to “exclude” rather than “include” participants. Try asking about the participant’s household size as an alternative to be more inclusive and get even more accurate information. However, when it’s not relevant to the study’s objectives, for example, in B2B studies, you can omit this question altogether.
With remote research, you have the opportunity to reach rural populations that were previously very difficult to access from our in-person research labs. To aid this, we’ve started asking participants whether they live in urban, suburban, or rural areas in our screener to recruit a better range of participant lifestyles. You might also consider asking about the region they live in (e.g. Northeast, Midwest, Southeast, etc.) to make sure you’re getting better representation from across the U.S. in your studies.
For more resources, visit answerlab.com/inclusivity.
Learn more about Research Operations at AnswerLab.