In an industry where we rely on research data to improve product designs, we need to take steps to ensure that our sample for testing reflects all intended users; we need to ask, “is this product really designed for all intended users, including those who do not conform to the gender binary?”
An outpouring of data in recent years has shown that failing to consider various body types in design has led to a multitude of problems. These issues include car safety, comfort when using a phone, ease in using voice recognition software, and algorithms reproducing biases in search platforms, among others (Criado Perez). These design problems exist, in part, because the products were designed with cisgender men in mind and because it was wrongly assumed that those designs would work for all bodies. To remedy this, products need to be designed for all genders in order to be designed for all body types, since someone’s gender is not a good indication of their body size or proportions.
So, what is our responsibility as UX researchers? How can we update our research and design practices to increase gender diversity and best serve our end users? Below are some actions we can take now:
- Create expansive gender quotas as opposed to using the gender binary. This keeps the research accountable and ensures that data is gathered from people of multiple genders.
- Ask respondents’ gender with an open-ended, fill-in-the-blank response. This signals to people that we respect their gender identity.
- Ask for respondents’ pronouns and use them during all interactions. It’s important to ask for both someone’s gender and pronouns because they are not synonymous and might not be conventionally paired. Since gender and pronouns are not the same, it’s important to not assume neither pronouns nor gender, an assumption can be inaccurate and therefore harmful. This will help convey to participants that we respect their pronouns and are taking steps to create a safe environment for them.
- Use participants’ self-reported gender and pronouns. This indicates that the sample is more closely aligned with real-world users and may account for some nuances that a more limited sample would miss.
Recommendations and design:
- Use gender neutral language and images. Be more descriptive and specific when talking about who the instructions pertain to and what message needs to come across. For example, is it that women cannot be pregnant while using this product? Or is it that anyone with a uterus cannot be pregnant when using this product?
- Gender-neutral and specific language could also better serve users of all races and ethnicities. For example, instead of instructions saying “men must shave their abdomen before applying the product,” it could read, “people with hair on their abdomen must shave before applying the product.” This simple change in language not only recognizes that people with hair on their abdomen might not be men and that some men might not have hair on their abdomens, but it also addresses that people of many races and ethnicities naturally have hair on their abdomen.
We won’t know how gender impacts the use of a product or service, if at all, until we collect more data and refine our research processes. Once we have data from a sample that encompasses more genders, we can analyze our results based on gender identity and see if use cases fall along gendered lines. If so, then we refine our design, and if not, we know that the product works for the representative population we tested, and that, as always, we can continue to make our research more reflective of real-world users.