Two Biases and one Effect: UX perspectives.

As a UX Researcher, I face multiple challenges in my everyday life. These challenges really vary, from how I make my work more visible to my stakeholders to which is the combination of methods that I need to follow to tackle a problem more successfully. These topics, by the way, are both extremely relevant and very important, but I am gonna touch them separately in some other blogs (probably!).

But there are some specific challenges that are related to my work itself when I am actually doing research and trying to identify user patterns, create stories for uncovered user needs and pain points and help the shaping of the product roadmap with data-informed ideas. When I and every researcher does research, they need to be able to produce insights. These insights don’t need to be homogeneous or unanimous, but they need to be able to shape a clear story even if there are contradictions in them.

Imagine that you work in a mobile app that targets a specific niche audience like outdoor enthusiasts. This mobile app suggests directions to popular trails and campsites and tips for staying safe in the wilderness. You are a nature-lover yourself and love camping in lakes (even the last year, you spend more than 6 months doing so, not because you wanted to conduct a field study, but simply because you love it!). Your stakeholders are thinking to review specific features of the app and re-prioritize the content provided (even re-design particular fields or the main menus) since they saw a decrease in the engagement of the app. Now, it’s your turn to conduct some UX research to find out the whats, whys, and (why not?) hows.

You recruit 8 people (mainly your own customers) for interviews, you prepare an interview script and you are ready for many follow-up questions which are outside your script. You start discovering that people love the app but most of them think that this addresses mostly professionals, since many trails that the app suggests, require a piece of equipment, which many of the users do not have. Is this a discovery for you? You knew from the beginning that something like that might arise, not only because people say that, but also because you are a nature lover yourself, you use the app and you know that you need equipment for most of the trails suggested there. After conducting this research, you are ready to present the data to your stakeholders, letting them know about the “data-informed” truth and asking them to immediately make the possibility to rent or buy equipment more prominent (maybe in the top menu of your app). But is it like this? So here we have the first bias: the Confirmation Bias — which is a cognitive bias where we, researchers tend to seek out and interpret information in a way that confirms our existing beliefs or biases.

Now, you should go back and ask yourself, did I recruit a diverse group of people with different backgrounds and perspectives? By collecting feedback from a variety of users, UX Researchers are able to identify patterns in how people interact with the product and identify areas where biases may be affecting user perceptions.

Plus, is your “data-informed” truth, really a “data-informed” truth? Have you triangulated your truth? (Triangulation again might be another topic for another blog!). Have you quantified your knowledge somehow? Have you taken into consideration that some users talked about weather alerts, that the app does not support and how this could help them predict the quality of their trail? Or are you mostly confirmed that making more visible that your app is selling or renting equipment to users is going to make it great again? Or even suggesting easier routes can grab the attention of more users? Did you simply choose to forget about other insights? And here we have the second bias — the Experimenter Bias. What happens with experimenter bias is that when a researcher is sharing their research findings with others, they tend to believe and share information that only agrees with their expectations. In other words, they promote and talk about things that are aligned with what they expected in that research study, and neglect to mention the parts that do not agree with their experiment or hypothesis.

Now, you kinda overcome the biases and finally decide to simply continue your study and iterate the design of it to have richer data (you may conduct blind studies or follow the “randomization” technique if you are a quantitative researcher or combine your interviews with other methods to be able to compare the results).

The new evidence shows that you may need a whole reconstruction of specific elements of your mobile app, which may lead this not to be the one you loved and the one that fits your own expectations as a user of it. But is this right? Or you should first try to share the ideas you had before? So here comes the Semmelweis Effect — which is the tendency to reject new evidence that contradicts a paradigm and what people in your company or even you already believe to be true. For that reason, you need to be open to innovation opportunities and be able to challenge the status quo. Don’t ever forget that you are not your user and start exploring these new approaches that your customers suggested in your studies, test them again with them, and finally align the product to meet the needs and goals of your customer.

What I always say to myself is: Rome wasn’t built on a day — and you should expect that the customer experience on your product/service will take longer than a day to be built and to be steady. When working in a UX position, be sure that you first love the interaction of the people with your product/service, even more than the product/service itself. Otherwise, quit immediately.