You’ve spent ages clarifying your thinking (maybe atop a mountain even).
You’re still likely to fall prey to a few biases from time to time.
As Soll, Milkman, and Payne mention in their HBR article,
“Even the smartest people exhibit biases in their judgments and choices. It’s foolhardy to think we can overcome them through sheer will. But we can anticipate and outsmart them by nudging ourselves in the right direction when it’s time to make a call.”
As a researcher, you would rather not be caught being foolhardy.
Your participants should ideally be selected randomly from your target population.
Selection bias creeps in when your pool of participants isn’t reliable.
All the inputs you receive during your research should be taken into account.
Confirmation bias pushes you to disregard some of the information that goes against your preconceived notions and opinions.
You instead end up only listening to the data points that confirm what you already believe in.
If you are running a user interview and the user says something you disagree with, you should make note of it and not enter a debate with them. If you are running a usability test and the participant uses your product in ways you didn’t intend, you should try not to correct them — instead, follow them as they figure your product out.
Debating and correcting participants may be keeping UXRs away from incredible new insights they hadn’t considered before.
As a social species, we all tend to moderate our conversations to what we consider socially acceptable or favorable for others in the conversation. This is great when it prevents bar fights from happening, but is disastrous for your research.
This bias can creep in for participants in UX research studies and the researcher’s job is to ensure that it doesn’t happen.
Participants may provide overly positive feedback about a product to avoid appearing critical. They may under-report any difficulties or challenges they encountered during a usability test to avoid feeling incompetent. This can result in an inaccurate representation of actual user experiences and behaviors, leading to flawed conclusions and design decisions.
We are terrible at remembering things. Can you recall the 2nd bias we discussed without scrolling up?
Recall bias creeps into UX research when participants remember events in a way that’s disconnected from how they actually happened.
If you are interviewing someone about their experience with a new feature over the past week, it’s highly likely that they aren’t describing their experience accurately. This isn’t because they are evil (most of ‘em), they just don’t remember.
This bias is named after a 1920s study that concluded that workers would improve their behavior just because they were being observed. Researchers should be mindful of the Hawthorne effect when trying to study true user behavior.
As Will Kenton writes in this article, the presence and impact of the Hawthorne effect has come under scrutiny of late.
“modern attempts to replicate the Hawthorne Effect have been inconclusive.
Only seven out of 40 such studies found any evidence of the effect.”
Even though it makes intuitive sense, this lack of evidence should compel you to take the Hawthorne bias with a grain of salt.
UX researchers bring their cultural perspectives, assumptions, and biases into the research process. So do participants.
This can lead to misinterpretations or misrepresentations of user experiences.
If you are conducting research for a dating app and are from a culture that considers dating to be taboo (South Asia represent!), you might value privacy and secrecy more than your participants from cultures where dating is normalized.
If you are negotiating with a seller over the price of an article (say a statue), the seller might use a trick called anchoring. They’ll name the first price and you will end up negotiating around that price, instead of deciding something independently. You’ll get “anchored” to their initial offer and put too much weightage on it.
This is fun when selling statues, but you should stay away from anchoring bias in UX Research. This bias creeps into a user’s responses if you provide non-neutral information upfront. If you present your product in a positive light from the get-go, the user is likely to moderate their own responses in a way that conforms to your initial information.
This prevents you from getting genuine user feedback.
We are more likely to attribute others’ mistakes to their faults and not to situational factors. This comes up in UXR as a tendency to blame the users for their inability to interact with the product, instead of the product itself.
This impacts both researchers and users, both of whom end up blaming the user. Was it strange that the website could only be navigated using a joystick? No — it’s the user’s fault for not having one at their office.
These biases scratch the surface of how irrational our decision-making often is.
The greatest antidote to this irrationality is consistent research with a wide variety of participants.
Looppanel makes user interviews so effortless, you can’t help but run them consistently.
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