If you think you’re going to achieve all that by patting yourself on the back, you are mistaken, compadré. To do great things, you must prove yourself wrong—as often as possible.
UX is Inherently Negative
That may seem like a weird way to begin an article about the virtues of using data to reach new levels of super duper product amazing-ness, but it’s true. UX is not made of rainbows and sunshine.
“But,” you might say “isn’t empathy a big part of UX?” Sure it is. And empathy is real swell, Wally. But the reason empathy is important for UX designers is because it makes you better at finding problems. UX is inherently negative because it is all about solving problems. Your problems. And you can’t solve a problem if you can’t find it.
The Average Person Never, Ever Tries to Find Problems With Their Own Work
Your intuition is actually built to fight the idea that something is wrong with you, your product, your company or even your personal preferences. Even if it’s true.
Your ideas, your work and all the planning and effort that go into them have value to you. It’s hard to have empathy for the users when they disagree with everything you worked so hard to create. The most important, and most valuable, and most interesting problems in your digital product are invisible, counter-intuitive, and frankly, you probably feel pretty good about the things that cause those problems. After all, you created them in the first place. You wouldn’t have gone to all that trouble if it wasn’t the right thing to do, right?
Data Never Lies… But Sometimes the Truth Hurts
In UX design, we have a secret weapon that can eliminate all those natural biases and show us clearly when something is working and when it isn’t. You just have to know how to use it and how to think about it.
You might be missing information that will give you valuable insights. You might be assuming that your users are experts when that isn’t true. You might have chosen a design that is beautiful, but ineffective. Or maybe your brilliant copywriter has made all of your form labels so clever that nobody understands them.
In those cases, you might make content that nobody shares, or see that advanced features aren’t being used, or get lots of positive feedback, but no sales or conversions. If there is a problem, the data will show you. If there is an improvement, the data will show you. The question is: what are you looking for?
If You Look For Proof That You Are Right: You Will Find It
Everyone’s first instinct when they start measuring digital things is to use data to prove what they already believe: that their shit smells like magic. No matter what the truth is, you can always twist your interpretation to see your own greatness in the numbers.
That 70% bounce rate suddenly becomes “good for your industry.” Everybody talks about the “amazing traffic” from your campaign, while ignoring the terrible click-through rate on the landing page. Or you measure how many people have registered instead of what percentage of people have registered, because big numbers are way more fun than small percentages.
We all want to be right. But like they say on CSI, you shouldn’t try to prove your theory is right. You should follow the evidence.
Ask yourself a few simple questions:
- What are the things that seem so obvious that you never actually thought to check if they’re true?
- If a problem exists somewhere, what is the sneakiest place it could hide?
- 6 months from now, what will you wish you did better?
- What else could cause the statistics you’re seeing now?
- Do you believe good news by default, or do you question it?
This may seem like a negative way of thinking, but that’s only because you’re thinking about yourself. If you were asking these questions about a competitor, you’d be excited to find all the places where they might have screwed up.
If it’s good enough to analyze your competitors, why isn’t it good enough to analyze yourself?
Prove Yourself Right By Proving Yourself Wrong—A Lot
Every time you find a problem, or a weakness, or a result that is worse than you thought, you have ruled something out. That means your next decision will be smarter by default. If you can prove yourself wrong early, and often, you will only be left with the options that work, rather than the options you like most.
Eventually, you will start creating sequences of improvements rather than sequences of preferences. Proving yourself wrong is only negative in the short term. In the long term, it focuses your efforts and eliminates all the “low-hanging fruit” that are easy and fast, but wrong. You will start spending your time on things that deliver results.
So, get into that data, assume that you have indeed done something wrong, and start looking for problems to solve.
Now you’re doing UX for real.