As we’ve been researching what design teams need to do to create great user experiences, we’ve stumbled across an interesting finding. It’s the closest thing we’ve found to a silver bullet when it comes to reliably improving the designs teams produce.
The solution? Exposure hours. The number of hours each team member is exposed directly to real users interacting with the team’s designs or the team’s competitor’s designs. There is a direct correlation between this exposure and the improvements we see in the designs that team produces.
The horizontal axis represents the investment the organization makes. As investment increases, the organization spends more resources on improving the quality (remember, Noriaka was a quality guy at heart) or adding new capabilities.
The vertical dimension represents the satisfaction of the user, moving from an extreme negative of frustration to an extreme positive of delight. (Neutral satisfaction being neither frustrated nor delighted is in the middle of the axis.)
It’s against the backdrop of these two axes that we see how the Kano Model works. It shows us there are three forces at work, which we can use to predict our users’ satisfaction with the investment we make.
A/B testing is an effective approach to use science to design and deliver deeply-frustrating user experiences.
A/B testing without upfront research is just random monkeys testing random designs to see which of those designs do “best” against random criteria.
If drug testing was actually implemented like most A/B tests, you’d give 2 drugs to 2 groups of people and pick the “winner” by whichever group had fewer deaths.
“Can I ask you one more question?”
“Sure.”
“Have you already decided on the next barn to burn?”
This caused him to furrow up wrinkles between his eyes; then he inhaled audibly through his nose. “Well, yes. As a matter of fact, I have.”
I sipped the last of my beer and said nothing.
“A great barn. The first barn really worth burning in ages. Fact is, I went and checked it out only today.”
“Which means, it must be nearby.”
“Very near,” he confirmed.
I walked around with a map, penciling in X’s wherever there was a barn or shed. For the next three days, I covered four kilometers in all four directions. Living toward the outskirts of town, there are still a good many farmers in the vicinity. So it came to a considerable number of barns—sixteen altogether.
I carefully checked the condition of each of these, and from the sixteen I eliminated all those where there were houses in the immediate proximity or greenhouses alongside. I also eliminated those in which there were farm implements or chemicals or signs that they were still in active use. I didn’t imagine he’d want to burn tools or fertilizer. That left five barns.
Every morning, I still run past those five barns. Not one of them has yet burned down. Nor do I hear of any barn fires. Come December, the birds strafe overhead. And I keep getting older. Although just now and then, in the depths of the night, I’ll think about barns burning to the ground.