What is a confidence interval? I wanted to know that recently and turned to one of my favorite books: Measuring the User Experience, by Tom Tullis and Bill Albert. And here’s what they say:
“Confidence intervals are extremely valuable for any usability professional. A confidence interval is a range that estimates the true population value for a statistic.”
Then they go on to explain how you calculate a confidence interval in Excel. Which is fine, but I have to admit that I wasn’t entirely sure that once I’d calculated it, I really knew what I’d done or what it meant. So I trawled through various statistics books to gain a better understanding of confidence intervals, and this column is the result. Read More
You’ve just completed a readout of your latest ground-breaking research, presenting an hour-long slideshow, and hopefully, you’ve wowed your audience with what you’ve shown them. But all too often, after you’ve reported your research results, everyone returns to their workspace and develops a serious case of insight amnesia. Stakeholders quickly forget the juicy morsels of information that would make your company’s products better. Your insights remain stuck in your slide deck and may never again see the light of day.
There are two questions that arise from this dilemma: First, how can you make your research insights more readily available to product teams so they don’t have to slog through your deck to find them? There are multiple, well-known solutions to this problem. The second problem, which is the focus of this article, is how can you ensure that your product team uses your research insights? Read More
The amount of data we produce every day is growing exponentially. This explosion of raw data means synthesis, analysis, and interpretation are more important than ever before. Without the right processes and tools in place to understand and act on our data, it has little value. It is essential that we understand what data is available, how it can answer pressing questions, and how it can enable action.
As UX professionals, we collect a wide array of data through a variety of sources and techniques—from market trends to one-on-one interviews to product-usage data to usability testing to sales feedback. We must collate, classify, and comprehend disparate sources of data to create a more holistic understanding of whatever question we need to answer. While the volume of data might seem overwhelming at first, design thinking and a tinkering mindset are invaluable in helping to break down the problem, define a plan of action, and iterate and refine solutions as necessary to turn the raw data into actionable insights and concrete products. Read More