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
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
In the last edition of Discovery, I explained how to collect data during your early-phase prototype research using tally sheets. If you missed that column, you might want to read it before reading this column to ensure you’ll get the most out of this one.
In this column, I’ll cover data analysis for a completed tally sheet, focusing on the following key areas:
findings versus insights—What’s the difference?
methods of analysis—We’ll look at grounded-theory techniques, using codes, and constant comparative analysis.
identifying themes in the data—These include the obvious, the less obvious, the not-so obvious, and what didn’t happen. Read More