About Archive Access

The Archive Access option lets you watch the recorded classes from the last time Indi recorded the course. Typically, this will be the class recordings from the previous year.

Archive Access provides a way for you to experience Indi’s course content on your own schedule, without waiting for the next Live class offering.

About this course

Summary

Research teams tend to hurry through data analysis, which bends the insights toward their own perspective. In this course, you will learn bias-free analysis of transcripts.

Research “insights” are the junk food of product teams.

Most research teams are working within complex contexts, and the people they study are complicated. They do their research in focused chunks to shed light on discrete parts of the situation. But many teams are told, “Give me a couple of good insights.” They’re asked, “What are the highlights?” “Trends?” “Pain points.” Teams end up sharing out answers to those questions rather than letting the data tell the real stories.

Research teams respond by providing a “summary” format of what they found–and literally this set of insights consists of a list of things they heard frequently. When creating this list, it takes a well-trained mind not to fall prey to cognitive bias. When you come at data from a top-down approach, the concepts that you’ve already become interested in get emphasized in what you remember from the data. Bottom-up analysis is the best way to avoid cognitive bias and let the data tell you what it really means. Very few research teams actually conduct bottom-up analysis.

(Here is an example of concepts & summaries from the first part of one transcript, about the purpose of going to a restaurant, or not, during the COVID19 pandemic.)

Learn true, unbiased, bottom-up analysis technique.

If you want to bring rock-solid, reliable information to your organization, you need to know how. This kind of deep analysis is not taught as a part of most user experience coursework. It requires keeping a neutral mindset and looking at the transcripts for types of concepts, not concept meaning. The meaning will bias you toward the things you are already interested in. Types of concepts, however, enables a bit of neutrality. Once you pull those types out and summarize them, you will have a true set of concepts that were actually expressed

You will learn how to:

• Develop cognitive empathy with each participant by thoroughly understanding their transcript
• Set yourself up for easier synthesis of patterns
• Recognize surface from depth
• Pull quotes across a transcript to form a single concept
• Summarize each concept so it makes later comprehension faster
• Prepare data for creating thinking styles and mental model diagrams
• Also use this approach for transcripts from user research