Qualitative data is narrative and descriptive data that gives you personal, yet subjective insight into your customers.
It helps you understand the why behind users behavior.
UX research methods:
Open ended survey questions
Focus groups etc.
In - app feedback
helps you identify new opportunities e.g user interviews
helps you assess/evaluate an existing feature or anexisting problem e.g. usability testing.
Customer Driven Data
Mostly "unsolicited" customer feedback e.g support tickets.
How do employees work on the go and what key capabilities are necessary to keep them productive
What does a day of work look like for you?
Do you conduct work on your phone? When?
What kinds of tasks do you complete on the go?
How successful are you at completing said tasks?
If you could only do one work task on your phone, what would it be?
What do you think when you look at this page
What are your initial impressions of this page
What do you think you can do on this page?
What do you think would happen if you click on this button.
Ideally transcribe interviews
Group insights and answers into themes
Keep grouping to you have key takeaways
Note both success and failure
Word and action mismatches
Common mistakes as well as outliers
Its power is really in helping you understand what to do, especially when you use it in combination with quantitative data, because it takes a lot of resources to create something new. It actually takes a lot of resources to build something that already exists. Take this time to understand the space in the client, know who you are targeting, and understand their behavior patterns. This gives you the ability to make informed decisions and deliver what people want.
To provide additional context for quantitative data findings.
To identify a new product area or direction.
To validate or invalidate feature ideas.
To understand how/if an existing feature addresses a user goal.
Don`t try to quantify qualitative data
Make your product directive insights not human directive insights
Underrepresented backgrounds get most affected by this.
If differs from your regular pool. It shows you need more insight.
Qual is subjective so not great for preference testing.
Try to get a diverse pool of users.
Don`t make population level generalizations.
Qualitative data gives you insight into the why of customer behavior.
Generative, evaluative, customer driven.
User interviews and usability testing are two key research methods for data collection. For both preparation is key to data accuracy!
Qual data goes hand in hand with quantitative data.
Don`t try to quantify your results and always focus on product insights not human insights.
Temi Moju-Igbene, Redfin Product Leader