The 80/20 of UX research: What qualitative data to use and when
We'll talk about the one qualitative process that you should use 80% of the time. Learn how to translate your customer research into meaningful numbers that you can make product decisions on.
How many customers do you have to talk to find 85% of the usability problems? How do you avoid the most common pitfalls that result in bad data? We'll go through that as well as the best practices you can use to confidentially calculate the extent of the problems you've found.
You'll walk out of the conference room with UX skills that you can put into practice right away and a gift bag to boot.
Outline/Structure of the Talk
It can be satisfying to only rely on quantitative data, it’s less messy than dealing with humans and what they really mean. Even when you do want to start doing usability research, where do you start and what practice do you use?
This talk will cover the 20% of UX skills that you can use 80% of the time. We’ll cover the most effective ways you can test your assumptions with people, what process you should use for each product decision and how to avoid the most common pitfalls. We’ll also talk about what’s the minimum UX research you have to reach a confidence interval.
This includes an exercise that will improve your research skills drastically.
Learning Outcome
You'll walk out of the conference room with UX skills that you can put into practice right away.
Target Audience
People who make, or help make, product decisions
Prerequisites for Attendees
None
Video
Links
schedule Submitted 5 years ago
Call for Proposals CLOSED
Ended on Mar 24 '18 12:00 AM AEDT
Share Your Data Intensive Experience!
YOW! Data is a two day technical conference for data professionals to share their challenges, best practices, techniques and tools. It provides data architects, engineers, scientists; database; visualisation and machine learning specialists to learn and discuss issues in designing, building, managing data systems and applications.
Lessons learned and specific practices are very important for this pragmatic conference. Hence we encourage submissions which deal with the practical challenges of working data to extract meaningful information for decision makers. Topics include case studies in data engineering, analytics, visualisation, architecture; machine learning; fast streaming data; working with structured and unstructured data; data intensive applications and new approaches to to problems in a data driven business. Please see the submission guidelines before submitting your proposal.
Dave Thomas
Josh Graham
Grant Carlson
Brian Thorne
James Binh Tham
