Hi! I'm Torie, a Mixed Methods UX Researcher.

We're in an age of data overload. While more data theoretically sounds better, in practice it can cause all kinds of problems if not approached with a disciplined strategy. Data overwhelm can manifest in ways like uncertainty about how to interpret experimentation results, using invalid or inappropriate benchmarks, disconnect from users' problems, chronic strategy indecision, and more.

To provide research that helps companies and brands focus on what's important and avoid getting distracted by what's available, I use the the following core principles:

1. Do generative research early, ideally first. Validating (or correcting) core product assumptions early can drive alignment and investment in high-level company and brand strategy. Having detailed context about users' experience can expedite decision-making from everything from granular interaction and UI design to product market fit.

2. Be selective about your north star and goaling metrics. Decide what's important and how best to measure it before running the numbers. With big data sets, meaningless connections can appear "significant", and a deluge of data can overwhelm our decision-making capabilities.

3. Principled decisions > A/B testing. A strong point-of-view is sufficient for making many product decisions. It creates cohesion in the end-to-end user experience, and clarity about what to say "no" to.

A/B testing also passes the buck to your users by creating churn - save testing for when you really need it and spare yourself potential data overwhelm.

✍️ Get in touch at vnelson012@gmail.com.