Channel Switcher

A new design for Twitch’s extensive catalog of creators

The number of live creators streaming to Twitch has grown exponentially over the last few years. Matching viewers with them has been my team’s core challenge.

We aimed to improve discoverability and stream sampling by allowing Twitch’s millions of viewers to more quickly explore its thousands of creators through more fluid, video-forward browsing.


Backed by prototyping, user research, and multiple phases of multivariate experiments I designed the Channel Switcher: an innovative interface for transitioning through a higher volume of live stream previews.

  1. Built and delivered Channel Switcher, increasing browsing conversion metrics. Viewers explored % more creators. New users used the most, retaining % more often.
  2. Ushered first redesign of browsing in years by synthesizing user needs, technical constraints, and business goals.
  3. Improved our prototyping process. Drafted a plan; my software engineering colleague then designed, implemented, and documented an AppSec-vetted process for hosting prototype builds on S3. (Thanks to Randal!)

Late 2021 – Present


Product Manager, support UX Designer, Researchers, Data Scientists, and a team of software engineers.


Figma, React, Typescript, GraphQL, RITE studies, multivariate testing, mixed methods.



Studied research about subject matter published by UXR; reviewed past experiments.

Analysis & Ideation

Made sense of our ongoing situation; came up with solutions based on reality; socialized ideas.


Roughed out wireframes, including a page-level carousel, a modal preview, and the persistent left nav.


Designed 3 broad directions with support from teammate Ed Scherf

Concept study

Conducted a concept study of the core ideas to validate and boil down the best direction.

Static Live Prototyping

Started with Figma, then built in with live data in React, Typescript, and our Core UI library with support of engineering team.

Rapid iteration study

Rapidly Iterated Testing & Evaluation (RITE) study with over 10 participants; refined the design as opportunities arose.

Live experiment

Directly supported engineering, shipped 2 multivariate tests, and contributed to data analyses.





1.0Starting with our customers

Our user feedback service overflowed with nearly 1,200 suggestions to improve discovery. Internal research also indicated gaps in our existing features. As the team’s viewer domain expert, I knew we had a massive chasm between what our viewers were looking for and what our discovery features offered.

I had spent the previous couple of years focused on several improvements of the watching experience; it was my turn to help viewers in getting there.

When I
I want to
so I can

This structure of user stories was liberally borrowed from this Jobs-to-Be-Done (JTBD) method.

Analyzing results from past experiments and research revealed insights that informed our direction. I synthesized the research into key insights:

Limited Access

Sharing is caring and all

While I love sharing my process — I’ve learned just about all I know from others who do so — the nature of this project requires that it be limited to certain audiences.