Global Search - MasterClass
Redesigning MasterClass Search to improve clarity, relevance, and cross-platform consistency—strengthening discovery across Web, iOS, and Android.
Making Search Searchable
At MasterClass, I led the end-to-end redesign of our Search experience across Web, iOS, and Android. This project followed the launch of the Library redesign I also led, and became the next strategic step in strengthening content discovery across the platform. We knew that users began their journey with Search, but lacked clarity about content types and relevance, leading to this redesign.
As the lead designer on this project, my goal was to reimagine Search as a clear, intuitive, and expressive entry point to help users effectively browse and find the content they’re looking for. I collaborated closely with Product, Engineering, Data Science, UX Research, and Design Systems to define the vision, build scalable patterns, and deliver a cohesive cross-platform experience.
Goals
Make Search easier to find by placing it in the global nav
Improve comprehension of content types and relevance
Increase Search usage and downstream engagement & build scalable UI patterns for Web, iOS, and Android, and strengthen cross-platform cohesion and metadata clarity
Hypotheses
If we improved how Search is found, understood, and explored, users would have greater confidence in finding relevant content on MasterClass and consume more content that matched their intent.
Process
I first wrote a design brief outlining the problem space, data signals, constraints, risks, and milestones, which paired with my PM’s PRD as our alignment document. This allowed us to set clear expectations early and make principled tradeoffs later.
Throughout the project, I met with Engineering, Product, Data, Leadership, and Design Systems to pressure-test decisions, ensure technical viability, and define how Search needed to scale.
I also partnered with UX Research to develop test plans, build prototypes, and run iterative evaluations. Insights from these sessions shaped everything from information architecture to metadata representation.
Search V1
As the project continued, to test and learn iteratively to build towards a larger North Star re-design, we structured this project into V1 and V2 to accelerate delivery while exploring bigger changes in parallel.
For our V1 release, I led and completed designs across Web, iOS, and Android. Search V1 launched in Q1 2023 and saw significant lifts in Search usage and engagement.
Search V2
For Web in our V2, we consolidated results into a single “All” view with content-type tabs. Each content type received its own display pattern, designed for recognition and clarity. A standout element was the “Best Match” tile, a hero result for exact instructor matches, designed to surface confidence signals quickly and celebrate the rich photography within the MasterClass catalog.
On Mobile (iOS / Android), we introduced a tabbed model for content-type differentiation to allow users to find relevant content quickly. As well as a few differentiated pattern elements: Large immersive tiles to highlight classes and compact tiles represented shorter content (e.g., lessons).
In our V2 designs, we wanted to further explore content display to encourage better wayfinding through content, and encourage relevant content browsing to help users find related content. To this end, in this stage of the project, I explored more substantial UX and IA improvements.
Final Designs
For our final designs, I delivered web, iOS, and Android use case flows and high-fidelity prototypes across platforms.
Search V1 launched to all users and drove lifts in content discovery and Search engagement. While search V2 shipped as an A/B test, it introduced scalable patterns and informed an updated global navigation system. Redesigning Search redefined how MasterClass’s catalog was explored and understood, improving clarity, confidence, and consumption across platforms for both consumer and enterprise users.
Finally, this redesign also resulted in cross-platform consistency and new scalable patterns that informed future catalog and navigation features.