End-to-end case study

Theatre Tracker – designing for ever-changing live performance data

A UX case study on helping theatre lovers make sense of constantly shifting showtimes, venues, and availability — and giving them a more reliable way to decide what to see next.

Role: End-to-end UX · research, IA, interaction design
Timeline: Academic project, multi-week sprint
Skills: Generative research, synthesis, prototyping, usability testing

Context & problem

In most cities, theatre information is fragmented across ticketing platforms, venue websites, and social media. Showtimes change, runs get extended, and last-minute seats open up — but people who love theatre still rely on word of mouth, screenshots, and browser tabs to keep track of what's happening.

The goal of Theatre Tracker was to explore how a digital product could make this messy, ephemeral information feel stable enough to plan around, while still reflecting the reality that things change all the time.

Research & key insights

I started with qualitative research: short interviews with frequent theatre-goers and desk research on how people currently discover and track shows. I also mapped the ecosystem of existing tools — from official ticketing platforms to informal spreadsheets shared between friends.

Discovery and decision-making are separate moments. People casually discover shows all the time, but commit to buying tickets much later.
"Did I miss it?" is a constant anxiety. Users were often unsure whether a show was still running or had already closed.
Everyone had a personal tracking system. Notes apps, Instagram saves, and shared docs were all doing quiet work behind the scenes.

Framing the opportunity

Instead of trying to be another ticketing platform, I framed Theatre Tracker as a layer on top of existing systems — a place to capture, organize, and act on theatre intentions over time.

This led to a core design question: how might we design for imperfect, ever-changing data in a way that still feels trustworthy?

Information architecture & flows

I mapped two primary flows: discovering a new show and deciding what to see this week. The IA intentionally keeps the system shallow — three main sections:

Inbox: shows you save from anywhere, waiting to be sorted.
Shortlist: upcoming shows you're actively considering.
Archive: past shows you've seen or decided against.

Key design decisions

Make uncertainty explicit

Instead of hiding imperfect data, the UI shows status labels like "dates tentative" or "run extended" so users understand what's known and what might change.

Separate "save" from "plan"

Saving a show is lightweight and reversible; moving something into the shortlist is a more intentional step, with clearer metadata about dates, location, and price.

Design around weeks, not days

People often plan theatre by week ("sometime next weekend"), so the schedule view groups options by week and time of day instead of asking for exact dates up front.

Outcomes & what I learned

I tested the prototype with a small group of theatre-goers and asked them to complete tasks like "decide what to see next weekend" and "check if a show you saved is still running."

Participants described the experience as "less stressful" and "more organized" than their current mix of tabs and notes.
Tasks that involved checking whether a show was still running were noticeably faster when uncertainty labels were present.
The "shortlist" concept helped people narrow down options without committing, which they said matched how they actually plan.

This project reinforced the value of making the UX process explicit — showing how research, insights, and constraints shape concrete design decisions, even in a speculative or academic context.