I turn data and design into things people actually want to use, because good decisions should feel easy.

Marketing analytics master's student at UT Austin's McCombs School of Business, by way of Illinois.

consumer insights marketing analytics UX research product research product management

Selected work

Research, design, and the results they led to.

Conjoint analysisExcelPricing

Which coffee shop would people choose?

What it was: A conjoint analysis of what drives coffee shop choice: service type, price, food availability, and wait time.
What I did: Designed a survey of 18 hypothetical shop concepts, collected ratings from 14 respondents, and ran a regression-based conjoint in Excel. I then simulated market shares and price elasticity across competing concepts.
What changed: Price and wait time came out as the strongest drivers, which led me to recommend a fast-service concept.

Estimated market shares from the conjoint simulation: concept X 90%, concept Y 10%, Alpine 0%, shown as a table and pie chart

Simulated market share across three competing concepts.

UX researchUsability testingAI chatbot

An AI search bot for LinkedIn Learning

What it was: LinkedIn Learning has a huge library, and users struggle to find what they want. We asked how to make it easier to navigate.
What I did: Interviewed 9 students and job seekers, surveyed 10 more on low-fidelity screens, and ran a thematic analysis. I designed a chatbot for laptop and mobile, then tested it with think-aloud sessions.
What changed: 7 of 9 interviewees supported the chatbot, and testers found and opened it on their own in an average of 11.2 seconds. Testing led to lighter arrows, larger text, and newest messages placed at the bottom.

View prototype

LinkedIn Learning AI Search Bot conversation recommending beginner programming courses

PythonStreamlit

Tracking the Skyfall: meteorite landings

What it was: A data project exploring where and when meteorites have landed around the world.
What I did: Analyzed global landing data in Python to find patterns over time and across locations. I built the charts with Altair, Plotly, Seaborn, and Matplotlib.
What changed: Our findings became a Streamlit app with three interactive maps and charts you can filter by year, mass, and meteorite class, plus two charts that show the bigger picture.

Interactive world map of meteorite impacts, sized by mass and colored by whether the meteorite was seen falling or found later

More design projects

HealthyMe

A health app concept with an AI coach, camera meal logging, and wearable syncing, plus a freemium business model.

Social Circle

An app to help UIUC students find clubs and friends, designed from user interviews.

Skills

Tools

SQL
Python
R
Tableau
Power BI
Excel

Analytics

Regression analysis
A/B testing
Price elasticity
Market share simulation

Consumer insights

Survey design
Market research
Competitive analysis
Consumer preference analysis

UX research

Usability testing
Customer journey maps
Empathy maps
Wireframing
Prototyping

Just me

Off the clock, here's my player profile.

Main questMarketing analytics at UT Austin

Side questsHorseback riding, taekwondo, pilates

Go-to gamesZelda, Mario Kart, Overwatch

Power-upsMatcha, coffee, makeup, fashion, art

Fun fact: I taught myself to play violin.

$Photo of Celesta Irawan$

About

I grew up in Illinois and studied Information Sciences with a business minor at the University of Illinois Urbana-Champaign. I'm now finishing a master's in marketing analytics at UT Austin (May 2027).

I like the space where research meets design: finding out what people want, then making it simple to get. Past work includes consulting for a health data startup, analyzing data in Python, designing UI/UX, and building a no-code AI chatbot.

Say hello

ceirawan@hotmail.com