I build research systems that turn consumer and behavioral data into decisions teams can actually act on. Four years of doing that across telehealth, fashion, higher education, and a family business.
I'm a Marketing and Business Analytics graduate from the University of San Diego. For four years I've worked on the same problem in different rooms: how do you take messy consumer data and turn it into something a team can actually decide on? I've done that for a telehealth platform with 4M+ members, a fashion client at a growth agency, a university career center, and my parents' small business.
Growing up in rural North Idaho as the daughter of Vietnamese immigrants who built their nail salon from nothing, I watched them earn trust with every customer, often without a shared language. That's where I learned business is really about understanding what people value. It's still the thing I'm best at.
What I'm after is the why. Why people choose, stay, leave, or fall for a brand. That question sits underneath every model I've built and every deck I've presented.
I joined BetterHelp as their first consumer insights analyst intern, sitting across Growth, Performance, Brand, Paid Social, and International. I spent the summer on one question: how do you turn research into something teams can actually use? I worked on it at two scales, market and organizational, and shipped three systems.
I presented this to the BetterHelp marketing organization in August 2026. It walks through the summer's work in depth: the research approach, the systems I built, and how each one gets used. Figures, market names, and identifying details have been modified to protect proprietary information.
Entering a new international market meant learning an unfamiliar consumer, competitive set, culture, and media environment fast. I built a self-updating repository that turns scattered evidence into decisions marketers can act on. It became the template for future country launches.
BetterHelp's marketing knowledge lived across people, decks, dashboards, Confluence, briefs, and Slack. I built the context layer behind Motion's AI creative workspace so future work starts from what the company already knows.
BetterHelp's nationwide insurance launch produced a lot of unstructured Looker data. I built the consumer research framework that made it usable, layering coverage status, insurance literacy, and decision friction across 51 markets.
"I loved having Zadie on my team at USD. She has a natural knack for marketing, social media and analytics, but what really sets her apart is her initiative; she doesn't just do the work, she looks for ways to make it better. She was a joy to supervise and a wonderful presence in our office. "
Coursework and competition projects in statistical modeling, segmentation, and consumer research. These are where I learned the methods I use professionally. Click any card for the full deck.
I built logistic regression models in JASP to isolate what actually drives web traffic from TV advertising. Comparing full and reduced models separated how much lift came from the creative itself versus where it ran.
Built a predictive churn model segmented by contract type and demographics. I modeled CLV and retention incentive scenarios to estimate profitability impact, balancing retention cost against how precisely we could target.
Hierarchical clustering on Spanish consumer data, validated with elbow and BIC, confirmed distinct with ANOVA. Three segments, each turned into a persona and a messaging angle for market entry.
I ran this one end to end, from raw messy data to strategic recommendation. Cleaning and transforming in R and SQL, then 22+ visualizations including heatmaps and decision trees to surface the behavioral patterns that actually move purchasing likelihood.
Skims moved into menswear and wasn't landing. We ran a focus group, then surveyed 108 men. Word associations came back sexy, underwear, Kim K, women. Celebrity endorsement barely beat everyday men, which cut against how the brand was spending.
GrabBike works in Southeast Asia. I looked at whether it translates to Brazil and what has to change if it does, then built the positioning and localization strategy around that.
Analytics and humanity belong in the same room. I want to build work that is analytically strong, culturally aware, and actually useful to the person who has to make the call. Not dashboards that report what already happened, but insight that changes what someone decides to do next.
I'm looking for full-time marketing analytics, consumer insights, and growth roles. Always happy to talk about segmentation, subscription data, creative strategy, audio and creator platforms, or any project where the numbers get to feel a little more human.
Roles where data, culture, and creativity get to live together. Teams that take consumer understanding seriously and let insight drive strategy all the way through. Open to the Bay Area, NYC, or remote.