Case study · 2025
Zia Pizza
The heart of your local pizzeria, at your fingertips.
Zia Pizza is a mobile ordering app for a local pizzeria — built around speed, customization, and trust. The product lets customers browse the menu, build their own pie, track an order in real time, and earn rewards for coming back. The design challenge was to make a takeout interaction feel as warm and human as walking into the shop itself.
The problem
People want a quick slice — not a phone call and a guess at when food will arrive.
User research surfaced a consistent pattern: customers want a faster, more reliable way to order their pizzas without phone calls, long waits, or confusing menus. Participants put convenience first — they expect a smooth ordering flow, easy customization, and accurate delivery or pickup times. Many also expressed frustration with not knowing the status of their order, and wanted real-time tracking to feel in control.
Loyalty rewards and personalized deals were strong motivators, especially for frequent customers who want recognition for their repeat business. Overall, users were looking for an app that simplifies ordering, highlights Zia's signature quality and freshness, and provides a seamless end-to-end experience from selection to the moment the pizza arrives.
Slow or confusing ordering
Existing flows buried the simple things — choosing a size, customizing toppings, paying — under unclear menus and dead ends.
No real-time order status
Once an order was placed, customers were left guessing. The lack of feedback bred anxiety and re-orders by phone.
Payment friction
Re-entering address and card info every order was a recurring drag — and a frequent reason carts were abandoned at checkout.
The user
Meet Alex Martinez.
A composite persona built from research — Alex represents the busy, convenience-oriented customer whose Friday-night order Zia needs to win.
Goals
- Order pizza quickly, with minimal steps.
- Save favorite items for fast reordering.
- Know exactly when the pizza will be ready or delivered.
- Get notified about deals or rewards.
Frustrations
- Not knowing order status after checkout.
- Confusing or slow checkout flows.
- Inaccurate wait times.
- Having to re-enter address and payment info every order.
- Missing out on deals and loyalty rewards.
Does this make the order faster — or does it just add a screen?
The question we asked of every screen in the flow
The process · 01
Started on paper.
Before opening Figma, I sketched the screens by hand to keep the focus on flow and layout rather than pixel-perfect polish. Each frame was a quick exploration of how to structure the home, menu, and build-your-own pages — testing where the cart, search, and primary CTA should live before committing to any visual direction.
The process · 02
Low-fidelity prototype.
With the rough layouts validated on paper, I moved into a low-fidelity prototype to test the full end-to-end ordering experience. Every core flow got its own screen: browse, choose, customize, check out, and confirm. By laying out the whole journey in lo-fi before any polish, I could push back on screens that didn't earn their place.
The process · 03
All flows, side by side.
Laid out together, the screens tell the full story: from Home browse and Menu, through Build-Your-Own and Check Out, to Delivery Confirmation, Navigation, About, and Saved orders. Seeing them as a set made the visual rhythm — the recurring header, the consistent CTA color, the same gestures across screens — a deliberate decision rather than a happy accident.
Reflection
What worked, what I'd do differently.
What worked
Anchoring every design decision to one of the three research pain points — slow ordering, no status, payment friction — kept the project from sprawling. The Build-Your-Own flow in particular survived several rounds of feedback because we could keep asking "does this make the order faster, or does it just add a screen?"
What I'd revisit
The persona was useful as a north star but stayed light on emotional context — when Alex is hungry, distracted, on the couch with friends. A second round of contextual interviews would have sharpened the notification model and the priority of dashboard elements like "reorder last pizza," which still feels under-promoted in the final flow.