F&B Mobile Ordering
Warning: this case study may induce hunger.
I designed a 0-to-1 food & beverage ordering platform for hotels, the newest addition to Canary's suite of revenue products. Guests' late-night munchies were increasingly going to DoorDash instead of the front desk, so we rebuilt room service to be modern, convenient, and visually enticing. Four months to MVP, $23K in committed ARR five weeks after launch.
One hotel we spoke to ran breakfast on door hangers. Guests forgot to hang them, staff missed pickups, and complaints piled up. At most properties the alternative was the front desk phone: misheard orders, tied-up staff, and enough friction that guests simply gave up. Meanwhile, Canary was losing deals in APAC markets where mobile ordering is table stakes.
Canary's Guest Hub was still a static content product. F&B ordering would make it transactional: a revenue engine, not just an info layer. The discipline was scope: no marketplaces, no kitchen software. Just get a guest's order to staff efficiently.
- Year
- 2025–2026
- Role
- Sole designer
- Scope
- Guest ordering
- Menu CMS
- Staff dashboard
The Solution
We built a mobile-first ordering experience for our guests that served as an extension to our existing guest experience platform. Guests can browse available menu items, add to their carts, and then send their orders to hotel staff easily.
To manage inbound orders, we built a dashboard and notification system that enabled operators to easily notify their kitchen staff and complete fulfillment. There were four major decisions that defined the design:
- Built upon our existing infrastructure: fast implementation was important in order to go-to-market quickly. We designed mobile ordering as an extension to our existing guest experience and upselling platforms using similar patterns, but tweaked to match food & beverage use cases.
- Delivery type drives the experience: hotel customers wanted to go beyond in-room dining in order to expand channels for revenue. We had to design a flow that flexibly allowed for alternative locations such as orders delivered poolside, or to the hotel lounge.
- Five system objects as the IA backbone: Ordering Outlets, Menus, Items, Modifier Groups, Orders. Manage items once, compose menus flexibly.
- Works with or without a PMS: reservation-linked ordering when integrated, manual entry fallback for everyone else. No POS requirement meant shipping to the whole market.
How hotels build their menus: create an item once, then reuse it across any menu and ordering location.
Research & Discovery
Customer interviews with hotel F&B staff, competitive analysis, and usability testing on a fully interactive Next.js prototype I built, which went on to become the primary demo tool for sales calls and GTM enablement. The research drove three calls: no POS requirement (a POS dependency would have blocked 80%+ of potential customers), a staff dashboard sorted by time-elapsed urgency so orders never get missed during peak hours, and a no-download mobile web flow using patterns guests already know.
Customer interviews with hotel F&B staff, competitive analysis, and usability testing on a fully interactive Next.js prototype I built, which went on to become the primary demo tool for sales calls and GTM enablement. The research drove three calls: no POS requirement (a POS dependency would have blocked 80%+ of potential customers), a staff dashboard sorted by time-elapsed urgency so orders never get missed during peak hours, and a no-download mobile web flow using patterns guests already know.
Impact & Results
F&B Ordering hit GA in February 2026 with two verbal commitments from demos alone and 50 pilot orders validating demand before launch. The delivery-type model became the architectural pattern for all future ordering scenarios (spa, activities, table-side), and APAC enterprise interest is building, with $25K+ in potential ARR from interested properties.
F&B Ordering hit GA in February 2026 with two verbal commitments from demos alone and 50 pilot orders validating demand before launch. The delivery-type model became the architectural pattern for all future ordering scenarios (spa, activities, table-side), and APAC enterprise interest is building, with $25K+ in potential ARR from interested properties.
Reflection
- Prototype in code, early. Hotel staff testing realistic flows made research dramatically more effective, and the prototype became a genuine GTM asset.
- Find the one variable. The delivery-type insight collapsed dozens of edge cases into a single configurable model. Designing for two audiences (guests ordering, staff fulfilling) means designing the system, not the screens.
- I'd push harder on staff notifications in the MVP. Post-launch feedback from HOMA showed hotels needed immediate alerts, as their team had to keep checking for new orders.
- Prototype in code, early. Hotel staff testing realistic flows made research dramatically more effective, and the prototype became a genuine GTM asset.
- Find the one variable. The delivery-type insight collapsed dozens of edge cases into a single configurable model. Designing for two audiences (guests ordering, staff fulfilling) means designing the system, not the screens.
- I'd push harder on staff notifications in the MVP. Post-launch feedback from HOMA showed hotels needed immediate alerts, as their team had to keep checking for new orders.