Eli Bonilla
Back to workCASE · ROBUSTA
Roasted coffee beans under a wireframe analysis overlay with technical callouts.
P-02 · ROBUSTA

Robusta Coffee House

Specialty coffee identity, packaging, and mobile ordering system.

Category
Brand · Packaging
Year
2022
§ S-01

Phase 01: Product context

SYSTEM_STATE: Ecosystem Unification

The project required translating a specialty-coffee brand into a coherent consumer product experience spanning discovery, customization, ordering, and fulfillment.

Consumers required a unified digital ecosystem to discover products, customize drinks, understand ingredients, place orders, and track fulfillment with a clearer, more streamlined interaction flow.

The objective was to architect a comprehensive system that translated the physical precision of the product and the operational constraints of the physical store into a coherent digital workflow.

§ S-02

Phase 02: User needs & discovery

DIAGNOSTIC: Qualitative Insights & Competitive Review

To define the system architecture, research was conducted to map user behaviors, preferences, and operational constraints within the existing market.

  • FINDING 01

    Parameter Control & Situational Awareness

    User research identified strong demand for granular drink customization and clear post-order visibility.

  • FINDING 02

    Fulfillment Asynchrony

    Analysis exposed a critical desynchronization between digital order ingestion, physical kitchen throughput, and user transit velocity (e.g., generic ETA windows ignoring user distance).

  • FINDING 03

    Competitive Review

    Competitive review exposed opportunities around personalization, integrated coffee tools, and customization depth without relying on nested menus.

§ S-03

Phase 03: Product architecture

ROUTING: Structured Task Flows & Information Hierarchy

To support multiple customization parameters without making the transaction flow cumbersome, the information architecture was structured hierarchically.

Core Transaction Pathway
  1. 01
    Authentication
  2. 02
    Category Selection
  3. 03
    Product Detail
  4. 04
    Parameter Customization
  5. 05
    Cart Aggregation
  6. 06
    Checkout / Payment
  7. 07
    Order Tracking
Systemic Fulfillment Logic
  1. 01
    User Travel Time + Store Prep Time
  2. 02
    System Decision (Hold/Brew)
  3. 03
    Arrival-Aware UI Status

Navigation Matrix: The architecture utilized a bottom-tab navigation system (Home, Rewards, Cart, Profile) to anchor the user, ensuring immediate access to loyalty status and order history without breaking the primary transaction flow.

§ S-04

Phase 04: Product experience

INTERACTION LOGIC: Parameter Control & Product States

The application translated the brand system into the core ordering and customization experience, prioritizing the relationship between digital input and physical operations.

GOOD MORNING

Maya.

QUICK ORDER
LAST ORDER

Oat Flat White

Large · 2 shots · Extra hot

Screen index03 / 13 · Home
Screen
Home
Product
:
Cart
0 items
History
0 deep

Thirteen screens, one component system. Size, milk, temperature and shot count set on Customize propagate through Cart, Payment and Tracking the totals are computed, not drawn. Every tap target is a real button: Tab through the frame, arrow keys move the index.

MODEL 01Travel syncing

Fulfillment timing compares user travel estimates against live queue conditions to determine when an order should hold, proceed, or accelerate.

INPUT

Travel ETA

transit velocity · route distance

Live queue state

open tickets · station throughput

PROCESS

Hold / brew decision

traffic buffer · hurry up override

OUTPUT

Arrival-aware status

held · brewing · ready on arrival

MODEL 02Arrival triggers

Fulfillment logic compares transit telemetry against queue times to trigger delayed holds for optimal product freshness.

INPUT

Macro-fence

3 minutes out · pre-stage ticket

Micro-fence

10 feet out · pickup proximity

PROCESS

Beverage physics

crema decay · foam stability · dilution

OUTPUT

Preparation trigger

release to station · notify user

MODEL 03Data parsing

Customization inputs are parsed into structured order data that feeds both the barista ticket and customer-facing nutrition interface.

INPUT

Customization input

modifiers · volumes · ratios

PROCESS

Recipe-to-matrix parser

baseline recipe matrix → resolved build

OUTPUT

KDS output

build steps only · zero-clutter ticket

Customer HUD

stage indicator · nutrition readout · ETA

§ S-05

Phase 05: Visual & component logic

INTERFACE DESIGN: Token Constraints & Visual Execution

The brand and interface were built on a highly constrained token set, with every surface, accent, and type role assigned a single deterministic function.

Substrate · charcoal#181A1B
Substrate (Charcoal - #181A1B): The default background, anchoring the system and allowing product imagery to advance in the visual hierarchy.
Surface · cream#FFF7EF
Surface (Cream - #FFF7EF): Reserved for primary typography and key physical artifacts (packaging).
Highlight · warm white#FDEED9
Highlight (Warm White - #FDEED9): Deployed as a secondary surface for tertiary UI components.
Accent · tan#A88157
Accent (Tan - #A88157): The primary interactive token, governing active states, primary CTAs, borders, and active loyalty indicators.
Display · serif

Aa Bb Cc 01

Text · sans

Aa Bb Cc 01

Typography: Engineered for distinct operational hierarchy, utilizing a high-contrast serif for display/wordmarks and a neutral geometric sans-serif for high-legibility interface data and button labels.

Robusta brand sheet: logo lockups, typography, palette, and packaging substrates.
FIG. R-01Consolidated brand sheet: mark system, palette, and substrate application.
§ S-06

Phase 06: Diagnostic retrospective

EVALUATION: System Vulnerabilities & Iteration

Treating the brand mark as a reusable component supported scalability across digital and physical substrates. However, relying on a single accent token (Tan) for all interactive weight across the application introduces potential edge-case ambiguity.

In future iterations, reserving a secondary semantic token strictly scoped to warning and error states would remove this ambiguity without diluting the stark, minimalist brand logic.

§ S-07

Phase 07: Ownership & outcomes

EXECUTION: PRODUCT & INTERACTION ARCHITECTURE

Consumer Product Architecture
Designed the mobile ordering experience across discovery, customization, checkout, tracking, and fulfillment.
Computational Product Logic
Designed the interaction logic for parameterized customization, nutritional calculation, and arrival-aware order timing.
Physical-Digital Fulfillment Model
Mapped user travel, preparation timing, ticket queues, geofencing triggers, and fulfillment states into a unified product model.
System Prototyping & Specification
Developed the interactive prototype and supporting system models that connected consumer-facing interactions with modeled physical operations.
Outcome
Unified customization, arrival-aware fulfillment, and physical preparation constraints into a coherent consumer product system.