Eat It

Eat It — a conceptual iOS application designed to simplify restaurant discovery, searching process and table reservations for city dwellers. Instead of juggling multiple platforms or making phone calls, users can search, compare, and reserve in one place.

Industry

Self-initiated concept · Mentorship

Scope of work

UI/UX Designer (solo project)

Duration

User research, user flows, wireframes, high-fidelity prototype, design system

Challanges

Booking a table today often feels unreliable. Users juggle Google searches, restaurant websites, and phone calls—yet still can't confirm if a table is actually available at their desired time. Phone reservations depend on business hours and staff availability, while online information is often outdated or incomplete.

This lack of a centralized, real-time booking system leads to errors, missed reservations, and user frustration. It also directly impacts restaurants through lost bookings, no-shows, and operational confusion during peak hours.

As a result, users experience:

  • Unclear or hidden availability

  • Time wasted switching between platforms

  • Inaccurate phone reservations

  • No single place for discovery and booking

Goals

The goal of this project was to design a mobile experience that simplifies the restaurant table booking process and fits naturally into users’ everyday behavior.

The app was intended to reduce friction during booking, supporting quick decision-making while still enabling exploration when users don’t have a specific place in mind. A strong focus was placed on mobile-first usage, taking into account short sessions, on-the-go interactions, and one-handed navigation.

Additionally, the project aimed to establish a scalable design foundation that could support future features and iterations as the product grows.

The goal of this project was to design a mobile experience that simplifies the restaurant table booking process and fits naturally into users’ everyday behavior.

The app was intended to reduce friction during booking, supporting quick decision-making while still enabling exploration when users don’t have a specific place in mind. A strong focus was placed on mobile-first usage, taking into account short sessions, on-the-go interactions, and one-handed navigation.

Additionally, the project aimed to establish a scalable design foundation that could support future features and iterations as the product grows.

Competitors

During research, I identified 9 key competitors by analyzing both direct and indirect market players.

It spanned dedicated reservation platforms like OpenTable, The Fork, and Expirenza, as well as delivery giants and discovery tools such as Glovo, Google Maps, and Tripadvisor.

During research, I identified 9 key competitors by analyzing both direct and indirect market players.

It spanned dedicated reservation platforms like OpenTable, The Fork, and Expirenza, as well as delivery giants and discovery tools such as Glovo, Google Maps, and Tripadvisor.

Strengths

  • mainly user-friendly, intuitive interface

  • features for convenient search, evaluation and booking

  • availability of loyalty systems and personalization

  • cooperation with other services

Weaknesses

  • cluttered interfaces with weak visual hierarchy

  • availability hidden behind multiple clicks

  • lack of breathing space ("air") in layouts

  • incomplete details — forces users to hunt for menus and photos on external sites or social media.

  • lack of spatial context — users book "blindly" without seeing the restaurant layout or table locations.

Analyzing similar applications allowed me to benchmark core features and integrate proven user patterns into the final design to ensure a competitive edge. Comparison table

User Research

Research Kit

To validate the problem and better understand user needs, I conducted:

  • Target audience analysis

  • 8 user interviews focused on booking behavior and pain points

  • Value Proposition Canvas to map user jobs, pains, and gains

  • 3 detailed personas representing primary user groups

Target Audience

Urban diners aged 18-40 who:

  • Book restaurants 2-4 times per month

  • Value convenience and speed over price

  • Are comfortable with mobile apps

  • Struggle with fragmented booking processes

  • Plan visits in advance or frequently discover new restaurants

Value Proposition Canvas

To clearly define the user problem space, I mapped a Value Proposition Canvas based on insights from interviews with 8 participants who regularly book tables at restaurants.

The goal was to understand key pains, jobs, and expectations around restaurant discovery and booking before moving into interface and feature decisions.

The identifies a lack of trust and control—particularly during phone bookings or group reservations—as the primary user challenge. Eat It addresses this by consolidating discovery and booking into a single mobile experience focused on confidence, clarity, and ease of use. Value Proposition Canvas

To clearly define the user problem space, I mapped a Value Proposition Canvas based on insights from interviews with 8 participants who regularly book tables at restaurants.

The goal was to understand key pains, jobs, and expectations around restaurant discovery and booking before moving into interface and feature decisions.

The identifies a lack of trust and control—particularly during phone bookings or group reservations—as the primary user challenge. Eat It addresses this by consolidating discovery and booking into a single mobile experience focused on confidence, clarity, and ease of use. Value Proposition Canvas

Design Solution

Navigation & Information Hierarchy

The app's navigation centers on the core user journey: discovering places, booking tables, and managing reservations.

A bottom navigation bar provides quick access to Home, Search, Bookings, and Profile—covering essential needs while maintaining context between exploration and booking.

Screen hierarchy minimizes depth, keeping key actions within one or two taps to reduce cognitive load for on-the-go usage. Complex tasks like table booking follow a linear, step-by-step flow, ensuring users always understand their progress without getting lost.

The app's navigation centers on the core user journey: discovering places, booking tables, and managing reservations.

A bottom navigation bar provides quick access to Home, Search, Bookings, and Profile—covering essential needs while maintaining context between exploration and booking.

Screen hierarchy minimizes depth, keeping key actions within one or two taps to reduce cognitive load for on-the-go usage. Complex tasks like table booking follow a linear, step-by-step flow, ensuring users always understand their progress without getting lost.

Personalized Discovery & Guided Choice

Many respondents requested to explore new places, so to optimize this process I have identified 4 progressive discovery layers:

  • Quick Category Filters — one-tap access to popular cuisines for users with specific cravings.

  • Must-Visit (personalized) — restaurants similar to previously liked or visited places, with popular picks as a fallback for new users.

  • Occasion-Based Suggestions — contextual collections for situational choices, such as romantic dinner, party, best terraces in Lviv, etc.

  • Expert Recommendations — сurated chef picks to build trust and encourage discovery beyond algorithmic results.

By applying progressive disclosure (from specific to social proof), the design streamlines the user journey, enabling informed decisions within 2–3 interactions while significantly reducing cognitive load.

Many respondents requested to explore new places, so to optimize this process I have identified 4 progressive discovery layers:

  • Quick Category Filters — one-tap access to popular cuisines for users with specific cravings.

  • Must-Visit (personalized) — restaurants similar to previously liked or visited places, with popular picks as a fallback for new users.

  • Occasion-Based Suggestions — contextual collections for situational choices, such as romantic dinner, party, best terraces in Lviv, etc.

  • Expert Recommendations — сurated chef picks to build trust and encourage discovery beyond algorithmic results.

By applying progressive disclosure (from specific to social proof), the design streamlines the user journey, enabling informed decisions within 2–3 interactions while significantly reducing cognitive load.

Many respondents requested to explore new places, so to optimize this process I have identified 4 progressive discovery layers:

  • Quick Category Filters — one-tap access to popular cuisines for users with specific cravings.

  • Must-Visit (personalized) — restaurants similar to previously liked or visited places, with popular picks as a fallback for new users.

  • Occasion-Based Suggestions — contextual collections for situational choices, such as romantic dinner, party, best terraces in Lviv, etc.

  • Expert Recommendations — сurated chef picks to build trust and encourage discovery beyond algorithmic results.

By applying progressive disclosure (from specific to social proof), the design streamlines the user journey, enabling informed decisions within 2–3 interactions while significantly reducing cognitive load.

Advanced Filtering & Search

To bridge the gap between generic search and specific user intent, I developed a multi-layered filtering system. I prioritized a location-first hierarchy to match user behavior and added quick-action chips for common needs ("Open Now" or "Nearby”), allowing users to bypass the filter menu and reach their choice faster.

The intent-driven "Vibe" system reflects research showing that social occasions often outweigh cuisine. Tags like Date Night or Work-friendly align with real-world goals, while a granular modal handles specific criteria like price, cuisine, and amenities (e.g., pet-friendly, accessibility).

Finally, I implemented an integrated Map View to provide spatial context. This allows users to explore via location pins and restaurant previews without leaving the map or losing filter settings.

Restaurant Cards & Restaurant Info

Restaurant cards display key decision factors at a glance: name, rating, location (distance/street), real-time status, price level, and favorites option.

A unified detail page consolidates all information to eliminate external searches and reduce booking drop-offs. The profile uses three tabs for depth without clutter: About (ratings, contact, reviews, peak-hours chart), Menu (categorized with ingredients), and Photos (professional + user content capturing authentic atmosphere).

A sticky "Book Table" CTA ensures frictionless conversion from browsing to booking.

Seamless 3-Step Booking Flow

The booking flow is condensed into three automated steps to minimize effort and abandonment, with all essential actions on one screen:

  • Step 1 - Core Essentials — fast selection of date, time, guest count, plus an "Invite Friends" feature for social engagement.

  • Step 2 - Spatial Selection — interactive seating map with real-time layout and quick-action chips for preferences (Window view, Quiet corner, Near bar, Outside).

  • Step 3 - Smart Summary — auto-filled profile data, guest avatars, and visual confirmation for one-tap completion.

For large companies, there is a modular table selection and guest invitation system that automates coordination.

Visual Style

The hedgehog mascot ("їжак" in Ukrainian) emerged from a playful wordplay on the app name: Eat It → sounds like "Eat Eat" → їж-їж (Ukrainian) → їжак (hedgehog). This clever link creates a strong mnemonic a memorable brand identity that stands out among generic booking apps.

The color palette centers on warm orange (food, energy, approachability), balanced by soft gray neutrals to reduce visual noise. Bright yellow and deep purple serve as accent colors for contrast and attention without overwhelming the interface.

Typography supports clarity and hierarchy: Craftwork Grotesk for headings (personality, confidence) and Fixel Display for body text and UI (readability, scannability), balancing expressiveness with everyday usability.

Create a free website with Framer, the website builder loved by startups, designers and agencies.