Dec 05, 2025·8 min
Build a Restaurant Web App for Reservations, Orders & Tables
Step-by-step plan to create a restaurant web app for reservations, online orders, and table turnover, covering MVP scope, UX, integrations, and launch.
Step-by-step plan to create a restaurant web app for reservations, online orders, and table turnover, covering MVP scope, UX, integrations, and launch.
Before you pick features or screens, decide what the app is truly meant to improve. Restaurant software fails most often when it tries to “do everything,” but doesn’t measurably help the team on a busy Friday night.
Write down the primary outcome in plain words. Examples:
A good rule: if you can’t explain the goal in one sentence, you’re still describing a wish list.
Restaurant apps have multiple “customers,” each with different needs:
Design decisions get easier when you know whose problem you’re solving in each flow.
List workflows from start to finish, not just “features.” For example:
When you map these, include edge cases you see every week: late parties, table merges, item 86’d, split payments, and comps.
Pick a small set of numbers that prove the app is working to reduce friction and increase revenue:
These metrics will guide what you build first and what you improve after launch.
Before you design screens or pick tools, decide what your app will do on day one. Restaurants don’t need “everything”—they need the few workflows that remove the most friction for guests and staff.
A usable reservation module isn’t just a booking form. At minimum, include:
Also decide early whether you support special requests (high chair, patio, allergy note) and deposit/no-show policies. These choices affect both the guest UI and the staff workflow.
Online ordering succeeds when the menu is easy to browse and the cart is hard to break.
Key capabilities to prioritize:
If you plan QR code ordering, treat it as the same flow with a different entry point.
Table management is where reservations and walk-ins meet reality. Your first version should cover:
Give managers control over the basics:
This feature set keeps scope focused while still supporting real service.
An MVP is not “a smaller version of everything.” It’s the smallest release that reliably handles your core restaurant operations without creating more work for staff.
For most restaurants, a strong MVP focuses on a few repeatable paths:
If your goal is table turnover, prioritize reservation + table status first. If revenue from takeout is the priority, choose ordering + payment first.
If you want to move faster than a traditional dev cycle, consider building the MVP on a vibe-coding platform like Koder.ai. You can describe the flows in chat, iterate on UI quickly, and generate a React-based app with a Go + PostgreSQL backend—then export the source code when you’re ready to take full control.
Write down what you will not build in the first release. Common exclusions that save months:
You can still design your data model to allow these later—just don’t build the UI and rules now.
A realistic range for a first version depends on integrations and complexity:
Budget typically follows the same curve: more systems to connect and more edge cases to handle means higher cost. Lock the scope before you lock the number.
Keep a running “later” list, but only commit to the next release after you see real usage patterns.
A restaurant web app succeeds or fails at the guest’s first two moments: booking a table and placing an order. The goal is simple—make these steps feel obvious, fast, and trustworthy on a phone.
Keep the reservation form focused on what the host actually needs. Start with party size and date/time, then show only the relevant time slots (not an open-ended “pick any time” input). Add fields for name, phone/email, and an optional special requests box (allergies, high chair, accessibility needs).
Reduce friction with small details:
tel and email inputs)Mobile-first layout matters: one column, large tap targets, and a sticky “Reserve” button that’s always reachable.
Whether guests order ahead or via QR code ordering, design the flow around confidence.
Show item photos sparingly, but always show price, key modifiers, and timing cues (e.g., “Ready in ~25–35 min” for pickup). Make the cart easy to edit, and avoid surprise fees—display taxes, tips, and service charges before checkout.
If you support dietary notes, keep it structured where possible (checkboxes for “no nuts,” “gluten-free bun”) and reserve free-text notes for edge cases.
Guests should be able to reschedule or cancel from the confirmation page without calling. Explain policies plainly: deposit, late arrival grace period, cancellation window, and no-show fees. Don’t hide these in fine print—place them near the final confirmation button.
Use readable type, strong contrast, and labels that screen readers can understand. Ensure every step works with keyboard navigation, and don’t rely on color alone to indicate errors or availability. These basics reduce drop-offs and increase completed reservations and orders.
A restaurant app only works if the team can run service without fighting the screen. The staff dashboard should feel like three focused tools—host, kitchen, and manager—built on the same data, but tailored to different decisions and time pressure.
The host needs a “live book” that answers: who’s arriving, who’s waiting, and which table can take them now.
Key elements:
Design tip: minimize typing during peak hours—use large buttons, defaults, and a fast search for name/phone.
For the kitchen, clarity beats feature depth. Show incoming orders in the right sequence and make it easy to update prep status without losing track.
Include:
The goal is fewer verbal interruptions: the screen should communicate what’s next and what’s blocked.
Managers need tools to protect the experience and revenue when reality deviates from the plan.
Provide:
Make permissions explicit: hosts don’t need payment controls, and kitchen staff shouldn’t see customer contact details unless required. Role-based access reduces mistakes and keeps the dashboard fast, focused, and safer by default.
A restaurant web app feels “smart” when it mirrors the real floor: how tables are arranged, how parties move, and where bottlenecks form. Start by modeling the dining room in a way that’s easy to maintain, not just accurate on day one.
Create a floor model with sections (Patio, Bar, Main), and tables that have attributes like table number, seat count, accessibility notes, and proximity tags (near window, quiet corner). If you support combining/splitting, treat that as a first-class concept:
This prevents accidental double-booking when staff are busy.
Use a small, consistent set of states that staff can change in one tap:
available → reserved → seated → ordered → dessert → paid → cleaning → available
Each transition should capture timestamps. Those timestamps power useful features like “time seated” and “average meal duration,” without asking staff to do extra work.
Turnover is a prediction problem. Start simple: estimate duration by party size + service style, then adjust using recent history (weekday vs weekend, lunch vs dinner). Highlight tables at risk when:
Surface this as a subtle warning on the staff dashboard, not an alarm.
For walk-ins, capture party size, preferences (booth, high-top), and a quoted wait. When the estimate changes, send optional SMS/email notifications (“Table ready” and “Running 10 minutes behind”). Keep messaging templates short, and always allow staff to override quotes based on judgment.
A good reservation engine does more than show open times—it enforces the same logic your host uses in real life. Clear availability rules prevent overbooking, reduce no-shows, and keep the kitchen from getting slammed.
Start by defining what “capacity” means for your restaurant. Some teams model it by tables only; others add pacing controls so the room fills gradually.
Common inputs include:
When a guest requests a time, the engine should check both table fit and pacing capacity before offering slots.
Availability needs strong conflict protection, especially under high traffic.
Use a two-step approach:
If two users select the same table/time window, the system must resolve it deterministically: the first confirmed reservation wins, and the other user is prompted to pick another time.
Add practical boundaries:
These settings should be editable without code changes.
Real restaurants run exceptions constantly. Support:
Store exceptions as dated overrides so your default rules stay clean and predictable.
Online ordering is where a restaurant web app either reduces chaos—or creates it. The goal is simple: guests place accurate orders quickly, staff can fulfill them predictably, and payments reconcile cleanly.
Your online ordering system should mirror how the kitchen thinks, not just how the menu looks. Model the menu as categories → items → modifiers, and treat key details as data, not text: allergens, dietary tags, and portion/size options.
Include operational toggles that staff can change without developer help:
Peak times are where ordering breaks. Add guardrails that align with prep capacity:
For dine-in, connect throttling to table management: if the kitchen is overloaded, QR code ordering can still work—but the app should communicate longer lead times clearly.
Most restaurant operations software needs at least two flows, often three:
Each type should generate a clear ticket for the restaurant dashboard and, if applicable, for restaurant POS integration.
Payment features should follow what your payment provider supports:
Decide early whether dine-in uses pay-at-table, pay-at-counter, or a hybrid. Clear rules here prevent mismatched totals and reconciliation headaches in reservation and ordering reports.
Integrations are where a restaurant web app stops being “another tool” and becomes part of daily service. The goal is simple: reduce double entry, keep guests informed, and give staff timely signals without adding new screens to watch.
Your POS is often the system of record for sales, menus, taxes, and receipts. You typically have three options:
Plan for a graceful “POS down” mode: queue orders, allow manual acceptance, and reconcile later.
Reservations and orders need clear, timely messages:
Keep templates editable and log every send (success/failure) for support.
If you offer delivery, validate addresses at checkout to reduce failed deliveries and refund requests. Even for pickup, map links in confirmation messages can lower “where are you?” calls.
Track where people drop off (reservation form, payment step), plus operational signals like no-show rate, prep time, and peak-hour load. Centralized logs and basic dashboards help you spot issues before staff complains. For deeper planning, connect metrics to your /blog/testing-launch-and-improvement playbook.
A restaurant web app succeeds when it’s easy to run day-to-day, fast at peak hours, and simple to extend. You don’t need an exotic stack—choose proven tools with a clear path to real-time updates and integrations.
If your team prefers an accelerated build path, Koder.ai standardizes this kind of stack (React on the frontend, Go + PostgreSQL on the backend) and supports planning mode, snapshots, rollback, and source code export—useful when you need to iterate quickly without locking yourself into a black box.
Hosts and kitchen teams need the same truth at the same time. For real-time updates (new orders, table status changes, reservation check-ins), use:
A common approach is to start with polling for the MVP, then add WebSockets when volume grows.
Plan your core objects early so features don’t fight each other later:
Restaurants change menus and hours constantly. Add an admin dashboard where managers can update menus, blackout dates, reservation rules, and table layouts—without waiting for a deploy.
If you want to move faster, use a lightweight CMS (or build a simple internal admin) so content changes stay safe, auditable, and quick.
Restaurant apps handle sensitive details: staff accounts, guest contact info, and payments. Getting the basics right early prevents expensive fixes later—and builds trust with guests and your team.
Protect accounts with secure authentication, strong passwords, and sensible permissions. Hosts don’t need the same access as managers.
Follow payment best practices by using a compliant payment provider (e.g., Stripe, Adyen, Square) instead of storing card data. This keeps your app out of the most complex parts of PCI compliance.
Practical rules:
When something goes wrong, you need a clear trail. Add audit logs for critical actions:
Include who did it, when, and what changed. Keep logs searchable in the manager view.
Collect only what you need (often: name, phone/email, party size, dietary notes). Provide a clear retention and deletion process:
If you operate in regulated regions, map your flows to GDPR/CCPA expectations early (consent where needed, access/deletion requests, and clear notices).
A restaurant app succeeds or fails during the busiest 90 minutes of the night. Treat testing and rollout as part of the product—not an afterthought.
Beyond “happy path” demos, run scenarios that mimic service pressure:
Include both “system” failures (slow network, printer offline, POS timeout) and “human” failures (host forgets to seat a party, server voids the wrong item). Your goal is graceful recovery.
Start with a single restaurant (or even a single shift) and gather feedback from:
Make it easy to report issues: one button for “something went wrong” plus a short note.
Create lightweight training plus printed SOPs:
Track a small set of operational metrics weekly:
Use insights to prioritize iterations, pricing changes (/pricing), or improvements to your ordering UX (see /blog/restaurant-online-ordering).
Start by writing one measurable outcome (e.g., “reduce no-shows” or “cut average wait time”). Then pick 1–2 guest flows and 1–2 staff flows that directly move that number.
A practical MVP set is often:
List your users by role and pressure level during service:
Design each screen around a single role’s “busy Friday night” decisions so the UI stays fast and focused.
Map workflows end-to-end (not feature-by-feature). A good starting set:
Include weekly edge cases like table merges, 86’d items, split payments, and comps so the MVP won’t break in real service.
Pick a few numbers that reflect both guest experience and staff load:
Make sure each metric is tied to an in-app event you can log (status changes, cancellations, payment states) so you can improve after launch.
At minimum, your reservation module should support:
Decide early on deposits/no-show policies, because they change both the guest UI and staff workflows (holds, disputes, and refunds).
Use simple, explicit rules and edit them without code:
To prevent double-booking, combine a short soft hold (2–5 minutes) with a final confirm step that re-checks conflicts before saving.
Start with a small set of one-tap states and capture timestamps:
available → reserved → seated → ordered → paid → cleaning → available
Timestamps let you calculate “time seated,” spot tables at risk of running long, and improve turn-time estimates without asking staff to do extra data entry.
Prioritize “hard to break” ordering:
Add kitchen guardrails like pausing items (86) and capping orders per time slot to prevent overload.
Use a payment provider (Stripe/Adyen/Square) and avoid storing card data.
Common decisions to make early:
Log payment state changes (authorized/captured/refunded) so end-of-night reconciliation is straightforward.
Treat testing like a service simulation, not a demo:
Roll out as a pilot (one location/shift), add simple SOPs for fallbacks, and track weekly metrics to drive iteration (see also /blog/testing-launch-and-improvement).