Booking Platform Feature Spec Template

What This Template Is For

Booking platforms sit at the intersection of supply (available time slots, rooms, seats, or resources) and demand (customers who want to reserve them). The core challenge is managing real-time availability without double-booking, handling timezone differences, and designing cancellation policies that balance flexibility for customers with predictability for providers.

This template helps you spec features for any reservation-based product: appointment scheduling, hotel or venue booking, event ticketing, equipment rental, or service marketplace scheduling. It covers the data model for availability, the user flows for both the booking side and the provider side, payment integration points, and the notification system that keeps all parties informed.

Use the PRD Template for broader product context before diving into this feature-level spec. If you are building a two-sided marketplace, the Product Strategy Handbook covers platform strategy fundamentals. For estimating your market opportunity, the TAM Calculator helps size the addressable market for your specific booking vertical.

How to Use This Template

1. Define the booking object first. What exactly is being reserved? A 30-minute slot with a person? A room for a date range? A seat at a specific time? The booking object determines every downstream design decision.
2. Map both sides of the marketplace. Spec the provider experience (setting availability, managing bookings, viewing earnings) and the customer experience (searching, booking, modifying, canceling) as parallel workflows.
3. Design for concurrency. Two users viewing the same available slot will both try to book it. Define how your system handles race conditions: optimistic locking, hold timers, or queue-based processing.
4. Specify timezone handling upfront. If providers and customers can be in different timezones, define where timezone conversion happens and what timezone is displayed in each context.
5. Model cancellation economics carefully. Cancellation policies directly affect provider trust, customer satisfaction, and platform revenue. Define the rules before building the happy path.

Booking Platform Feature Spec

Feature Overview

One-line summary: [What this feature does in plain language.]

Business context: [Why this feature matters. Booking volume, provider onboarding rate, customer conversion rate, or competitive gap.]

Booking Object Model

Define the core entity being reserved.

BookingObject:
  id: UUID
  type: [appointment / room / seat / equipment / service]
  provider_id: UUID (who owns or provides this)
  name: string
  description: text
  duration: [fixed / variable] (minutes or date range)
  capacity: integer (1 for appointments, N for group/room)
  location: [physical address / virtual link / hybrid]
  timezone: IANA timezone string
  price: decimal (currency)
  currency: ISO 4217 code
  status: [active / paused / archived]
  metadata: JSON (vertical-specific fields)

Booking record:

Booking:
  id: UUID
  booking_object_id: UUID
  customer_id: UUID
  provider_id: UUID
  start_time: datetime (UTC)
  end_time: datetime (UTC)
  status: [pending / confirmed / checked_in / completed / cancelled / no_show]
  payment_status: [pending / authorized / captured / refunded / partially_refunded]
  cancellation_reason: string (nullable)
  cancelled_by: [customer / provider / system / admin]
  created_at: datetime
  updated_at: datetime
  notes: text (nullable)

Availability Management (Provider Side)

Define how providers set and manage their available inventory.

Availability model:

Provider availability settings:

• ☐ Recurring weekly schedule (e.g., Mon-Fri 9am-5pm)
• ☐ Per-day overrides (block specific dates, extend hours)
• ☐ Buffer time between bookings: [N] minutes
• ☐ Minimum advance notice: [N] hours before booking
• ☐ Maximum advance booking window: [N] days ahead
• ☐ Capacity per slot: [1 / N / configurable per slot]
• ☐ Break times: [manual / auto-insert after N consecutive bookings]
• ☐ Holiday calendar integration: [manual / country-specific auto]

Availability calculation logic:

Available slots =
  (Recurring schedule for day)
  - (Per-day blocks/overrides)
  - (Existing confirmed bookings)
  - (Buffer time around bookings)
  - (Slots within minimum advance notice window)
  filtered by: capacity > current_bookings

Search and Discovery (Customer Side)

Define how customers find and select available options.

Search parameters:

Search results display:

• ☐ List view with date/time grouping
• ☐ Calendar view (day / week / month)
• ☐ Map view (for location-based searches)
• ☐ Provider comparison cards
• ☐ Real-time availability indicators (green/yellow/red)
• ☐ Price displayed per [unit / hour / session / night]

Sort options: [Earliest available / Price low-high / Rating / Distance / Relevance]

Booking Flow

Define the step-by-step process from selection to confirmation.

Step 1: Select slot

• Customer selects an available time slot or date range
• System places a temporary hold for [5 / 10 / 15] minutes
• Show countdown timer if hold is active
• If hold expires, release slot back to available inventory

Step 2: Provide details

• Customer enters required information: [name, email, phone, party size, special requests]
• Pre-fill from profile if customer is logged in
• Guest checkout: [Allowed / Requires account]

Step 3: Payment

• Payment timing: [Pay now / Pay at time of service / Deposit + remainder]
• Payment methods: [Credit card / PayPal / Apple Pay / Bank transfer]
• Authorization: [Full capture / Auth hold + capture on completion]
• Deposit amount: [Flat fee / Percentage of total]
• Tax calculation: [Inclusive / Added at checkout]

Step 4: Confirmation

• Show confirmation screen with booking details
• Send confirmation email to customer
• Send notification to provider
• Add to customer's calendar: [.ics file / Google Calendar / Apple Calendar]
• Booking reference number format: [e.g., BK-YYYYMMDD-XXXX]

Cancellation and Modification

Define the policies and workflows for changes.

Cancellation policy tiers:

Modification rules:

• ☐ Date/time change: [Allowed N times / Once / Not allowed]
• ☐ Reschedule window: [Same cancellation tiers apply / Free reschedule anytime]
• ☐ Party size change: [Allowed if capacity permits / Requires new booking]
• ☐ Provider-initiated cancellation: [Full refund always / Platform credit option]
• ☐ Platform-initiated cancellation (e.g., fraud): [Full refund + notification]

Cancellation flow:

1. Customer requests cancellation via [app / email / phone]
2. System calculates refund based on policy tier
3. Show refund amount and confirmation prompt
4. Process refund to original payment method
5. Release slot back to available inventory
6. Notify provider of cancellation
7. Offer customer option to rebook

Notifications

Timezone Handling

Timezone detection: Use browser timezone API for web. Use device timezone for mobile. Allow manual override in user settings.

Concurrency and Double-Booking Prevention

Chosen approach: [Describe which strategy and why]

Race condition handling:

• If two users attempt to book the same slot simultaneously, [first to complete payment wins / first to click "book" wins / system holds for both and resolves]
• Losing user receives: [immediate error / waitlist option / suggestion of next available slot]

Edge Cases

Out of Scope

• [Recurring/subscription bookings (future iteration)]
• [Waitlist functionality (future iteration)]
• [Multi-provider group bookings (e.g., booking a team of 3 stylists)]
• [Loyalty program or reward points]
• [Dynamic pricing or surge pricing]

Filled Example: Salon Appointment Booking

Feature Overview

One-line summary: Customers search for salons by service type and location, view stylist availability in real-time, and book appointments with instant confirmation.

Business context: Currently 62% of salon bookings happen via phone. Converting phone bookings to self-serve digital bookings reduces salon staff overhead by 3.5 hours per week per location. Customer research shows 78% of users under 35 prefer online booking. For a framework to prioritize which service types to launch first, see the RICE scoring method.

Availability Setup

Each stylist sets their own schedule:

• Recurring weekly hours (e.g., Tue-Sat, 9am-6pm)
• 15-minute buffer between appointments for cleanup
• Lunch block: 12pm-1pm daily
• Minimum 4 hours advance notice for new bookings
• Maximum 30-day booking window

Services have fixed durations: Haircut (45 min), Color (120 min), Blowout (30 min), Treatment (60 min).

Cancellation Policy

After 3 no-shows in 90 days, require prepayment for future bookings. For tracking metrics like no-show rate and rebooking rate, the Product Analytics Handbook covers how to set up a metrics dashboard.