Reserve Easy Project
Welcome to ReserveEasy 🍽️
You are now the Product Manager for ReserveEasy - a two-sided marketplace connecting diners with restaurants for seamless table reservations.
This folder contains the complete product lifecycle - from initial market research through technical implementation to analytics and quality assurance.
The Product
For Diners:
- Search restaurants by cuisine, location, price range
- View real-time table availability
- Book in 60 seconds (vs 5 minutes calling)
- Instant SMS confirmation
- Easy modification/cancellation
For Restaurants:
- Reduce no-shows from 30% to <5%
- Automated customer communication
- Analytics dashboard (peak hours, popular dishes)
- Fill tables during off-peak hours
The Business Model
Revenue: 10% commission on completed bookings
Example:
- Average booking value: $50/person × 4 people = $200
- ReserveEasy commission: $200 × 10% = $20 per booking
- Target: 10,000 bookings/month = $200k monthly revenue
Project Structure
📊 01-discovery/
Market research, user personas, opportunity analysis
Key Files:
- market-analysis.md - 9-Dimension Gap Analysis
- user-personas.md - "Restaurant Manager Raj" & "Busy Diner Sarah"
- opportunity-tree.md - Visualizing business outcomes → solutions
📐 02-specs/
Requirements documentation and technical specifications
Key Files:
- BRD-v1.0.md - Business Requirements Document
- FSD-booking-mod.md - Functional Specification for booking modifications
- API-specs/booking-api.yaml - OpenAPI 3.0 specification (code-adjacent!)
- API-specs/webhooks.md - SMS Gateway integration docs
Portfolio Highlight: Show interviewers the .yaml file - proves you can work with engineers.
🎨 03-design/
Process maps and UI/UX artifacts
Key Files:
- process-maps.md - Mermaid sequence diagrams (User → App → DB → SMS Gateway)
- wireframes/ - Placeholder for Figma/Sketch links
⚡ 04-delivery/
Agile execution artifacts
Key Files:
- product-backlog.md - Prioritized user stories with story points
- sprints/sprint-15-goal.md - Example sprint commitment
📊 05-analytics/
Metrics, SQL queries, and data analysis
Key Files:
- north-star-metric.md - KPI definitions (Monthly Active Bookers)
- schema.sql - PostgreSQL database schema (code-adjacent!)
- queries/funnel_analysis.sql - Track conversion drop-offs
- queries/retention_cohort.sql - Cohort retention analysis
- queries/ab_test_results.sql - Statistical significance testing
Portfolio Highlight: Real .sql files with syntax highlighting - shows data fluency.
🛡️ 06-qa/
Test plans, test cases, and defect tracking
Key Files:
- master-test-plan.md - Comprehensive QA strategy
- test-cases/TC-001-guest-booking.md - Detailed manual test script
- bug-reports/BUG-234-sms-fail.md - Example defect documentation
How to Use This Project
For Learning
- Read the curriculum module first (e.g., Module 1: Requirements Engineering)
- Apply it to ReserveEasy (e.g., read the Gap Analysis)
- Try it yourself - create artifacts for your own product idea
For Portfolios
- Fork this repository to your GitHub
- Replace ReserveEasy with your own product (keep the structure)
- Show in interviews: "Here's my BRD, API spec, and SQL queries for market analysis"
For Practice
- Create issues using .github templates
- Submit PRs with improvements
- Practice Git workflows (branch, commit, review)
The Team (Fictional)
- Product Manager (You): Define what to build
- Engineering Lead (Alex): Technical architecture
- Designer (Maya): UI/UX mockups
- Data Analyst (Chris): SQL queries, dashboards
- QA Lead (Jordan): Test plans, test cases
- Stakeholders: Restaurant owners, investors, exec team
Timeline
Success Metrics
| Metric | Baseline | Target (Year 1) | Current |
|---|---|---|---|
| Monthly Active Bookers (MAB) | 0 | 15,000 | TBD |
| Restaurants Onboarded | 0 | 500 | TBD |
| Booking Conversion Rate | - | 25% | TBD |
| No-Show Rate Reduction | 30% (industry) | <5% | TBD |
| Average Booking Time | 5 min (phone) | <60 sec | TBD |
What Makes This Real-World?
1. Code-Adjacent Documentation
- API specs in
.yaml(not Word docs) - SQL queries in
.sqlfiles (not screenshots) - Diagrams in Mermaid (version-controlled)
2. Realistic Complexity
- Multi-stakeholder (diners + restaurants)
- Real integrations (payment, SMS)
- Edge cases (conflicts, no-shows, refunds)
3. Data-Driven
- North Star Metric defined
- SQL queries Written for funnel, cohort, A/B test analysis
- Metrics dashboard specified
Get Started
📖 Start with: Market Analysis
🏗️ Then review: BRD → API Spec → SQL Schema
🛠️ Practice: Create your own product using this structure as a template