User Stories and Personas for Route Optimization

User Personas

1. Maria - Founder of Artisan Blooms

Profile: - Online florist owner - 3-year-old business - Daily delivery volume: 100-300 orders - Manually plans routes using spreadsheets and Google Maps - Primary Pain Point: Inefficient route planning consuming 3-4 hours daily

Goals: - Reduce route planning time - Minimize delivery costs - Improve delivery efficiency - Scale business without increasing operational complexity

2. Carlos - Logistics Coordinator

Profile: - Manages delivery team - Responsible for route optimization - Uses multiple tools and manual calculations - Struggles with: * Balancing driver workload * Minimizing fuel costs * Meeting delivery time commitments

Goals: - Automate route planning - Improve driver satisfaction - Reduce operational overhead

User Stories

Bulk Upload and Initial Processing

1. As Maria, I want to upload my daily delivery list quickly
2. Given I have a CSV file with delivery locations
3. When I upload the file

4. Then I should receive immediate validation feedback

   • Validate all delivery IDs
   • Check latitude/longitude accuracy
   • Show me which rows have errors
   • Allow partial upload of valid entries

5. As Carlos, I need a clear overview of my uploaded deliveries

6. Given I've uploaded a delivery list
7. When the system processes the file
8. Then I want to see:
   • Total number of deliveries
   • Number of valid and invalid entries
   • Estimated total route distance
   • Potential optimization opportunities

Route Optimization

1. As Maria, I want an intelligent route suggestion
2. Given I have a list of deliveries
3. When the system generates routes

4. Then I expect:

   • Grouped deliveries by geographic proximity
   • Estimated time and fuel savings
   • Recommended vehicle type for the route
   • Option to manually adjust suggested routes

5. As Carlos, I need flexible route management

6. Given an initial route suggestion
7. When I review the proposed routes
8. Then I can:
   • Add priority markers to specific deliveries
   • Manually override system suggestions
   • Save custom route configurations
   • Compare multiple routing options

Reporting and Insights

1. As Maria, I want to track route efficiency
2. Given completed deliveries
3. When I access the system dashboard

4. Then I can see:

   • Actual vs. suggested route performance
   • Fuel and time savings
   • Delivery success rates
   • Trends in route optimization

5. As Carlos, I need comprehensive reporting

6. Given multiple delivery days
7. When I generate reports
8. Then I want insights on:
   • Driver performance
   • Route efficiency trends
   • Potential areas of improvement
   • Cost-saving opportunities

Acceptance Criteria

System Capabilities

• Support CSV uploads up to 200 entries
• Validate all input data with clear error messaging
• Generate route suggestions within 5 seconds
• Provide interactive route planning interface
• Offer real-time route refinement
• Maintain data privacy and security

Performance Metrics

• Reduce route planning time by 75%
• Achieve 10-15% fuel cost savings
• Improve delivery time accuracy by 20%
• Support partial uploads with clear error reporting
• Provide near-instantaneous route optimization feedback

Technical Constraints

• Works with standard CSV formats
• Supports major web browsers
• Mobile-responsive design
• Integrates with existing delivery tracking systems

Future Considerations

• Machine learning model to improve suggestions over time
• Integration with real-time traffic and weather data
• Support for multiple vehicle types
• Expansion to other industry verticals

Next Implementation Steps

1. Design initial data validation logic
2. Create route clustering algorithm
3. Develop user interface mockups
4. Build prototype for initial testing