Delivery Route Data
Buy and sell delivery route data data. Last-mile delivery paths with timestamps, stop durations, and completion rates. Route optimization AI runs on this data.
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Find Me This Data →Overview
What Is Delivery Route Data?
Delivery route data comprises last-mile delivery paths with timestamps, stop durations, and completion rates collected from real-world logistics operations. This data captures the granular details of how packages move from distribution centers to customer addresses, including GPS coordinates, visit sequencing, dwell times at each stop, and whether deliveries succeeded on the first attempt. Route optimization AI and machine learning models rely on this data to predict delivery failures, improve scheduling accuracy, and reduce operational inefficiencies across e-commerce and logistics networks.
Market Data
Up to 20%
First-Attempt Delivery Failure Rate
Source: Production and Operations Management
Over $2 billion
Annual Cost of Failed Deliveries (UK)
Source: ResearchGate
39 million miles
Miles Saved by UPS ORION System
Source: The Knowledge Academy
20,000 metric tonnes
CO2 Emissions Reduced (UPS ORION)
Source: The Knowledge Academy
Who Uses This Data
What AI models do with it.do with it.
Route Optimization Algorithms
AI systems analyze delivery route data and driver movements to identify the most efficient paths, reduce miles driven, and lower fuel costs.
Delivery Attempt Prediction
Machine learning models use historical route and stop data to predict delivery failures, enabling carriers to prioritize routes with higher first-attempt success rates.
Last-Mile Logistics Planning
Logistics operators use timing, stop duration, and completion rate data to optimize dispatch scheduling and reduce delivery failures that damage brand reputation.
Real-Time Shipment Tracking
E-commerce platforms and logistics providers leverage route data for proactive problem-solving and real-time visibility of goods movement.
What Can You Earn?
What it's worth.worth.
Varies
Varies
Pricing depends on data volume, geographic coverage, temporal resolution (granularity of timestamps), completion rate accuracy, and exclusivity. High-quality datasets from major carriers command premium rates.
What Buyers Expect
What makes it valuable.valuable.
Accurate Timestamps
Precise arrival and departure times at each delivery stop, enabling temporal analysis and scheduling optimization.
Stop Duration Data
Detailed dwell times at each location, reflecting service complexity and allowing better prediction of delivery windows.
Completion Rates & Attempt Metadata
Clear indication of whether deliveries succeeded on first attempt, reasons for failure (if available), and retry information for training failure-prediction models.
GPS Coordinates & Route Sequencing
Precise latitude/longitude and the order in which stops were visited, essential for route reconstruction and optimization algorithm training.
Companies Active Here
Who's buying.buying.
Uses GPS tracking, handheld devices, and sensors to gather delivery data; operates ORION (On-Road Integrated Optimisation and Navigation) system that analyzes route data and driver movements to optimize paths and reduce emissions.
Leverage delivery route data to optimize networks, select carriers with higher first-attempt success rates, and reduce delivery failures that harm brand reputation.
Deploy big data analytics to optimize last-mile logistics operations, enable real-time shipment tracking, and enhance proactive problem-solving.
FAQ
Common questions.questions.
Why is delivery route data valuable?
Delivery route data enables optimization of last-mile logistics, prediction of delivery failures, reduction in miles driven, and lower fuel costs. With up to 20% of deliveries failing on first attempt, this data is critical for improving success rates and reducing operational costs.
What specific data points should I include?
Include GPS coordinates, timestamps (arrival/departure at each stop), stop duration, delivery completion status, attempt number, and any failure reasons if available. Higher temporal and spatial granularity increases value for route optimization AI.
Who are the primary buyers?
Major logistics carriers (like UPS), e-commerce retailers, last-mile delivery platforms, and route optimization software vendors are active buyers. They use the data to train algorithms, reduce failed deliveries, and improve scheduling.
How does this data differ from general location data?
Delivery route data is specifically structured around stop sequences, dwell times, and completion outcomes rather than continuous location tracking. This sequential, delivery-focused perspective makes it directly applicable to logistics optimization and failure prediction models.
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If your company generates delivery route data, AI companies are actively looking for it. We handle pricing, compliance, and buyer matching.
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