Failed Delivery Attempt Data
Buy and sell failed delivery attempt data data. Why deliveries fail - not home, wrong address, gated community, dog. Each failed attempt costs $15-20. This data prevents them.
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Find Me This Data →Overview
What Is Failed Delivery Attempt Data?
Failed Delivery Attempt Data documents why shipments don't reach customers on first attempt—whether due to incorrect addresses, recipients being unavailable, limited delivery windows, or access issues like gated communities. Each failed attempt costs logistics and e-commerce businesses approximately $17.20 in direct operational expenses (fuel, labor, vehicle maintenance) plus the downstream cost of lost customer loyalty. This dataset helps delivery networks, logistics operators, and e-commerce platforms predict and prevent failure scenarios before they happen, enabling companies to optimize routing, validate addresses, and coordinate better with customers to achieve first-attempt success rates around 90%.
Market Data
$17.20 USD
Cost Per Failed Attempt
Source: Alexander Jarvis
69-70% won't return
Customer Loss After One Failure
Source: Alexander Jarvis
36% of failed attempts
Recipients Not Home (Primary Cause)
Source: Alexander Jarvis
Up to 30% of orders contain errors
Incorrect Address Problem Rate
Source: Alexander Jarvis
90% (efficient retailers)
First-Attempt Success Benchmark
Source: Alexander Jarvis
Who Uses This Data
What AI models do with it.do with it.
E-commerce Operations
Platforms use failed attempt patterns to validate addresses at checkout, reducing errors by up to 70%, and segment customers by delivery availability to optimize scheduling and reduce costly re-attempts.
Last-Mile Delivery Networks
Logistics operators leverage historical failure data to improve route optimization, predict access issues (gated communities, apartment numbers), and allocate resources more efficiently to boost first-attempt success rates.
Customer Service & CRM Integration
Combining delivery attempt data with CRM systems reveals patterns in address mistakes and customer availability, enabling proactive outreach and reducing failed attempts by up to 30% through better coordination.
Supply Chain Analytics
Predictive supply chain systems use failed delivery datasets to move from reactive (post-mortem) incident management to proactive forecasting, anticipating delays and preventing cascading operational inefficiencies.
What Can You Earn?
What it's worth.worth.
Per Failed Attempt Record
Varies
Market reference: businesses lose $17.20 per failed attempt; data value scales with prediction accuracy and scale of operations covered
Historical Dataset Bundle
Varies
Comprehensive last-mile delivery datasets command premium pricing based on volume, geographic coverage, and failure reason taxonomy
Real-Time Feed
Varies
Streaming failed delivery signals offer higher margins; value depends on latency, coverage area, and integration with buyer's logistics platform
What Buyers Expect
What makes it valuable.valuable.
Root Cause Classification
Clear categorization of failure reasons: incorrect address, recipient not home, access restrictions (gated, locked), delivery window misalignment, or location data issues.
Addressability & Validation
Data must include address details (street, apartment/unit, ZIP, coordinates if available) and indicate whether addresses failed validation or if errors were detected post-delivery.
Operational Context
Include attempt timestamps, delivery window offered, customer availability signals (if available), and any access barriers encountered to enable pattern matching and predictive modeling.
Scale & Consistency
Large, deduplicated datasets with consistent schema across geographies and time periods; buyers use this to train machine learning models and validate improvement strategies.
Companies Active Here
Who's buying.buying.
Published LaDe, the first comprehensive last-mile delivery dataset from industry, indicating active investment in delivery attempt analytics and failure prevention
Implement address verification tools and CRM integration to reduce failed attempts by 30-70%; heavily dependent on accurate failure data to optimize delivery operations
Use historical delivery attempt data to train predictive models, optimize routing, and proactively address access issues before delivery windows occur
FAQ
Common questions.questions.
What is the typical cost of a failed delivery attempt?
Each failed delivery attempt costs businesses an average of $17.20 in the U.S. (£11.6 in the UK). This includes fuel, labor, vehicle maintenance, and customer service overhead. For lower-priced items, these costs can wipe out profit margins.
What are the most common reasons for failed deliveries?
The primary causes are: recipients not home (36% of failed first attempts), incorrect address information (22% reported by consumers, up to 30% of orders contain errors like typos or missing apartment numbers), and limited delivery windows forcing customers to choose between personal commitments and package receipt.
How much can address verification improve delivery success?
Implementing address verification tools at checkout can reduce errors by up to 70%. Proactive customer communication—like confirming current addresses before delivery—prevents costly routing errors, as about 25% of shoppers won't update addresses after moving.
What impact does a failed delivery have on customer loyalty?
Approximately 69-70% of shoppers won't return after experiencing a delivery failure, forcing businesses to spend significantly more on customer acquisition to offset lost lifetime value.
Sell yourfailed delivery attemptdata.
If your company generates failed delivery attempt data, AI companies are actively looking for it. We handle pricing, compliance, and buyer matching.
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