What's a good FADR to target?

It depends on vertical and geography. 85–90% is strong for general parcel; 90%+ is excellent. Big-and-bulky can hit 95%+. Below 75% usually indicates structural problems (address quality, scheduling, customer comms) rather than driver execution.

What are the top reasons for first-attempt failure?

Consistently: incorrect or incomplete address (often 30–40% of failures), customer unavailable (25–35%), refused delivery or wrong time window (10–20%), and access issues (10–15%). Operational errors are usually a small fraction.

How does AI improve FADR?

AI helps with address normalization (turning unstructured inputs into deliverable addresses), ETA accuracy (so proactive comms are actually useful), and NDR rescue (autonomously resolving the failure before a retry). Each lever compounds.

Does FADR apply to quick commerce?

In principle yes, but FADR is usually near 98–99% in quick commerce because orders are initiated by customers who are actively waiting. The equivalent QC metric is usually SLA adherence (10-min delivery %).

What's the relationship between FADR and cost per shipment?

Roughly linear in the reverse direction — every 1% FADR improvement reduces cost per shipment by 1.5–2% because retry costs scale faster than attempt counts. For high-volume networks, FADR is often the biggest single lever on unit economics.

What is FADR (First Attempt Delivery Rate)?

First Attempt Delivery Rate (FADR) is the percentage of shipments successfully delivered on the first delivery attempt. It’s one of the most consequential metrics in last-mile logistics because every failed first attempt triggers a second (or third) delivery run — and each retry roughly doubles the cost of that shipment while degrading customer experience.

How does it work

FADR is calculated as: (shipments delivered on first attempt) ÷ (total delivery attempts made) × 100. A 90% FADR means 9 out of every 10 parcels were delivered the first time a driver reached the address.

First-attempt failure comes from a handful of root causes: incomplete or incorrect address, customer unavailable, refused delivery, access issues (security gate, building restriction, closed office hours), wrong time window, or operational errors (loaded onto wrong vehicle, missing paperwork). Each root cause has a different fix — which is why measuring FADR alone isn’t enough; operators need FADR broken down by failure reason.

Improving FADR usually requires action in three places: pre-dispatch (address cleaning, time-window planning), in-transit (proactive customer comms, ETA accuracy), and at-door (driver app capabilities, flexible handoff).

Why it matters

FADR is the largest single lever on last-mile unit economics. A shipment that fails and needs a retry costs roughly 1.8–2.2× the original delivery attempt. For a parcel operator doing 100,000 shipments a day at 85% FADR, pushing to 92% FADR is typically millions of dollars in monthly savings plus materially better customer NPS.

It also correlates tightly with network scalability. Operations with low FADR hit a wall at peak — there’s simply no capacity to absorb the retry volume. High-FADR operations scale through peaks without the same cost shock.

Where it shows up in logistics

FADR benchmarks vary by vertical and geography.

Segment	Typical FADR range	Notes
E-commerce parcel (developed markets)	85–92%	Driven by address quality and customer comms
E-commerce parcel (emerging markets)	65–80%	Address data and availability are harder
Big & bulky / furniture	90–95%+	Scheduled slots lift FADR materially
Pharma home delivery	88–94%	OTP-driven, requires recipient present
COD deliveries	70–85%	Payment friction reduces first-attempt success

A global big-and-bulky retailer operating in the furniture and home-goods category has sustained 95%+ FADR on Shipsy — the top of the industry range.

How Shipsy approaches FADR

Shipsy attacks FADR across the whole journey. Before dispatch, the Address Intelligence Service normalizes and enriches incomplete addresses — a major driver of first-attempt failure in many markets. Time-window planning ensures routes respect customer availability. During execution, Clara runs proactive customer comms — the pre-dispatch message, the en-route update, and the 15-minute-out nudge — which dramatically lifts customer readiness. When exceptions happen, Clara attempts autonomous NDR rescue (rescheduling, drop-off options, neighbor delivery) before triggering a retry. Astra dynamically re-sequences routes in real time if earlier stops slip. The compounded effect is typically a 5–15 point FADR lift.

Explore the FADR mechanisms deep-dive, the Last-Mile product page, or the industries hub.