At a glance
Share of Amazon Prime Shipping consignments that hit any non-success scan event in the period: failed first attempt, customer-not-home, address issue, refused, damage, returned-to-sender. Exception is broader than “Prime promise miss” because some exceptions still deliver on-time after a re-attempt. The card surfaces operational noise that does not always show on the headline OTD but degrades Prime customer experience.
Calculation
Calculated automatically from your Amazon Prime Shipping (SFP) data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A US health-and-beauty merchant on SFP shipping from Phoenix: $45 average order, mix of UPS Ground 2-Day to East and OnTrac to West Coast. Reading taken at 09:00 PT on 22 Mar 26 for the trailing 30 days (20 Feb 26 to 21 Mar 26).
Total volume: 12,700 consignments. The card reads 1.7%, comfortably under the 3% alert. Five things to notice:
- Recipient-absent at 41% is below the carrier-network average (~50 to 60% on UK premium tier; less applicable here, USPS/UPS/OnTrac differ but pattern similar). Amazon Prime customers tend to be home or have engaged delivery preferences (apartment-package-rooms, secure lobby drops); the cohort selection helps.
- Damaged-in-transit 0.1% is healthy. Health and beauty packaging tends to be reasonably robust; below 0.3% benchmark.
- Driver mis-route / depot delay at 15% is the carrier-fault cohort that feeds
amazon_prime_promise_miss_rate. Track this slice; rising trend indicates carrier-side performance issue requiring carrier mix review. - Weather / force-majeure is seasonal. Storm-of-the-century events drive cohort spikes; Amazon excludes documented weather-events from SFP eligibility scoring if filed properly via the Seller Central case system.
- 1.7% exception rate against 1.0 to 2.5% benchmark is in spec. No urgent action; track refused-at-door cohort because it correlates with downstream A-to-Z claim rate (Amazon’s customer-protection program). A 1-point refused-at-door rise predicts 0.2 to 0.4 point A-to-Z claim rise at 10 to 14 day lag.
Sibling cards merchants should reference together
Exception rate is the broad operational-noise gauge. Pair with these:Reconciling against the vendor’s own dashboard
Where to look: Exception rate is not a native single Amazon-dashboard metric. The closest views: Seller Central → Performance → Account Health → Customer Service Performance for refused / claim events, and Performance → Shipping Performance → Late / Failed Shipment Rate for delivery-side exceptions. Carrier-side (UPS, USPS) portals expose their own exception dashboards which are the source-of-truth for delivery-attempt events. Why our number may legitimately differ:
Cross-connector reconciliation:
Known limitations / merchant FAQs
Why is the Prime Shipping exception rate lower than Parcelforce / APC? Selection bias plus carrier mix. Amazon Prime customers are more delivery-engaged (more likely to set apartment-package-room preferences, secure-lobby drops); the cohort generates fewer recipient-absent exceptions. Carrier mix (UPS, OnTrac, Amazon Logistics) favours large-network operators with mature exception-handling infrastructure. Customer-fault exceptions: do they count against SFP eligibility? Not when properly documented. Amazon’s SFP eligibility scoring excludes weather, force-majeure, customer-fault delivery refusals if the seller files a Plan-of-Action via Seller Central case management. The card includes all because all affect operations and customer perception; the SFP-eligibility-specific card (amazon_prime_sfp_otd_sla) tracks the Amazon-scored slice.
Damaged-in-transit on Prime drives A-to-Z claims; how do we mitigate?
Two paths. (1) Packaging review: Prime customers often have heightened expectations because Amazon’s branded packaging is well-engineered; merchant-side packaging that arrives bruised triggers refusal disproportionately. (2) Carrier choice: UPS Ground generally handles parcels more gently than USPS Priority for small-package volumes.
Refused-at-door climbing: what is the lead indicator?
Often an Amazon listing-side issue: stale product photos, sizing variance, customer expectation gap. A 0.3-point refused-at-door rise typically follows a SKU launch where listing copy did not match received product. Cross-reference with Amazon’s recent return-reason analysis for the affected ASINs.
Weather / force-majeure: how do we get them excluded from SFP scoring?
File a case in Seller Central within 48 hours of the event with documented context (NWS storm warnings, carrier-published service alerts, FAA advisories for air-freight). Amazon excludes these from the eligibility floor when accepted; appeals run 5 to 10 days.
Buy with Prime exceptions: are they pooled?
Yes the card pools both unless the merchant only has one product line connected. Buy with Prime customer-cohort tends toward fewer exceptions but disproportionately impacted by bad ones (Prime-trust signal is sharper-broken).
Q4 peak: what is realistic?
Q4 typically lifts exception rate 1.5 to 2.5 percentage points across all networks. Plan capacity in October; consider pre-emptive Prime-suspension during November-December if exception rate threatens SFP eligibility floor.
A single bad UPS depot: how do we identify?
Pair this card with ama_route_otd for geographic split. If exceptions cluster in 2 to 3 ZIP code prefixes that share a UPS hub-and-spoke route, the issue is depot-level. Account-team conversation with UPS or shift to Amazon Logistics for those ZIPs if available.
Compared to FBA-level exception rate, where does SFP land?
FBA typically runs lower exception rate (1 to 2%) because Amazon’s fulfilment centres are highly automated and use Amazon Logistics for most last-mile. SFP at 2 to 3% is comparable but consistently slightly higher; the gap is the merchant-side warehouse vs Amazon-side warehouse efficiency.
Single-warehouse SFP: are exceptions higher than 2-warehouse setup?
Yes structurally. Single-warehouse SFP has longer transit distances on average (more zone-distance per shipment), more weather and route-variability exposure, more chance of an exception per shipment. Multi-warehouse setups reduce exceptions by 0.5 to 1.5 percentage points.