> ## Documentation Index > Fetch the complete documentation index at: https://docs.vortexiq.ai/llms.txt > Use this file to discover all available pages before exploring further. # Exception Rate, Amazon Prime Shipping (SFP) > Exception Rate for Amazon Prime Shipping (SFP) stores. Tracked live in Vortex IQ Nerve Centre. How to read it, why it matters, and how to act on it. **Metrics type:** [Key Metrics](/nerve-centre/overview#metrics-types-explained) • **Category:** [Shipping & Courier](/nerve-centre/connectors#connectors-by-type) ## 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. | | | | ----------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **What it counts** | `COUNT(DISTINCT shipments WHERE any_event IN ('FAILED_ATTEMPT','REFUSED','RTS','DAMAGED','UNDELIVERABLE')) / COUNT(shipments)` over rolling 30 days. Each consignment counts once. | | **What counts as "exception"** | Any non-success scan event from the carrier (UPS, USPS, OnTrac, Lasership, Amazon Logistics) in the merchant's chosen Prime-eligible carrier mix. | | **Customer-fault vs carrier-fault** | Pooled. \~60% customer-fault (recipient absent, address wrong, refused), \~30% carrier-fault (mis-route, depot delay), \~10% external (weather, force-majeure, customs for international Prime where applicable). | | **Service level scope** | Prime-eligible consignments only. | | **Money-back-on-late interaction** | Customer-fault exceptions do not affect SFP-eligibility scoring directly (Amazon excludes them from on-time calculation if properly tagged). Carrier-fault exceptions on Prime promises feed `amazon_prime_promise_miss_rate`. | | **Buy with Prime cohort** | Buy with Prime customers tend toward fewer exceptions (the cohort is Prime-engaged and provides reliable delivery preferences) but disproportionately impacted by exceptions when they occur. | | **2-day Prime coverage gaps** | Rural-ZIP exceptions are over-represented in the headline because rural deliveries hit more access issues, weather delays, and address-issue events than urban deliveries. | | **Time window** | `30D vsP` | | **Alert trigger** | `>3%` critical, `>1%` good. Amazon Prime Shipping cohort typically runs 1.0 to 2.5% (lower than Parcelforce / APC because of carrier mix + buyer-cohort selection bias). | | **Roles** | owner, operations | ## 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). | Exception reason | Consignments | % of exceptions | % of total volume | | -------------------------------- | ------------ | --------------- | ----------------- | | Recipient absent (no safe place) | 88 | 41% | 0.7% | | Address details required | 38 | 18% | 0.3% | | Refused at door | 22 | 10% | 0.2% | | Damaged in transit | 18 | 8% | 0.1% | | Driver mis-route / depot delay | 32 | 15% | 0.3% | | Weather / force-majeure | 18 | 8% | 0.1% | | **Total exceptions** | **216** | 100% | **1.7%** | Total volume: 12,700 consignments. The card reads **1.7%**, comfortably under the 3% alert. Five things to notice: 1. **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. 2. **Damaged-in-transit 0.1% is healthy.** Health and beauty packaging tends to be reasonably robust; below 0.3% benchmark. 3. **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. 4. **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. 5. **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: | Card | Why pair it with Exception Rate | What the combination tells you | | -------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------- | -------------------------------------------------------------------------------------- | | [Failed Deliveries](/nerve-centre/kpi-cards/amazon-prime-shipping/failed-deliveries) | Subset specifically carrier-fault first-attempts. | Subtract failed-deliveries from exceptions for the customs/damage/access-issue bucket. | | [Prime 1-Day / 2-Day Promise Miss Rate](/nerve-centre/kpi-cards/amazon-prime-shipping/prime-1-day-2-day-promise-miss-rate) | Carrier-fault subset that affects SFP eligibility. | Most carrier-fault exceptions feed promise-miss. | | [Returned to Sender](/nerve-centre/kpi-cards/amazon-prime-shipping/returned-to-sender) | Terminal exception subset. | High exception + rising RTS = re-attempt logic failing. | | [On-Time Delivery Rate](/nerve-centre/kpi-cards/amazon-prime-shipping/on-time-delivery-rate) | Some exceptions still deliver on time after re-attempt. | High exception + high OTD = re-attempts working. | | Cross-connector: [`amazon.az_claims`](/nerve-centre/amazon/az_claims) | A-to-Z claims downstream impact. | Refused-at-door + damage exceptions drive A-to-Z claims at 10 to 14 day lag. | | Cross-connector: [`shopify.refund_rate`](/nerve-centre/kpi-cards/shopify/refund-rate) (for Buy with Prime) | Direct downstream for Buy-with-Prime cohort. | Prime-cohort refund rate is sharper-responding than non-Prime. | | Cross-connector: [`shipbob.sb_exception_rate`](/nerve-centre/shipbob/sb_exception_rate) | Peer 3PL benchmark. | Different orders entirely; comparable cohort behaviour for benchmarking. | ## 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:** | Reason | Direction | Why | | ---------------------------- | ----------- | ------------------------------------------------------------------------------------------------ | | **Distinct vs event-count** | Ours lower | Carrier portals count each scan; card de-duplicates per consignment. | | **Customer-fault inclusion** | Ours higher | Amazon's eligibility-scoring excludes properly-documented customer-fault; the card includes all. | | **Time zone** | Boundary | PST (Amazon) vs connected-timezone (card). | **Cross-connector reconciliation:** | Card | Expected relationship | What causes legitimate divergence | | ---------------------------------------------------------------------- | --------------------- | ---------------------------------------------- | | [`amazon.az_claims`](/nerve-centre/amazon/az_claims) | Downstream. | A-to-Z claims involve more than late delivery. | | [`shipbob.sb_exception_rate`](/nerve-centre/shipbob/sb_exception_rate) | Peer 3PL. | Different orders. | ## 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. *** ### Tracked live in Vortex IQ Nerve Centre *Exception Rate* is one of hundreds of KPI pulses Vortex IQ tracks across Amazon Prime Shipping (SFP) and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. [Start for free](https://app.vortexiq.ai/login) or [book a demo](https://www.vortexiq.ai/contact-us) to see this metric running on your own data.