> ## 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, Bring > Exception Rate for Bring 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 Bring consignments that hit a non-delivery exception event in the period: held at terminal, address invalid, recipient absent, customs delay, weather hold, or other interruption that breaks the normal "booked → in transit → delivered" flow. Exceptions do not always become late deliveries (most resolve within 24 hours), but a rising exception rate is the leading indicator that next week's [On-Time Delivery Rate](/nerve-centre/kpi-cards/bring/on-time-delivery-rate) and [Late Shipments](/nerve-centre/kpi-cards/bring/late-shipments) will move down. Treat this as the early-warning dial on Bring carrier health. | | | | ----------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **What it counts** | `COUNT(DISTINCT consignmentNumber WHERE event_code IN exception_codes) / COUNT(DISTINCT consignmentNumber WHERE booked_in_period)`. A consignment hitting two exceptions counts once; the rate is by parcel, not by event. | | **API endpoint** | Bring Tracking API `GET /tracking/v3/tracks/{consignmentNumber}` event stream. The card pattern-matches on `eventCode` against the curated exception code-set: `held_at_terminal`, `address_unknown`, `recipient_absent`, `delivery_attempted`, `customs_inspection`, `weather_delay`, `damaged_in_transit`, `lost_in_transit`, `incorrect_address`, `recipient_refused`. | | **Exception vs late** | An exception is an in-transit interruption; a late delivery is the outcome where the parcel arrived after promise. Most exceptions resolve and the parcel still delivers on-time (held-at-terminal often clears in 4 to 12 hours during peak). The relationship is leading-indicator, not equivalence. | | **Climate / weather codes** | The Bring tracking feed surfaces `weather_delay` codes during winter on northern Norwegian routes; these are real and the card includes them. Some merchants exclude weather-related exceptions from operational alerts because they are not actionable; the card reports the gross rate and lets the merchant filter at the alert layer. | | **Service-tier scope** | All tracked services with an event stream: Home Delivery Parcel, Pickup Parcel, Business Parcel, Cargo. Mail products and untracked services are excluded because they have no exception events to count. | | **Cross-Border partner exceptions** | For non-Nordic destinations the partner-carrier event feed is included where available. Partner feeds are noisier than Bring's own feed; the card normalises common partner codes (DHL `held_at_clearance`, PostNord `customs_clearance`) into the canonical Bring exception set. | | **Returns / RTO** | **Outbound only.** Return-leg exceptions are filtered. RTO volume is on [Returned to Sender](/nerve-centre/kpi-cards/bring/returned-to-sender). | | **Currency** | The card is a percentage. To value the exception tail, join with [Avg Shipping Cost](/nerve-centre/kpi-cards/bring/avg-shipping-cost) and an internal CS-cost-per-ticket assumption; an exception costs roughly the same as a late delivery in CS time. | | **Time window** | `30D vsP` (rolling 30 days, period-over-period). Daily readings are noisy below 200 consignments per day; weekly is the operational cadence. | | **Alert trigger** | `>3%`. Bring's network typically runs 0.5 to 1.5 percent exception rate domestic Norway, 1.5 to 3 percent Cross-Border Nordic, 3 to 6 percent rest-of-EU. The 3 percent trigger is calibrated to fire on Norwegian-domestic disruption, not on routine Cross-Border noise. | | **Sentiment key** | `{'type': 'gauge', 'thresholds': {'good': 1, 'warn': 3}}` | | **Roles** | owner, operations | ## Calculation Calculated automatically from your Bring data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading. ## Worked example The Drammen-based outdoor-apparel merchant, 15,300 trailing-30-day Bring consignments. Reading taken at 09:00 CET on 11 Mar 26 for the trailing 30 days (10 Feb 26 to 10 Mar 26). | Exception code | Count (distinct consignments) | % of period volume | Median resolution time | | -------------------------------------------- | ----------------------------- | ------------------ | ----------------------------------------------- | | `held_at_terminal` | 142 | 0.93% | 8 hours | | `recipient_absent` (Home Delivery only) | 98 | 0.64% | 22 hours (redelivered or moved to pickup point) | | `weather_delay` (northern routes) | 71 | 0.46% | 36 hours | | `address_unknown` | 44 | 0.29% | 48 hours (with merchant intervention) | | `customs_inspection` (Cross-Border) | 38 | 0.25% | 72 hours | | `delivery_attempted` (no answer at door) | 24 | 0.16% | 14 hours (collected next day) | | `damaged_in_transit` | 7 | 0.05% | 96 hours (claim filed) | | `lost_in_transit` | 3 | 0.02% | not resolved | | **Total exception consignments (this card)** | **427** | **2.79%** | **median 18 hours** | The dial reads **2.79 percent**; warn at `>3%` is not tripped, but the trend matters more than the level. Five things to notice: 1. **Held-at-terminal is the largest bucket and the most resolvable.** 142 consignments held at terminal usually means a sortation backlog at one or two specific facilities. If the bulk is at the Oslo Alfaset terminal, a quick peak-shift conversation with the Bring account team typically resolves it; if it is at a partner-handover terminal in Sweden or Denmark the resolution is slower. 2. **Recipient-absent is structural, not an issue.** 98 absent-recipient exceptions on Home Delivery is normal for residential Norway; recipients work, parcels go to pickup point, recipients collect within 48 hours. The healthy reading is around 0.5 to 1 percent of Home Delivery volume; this merchant's 1.3 percent is within range. 3. **Weather delay is seasonal noise to annotate, not act on.** 71 weather-delay exceptions in March is the tail end of winter; in July this category will read close to zero. Do not re-baseline the alert threshold for weather; instead note the seasonal pattern in the board commentary. 4. **Address-unknown is the merchant's problem, not Bring's.** 44 unknown-address exceptions usually trace back to the checkout flow: missing apartment numbers, unit numbers, postcode mismatches. Pair with [`shopify.checkout_address_validation`](/nerve-centre/shopify/checkout_address_validation) or equivalent, and consider a checkout address-validator if the count exceeds 0.4 percent. Each address-unknown exception costs roughly 25 to 45 minutes of CS time to resolve. 5. **Lost-in-transit is the small number that hurts most.** 3 lost-in-transit consignments at an average order value of 850 NOK each = 2,550 NOK of refund-or-reship liability, plus 3 angry customers and 3 negative reviews. Treat lost-in-transit as a separate dial; the [Open Claims](/nerve-centre/kpi-cards/bring/open-claims) card breaks these out and tracks claim-recovery time. ## Sibling cards merchants should reference together Exception Rate is a leading indicator. Pair it with these to read the signal: | Card | Why pair it with Exception Rate | What the combination tells you | | ------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | [On-Time Delivery Rate](/nerve-centre/kpi-cards/bring/on-time-delivery-rate) | The downstream outcome dial. | A 3-point exception-rate spike usually shows up as a 1 to 2 point OTD drop 24 to 72 hours later. If exceptions climb but OTD holds, the network is recovering exceptions inside the promise window (good news). | | [Late Shipments](/nerve-centre/kpi-cards/bring/late-shipments) | The downstream count. | Exception-to-late conversion is roughly 30 to 50 percent for Norwegian-domestic, 50 to 70 percent for Cross-Border. Multiply expected late by exception delta to forecast next week's late count. | | [Failed Deliveries](/nerve-centre/kpi-cards/bring/failed-deliveries) | The subset of exceptions that did not recover. | Most exceptions resolve and the parcel still delivers; the unresolved tail becomes a failed delivery, then potentially an RTO. | | [Open Claims](/nerve-centre/kpi-cards/bring/open-claims) | The recovery-and-money side. | Damaged-in-transit and lost-in-transit exceptions become claims; the dollar value sits on the claims card. | | [OTD by Route](/nerve-centre/kpi-cards/bring/otd-by-route) | Where the exceptions are concentrated. | A network-wide exception spike points to Bring; a route-concentrated exception spike points to a specific terminal or partner depot. | | Cross-connector: [`shopify.checkout_completion_rate`](/nerve-centre/shopify/checkout_completion_rate) | Upstream cause for `address_unknown` exceptions. | Checkout flows that do not validate address completeness leak into Bring as `address_unknown` exceptions; validating at checkout cuts this exception class by 60 to 80 percent. | | Cross-connector: [`gorgias.tickets_open`](/nerve-centre/gorgias/tickets_open) | Downstream impact. Exceptions drive WISMO and "where is my refund" tickets. | A 1-point exception-rate spike typically maps to a 12 to 18 percent ticket-volume increase at 24 to 72 hours lag. | | Cross-connector: [`klaviyo.transactional_email_delivery`](/nerve-centre/klaviyo/transactional_email_delivery) | Defensive comms. Proactive "your parcel had an issue" emails reduce ticket inflow. | Triggering a Klaviyo flow on Bring exception webhooks reduces customer-initiated WISMO tickets by 35 to 55 percent. | ## Reconciling against the vendor's own dashboard **Where to look in Bring's own portal:** [Mybring](https://www.mybring.com/) → **Statistics → Tracking Events**, then filter the event-code dropdown to the exception classes (held-at-terminal, address-unknown, recipient-absent, customs-inspection, weather-delay, damaged, lost). Mybring presents the data as an event count rather than as a per-consignment rate; the card normalises to per-consignment to avoid double-counting. **Why our number may legitimately differ from Mybring:** | Reason | Direction | Why | | ----------------------------------------- | ----------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Per-event vs per-consignment counting** | Mybring higher | Mybring's default view counts events; a single consignment hitting `held_at_terminal` then `delivery_attempted` then delivered counts as two events in Mybring and one consignment in the card. | | **Exception code curation** | Either | Bring's tracking feed has 60+ event codes; the card's exception set is curated to operationally meaningful breaks. Codes like `arrived_at_sortation_centre` are normal in-transit events and excluded. Mybring's exception view sometimes uses a different curated set. | | **Cross-Border partner code mapping** | Ours typically lower | Partner-carrier event feeds use carrier-specific codes; the card maps the major partners (DHL, PostNord, GLS) but unrecognised codes are not counted as exceptions. Mybring may over-count partner events. | | **Resolution-window deduplication** | Ours lower for active retries | If a consignment hits the same exception code twice (e.g. `delivery_attempted` on Tuesday and Wednesday), the card counts it once. Mybring may count both attempts. | | **Timezone (CET / CEST vs UTC)** | Boundary days off | Mybring reports in Oslo local time; the card stores in UTC. Across a 30-day window the boundary effect is below 0.05 percentage points. | **Cross-connector reconciliation:** | Card | Expected relationship | Causes of legitimate divergence | | ------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------- | | [`gorgias.tickets_open`](/nerve-centre/gorgias/tickets_open) | Exceptions feed CS tickets at 12 to 18 percent ticket-volume increase per 1-point exception-rate increase. | Not all tickets relate to Bring; not all Bring exceptions become tickets. Strong directional correlation, no exact identity. | | [`shopify.checkout_address_validation`](/nerve-centre/shopify/checkout_address_validation) | Upstream cause for address-unknown exceptions. | Checkout-side validation typo rates and the carrier-side `address_unknown` exception rate move together; not all merchants have an address validator deployed. | | [`postnord.pos_exception_rate`](/nerve-centre/kpi-cards/postnord/exception-rate) | Adjacent Nordic carrier exception rate for the same period. | Different carrier, different shipments; cross-compare to monitor both networks during winter or industrial-action incidents. | ***
Documentation cross-reference (for agencies running multiple shippers) Exception-rate metrics exist with conceptually similar definitions across other Nordic and EU carriers and 3PLs. These are not parallel measurements of the same shipments, they are independent operations. * [`postnord.pos_exception_rate`](/nerve-centre/kpi-cards/postnord/exception-rate) (Nordic peer) * [`deutsche_post.deu_exception_rate`](/nerve-centre/kpi-cards/deutsche-post/exception-rate) (German national-postal peer) * [`royal_mail.roy_exception_rate`](/nerve-centre/kpi-cards/royal-mail/exception-rate) (UK national-postal peer)
## Known limitations / merchant FAQs **Should I exclude weather delays from the alert threshold during winter?** Reasonable choice. Norwegian winter on northern routes (postcode 90xx and above) generates a structural 0.5 to 1.5 percent weather-delay exception rate from November through March. The card reports the gross rate; configure the alert at the integration layer to either (1) exclude `weather_delay` from the alert formula during winter months, or (2) raise the threshold from 3 percent to 4 percent for that window. Do not delete weather exceptions from the underlying data; they are real and you may want to comment on the customer-felt experience separately. **My exception rate is 4 percent and OTD is still 96 percent. Is this fine?** Probably yes. The relationship is leading-indicator, not equivalence. If exceptions are running 4 percent but resolving inside the promise window (sortation backlog cleared in 6 hours, recipient-absent collected next morning) the OTD dial is unaffected. Watch the trend: if exception rate keeps climbing while OTD stays flat, you are riding a recovery margin that will eventually exhaust. If OTD starts falling 24 to 72 hours after the exception spike, the recovery margin has run out. **A single warehouse error caused 200 address-unknown exceptions in one day. Is the dial broken?** The dial is reading reality. A label-data export bug or a checkout typo can produce a one-day spike. The card does not auto-smooth; configure your alert to trigger on a 7-day rolling rather than daily reading if one-day spikes are too noisy for your operations cadence. The underlying data should still be fixable: identify the affected consignments via the drill-down, contact Bring to update addresses (the parcels are usually still in network and re-deliverable), and patch the upstream cause. **Why does my Cross-Border exception rate read so much higher than my Norwegian-domestic rate?** Three structural reasons. (1) **Customs inspections.** EU + Norway is not a frictionless border for parcels above 350 NOK; customs inspections for non-EU origin (or non-Norway-EFTA exemptions) add 1 to 3 percentage points of `customs_inspection` exceptions. (2) **Partner-carrier hand-overs.** Each hand-over (Bring → PostNord → DHL last-mile) is an opportunity for a hand-over scan to fail or get logged as an exception. (3) **Address-format mismatches.** Norwegian, Swedish, Danish, and Finnish postcode formats differ; a checkout that does not validate per-country generates 0.5 to 2 percent extra address-unknown exceptions on cross-border. The fix for (1) is to ensure correct customs-data on the booking; the fix for (2) is structural and outside the merchant's control; the fix for (3) is a per-country-aware checkout validator. **Held-at-terminal keeps showing up. Should I worry?** Held-at-terminal is the most common exception code and usually the least concerning; it just means the parcel paused at a sortation facility. Concerning patterns: (1) consistently held at the same terminal more than 24 hours, suggesting a local capacity problem, (2) held-at-terminal on the same lane every Monday, suggesting a recurring weekend backlog, (3) held-at-terminal followed by lost-in-transit, suggesting the parcel actually went missing during the hold. Use the drill-down to identify the terminal pattern; raise it with your Bring account team if it is a single-facility issue. **Which exception codes should I treat as actionable vs ignorable?** Actionable (chase same-day): `damaged_in_transit`, `lost_in_transit`, `incorrect_address` (when paired with a high-value consignment), `recipient_refused`. Actionable (chase within 24 hours): `address_unknown`, `customs_inspection` exceeding 48 hours. Monitor only: `held_at_terminal`, `recipient_absent`, `delivery_attempted`, `weather_delay`. The alert threshold of 3 percent is calibrated to the actionable + monitor mix; if you split the alert into "actionable-only", set it lower (around 1 percent). **My CS team wants a webhook for new exceptions, not a periodic dashboard read. Is that supported?** Yes. Configure the Bring webhook integration to push exception events to your CS tool (Gorgias, Zendesk, etc.) with `eventCode IN exception_set` as the filter. Pair with [Klaviyo Transactional Email](/nerve-centre/klaviyo/transactional_email_delivery) to send a proactive customer email on the same trigger. The card itself reads from the same event stream; webhook + dashboard reads are consistent. **The dial dropped from 2.8 percent to 0.4 percent overnight. Did the network suddenly improve?** Probably not. Most overnight dial drops on this card are data-feed issues, not network improvements. Three things to check: (1) is the Bring tracking-API integration still authenticated (see [Days to Token Expiry](/nerve-centre/kpi-cards/bring/days-to-token-expiry)), (2) is the booking-API integration still posting (a missing booking flow means newer parcels are not in the denominator), (3) is there a consignment-number mismatch between booking and tracking (a recent service-code rename can break the join). If all three are healthy and the drop is real, double-check by comparing against [Late Shipments](/nerve-centre/kpi-cards/bring/late-shipments); the two should move in directionally consistent ways. **Is the 3 percent threshold suitable for a B2B-heavy merchant?** Mostly yes. Bring Business Parcel Bulk B2B has a structurally lower exception rate than residential (roughly 0.5 to 1 percent vs 1 to 2 percent for residential) because B2B receivers are at fixed addresses with goods-in operations. A B2B-heavy merchant might tighten the alert to 2 percent. A B2C-heavy merchant on Cross-Border is comfortably above 3 percent on a normal week and may need to loosen to 4 percent or split per-route. *** ### Tracked live in Vortex IQ Nerve Centre *Exception Rate* is one of hundreds of KPI pulses Vortex IQ tracks across Bring 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.