> ## 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.

# ShippyPro audit profile, Vortex IQ

> What the Vortex IQ ShippyPro health audit checks: ShippyPro: Label Generation, Rate-Shop Consistency & Cross-Channel Leak

**[Nerve Centre KPIs](/nerve-centre/kpi-cards/shippy-pro) · [Audit Profile](/nerve-centre/kpi-cards/shippy-pro/audit) · [Sentiment Settings](/nerve-centre/kpi-cards/shippy-pro/sentiment)**

ShippyPro is a European shipping aggregator with rate-shopping across multiple sub-carriers. CloudHub probe shows 1 active merchant on bearer- token auth (BaseUrl [www.shippypro.com/api/v1](http://www.shippypro.com/api/v1)). Findings either lose money (label-generation failures = orders blocked) or hide carrier mistakes. Cross-references commerce siblings via order\_ref; sub-carrier shipments via parent\_consignment.

## What this audit checks

### Authentication & access

* Bearer token still valid (no 401 on /account)
* Token re-issuance via login email + password works on expiry
* Sandbox vs production base URL flagged correctly

### Label generation & rate-shop

* Label-generation success \< 98% rolling 24h
* Rate-shop winner consistency: top-carrier share volatility > 20% WoW
* Address-validation failure rate > 2%
* Manifest gap (LabelPrinted >24h with no OnManifest event) > 0.5%

### Sub-carrier consolidation health

* Single-sub-carrier dependency > 80% (defeats consolidation point)
* Sub-carrier OTD spread > 10pp
* New sub-carrier added without OTD baseline established

### International cross-border lanes

* Cross-border (destination != origin) exception rate > 5%
* Customs-held parcels > 1%
* EU mainland transit time > 5 days (cross-border lane stretch)

### Exceptions, claims & cost

* Exception rate > 3% rolling 30D
* Open claims unresolved > 7 days
* Avg cost / shipment up >10% vs prior period
* Claim value as % of ShippyPro revenue > 2% rolling 90D

### Cross-channel: revenue at risk (the kill-shot area)

* Cross-channel: late shipments joined to commerce\_sibling orders -> revenue at risk per channel
* Cross-channel: open claims with no Jira tracker\_item -> CS coverage gap
* Cross-channel: customs-held cross-border parcels -> proactive merchant-IOSS-fix candidates
* Cross-channel: rate-shop loser carriers correlated with poor OTD -> exclusion candidates

## Severity thresholds

| Signal                               | Warn | Critical |
| ------------------------------------ | ---- | -------- |
| `on_time_delivery_rate`              | 95   | 90       |
| `label_generation_success_pct`       | 99   | 98       |
| `rate_shop_volatility_pct`           | 15   | 20       |
| `address_validation_fail_pct`        | 1    | 2        |
| `customs_hold_pct`                   | 0.5  | 1        |
| `exception_rate`                     | 2    | 3        |
| `open_claims_age_days`               | 7    | 14       |
| `shipping_cost_per_order_change_pct` | 5    | 10       |
| `sub_carrier_concentration_pct`      | 70   | 80       |
| `claim_value_pct_of_revenue`         | 1    | 2        |
| `auth_token_failures_24h`            | 1    | 5        |

## Data sources

* `GET https://www.shippypro.com/api/v1/account` - Auth probe + account metadata
* `GET https://www.shippypro.com/api/v1/shipments` - Shipment list + label-gen success
* `GET https://www.shippypro.com/api/v1/tracking/{shipment_id}` - Tracking events
* `GET https://www.shippypro.com/api/v1/rates` - Rate-shop quote analysis