> ## 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.

# Shopline audit profile, Vortex IQ

> What the Vortex IQ Shopline health audit checks: Shopline: Token Health, Catalogue Drift & Cross-Channel Leak

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

Shopline is an APAC/US-rooted DTC ecommerce platform - sister of Shopify and BigCommerce, with a long-lived JWT bearer and region-pinned API hosts. Audits cover JWT/auth health (the silent-expiry trap that breaks order downloads without warning), catalogue & SEO completeness (variants missing SKUs, products missing descriptions), refund + fulfilment SLA (the merchant-trust signals), inventory hygiene, and cross-channel comparisons against Amazon / eBay / Ads / Email / Monitoring siblings to surface catalogue drift, OOS-with-active-spend, revenue-at-risk-from- incident, and email-attribution share.

## What this audit checks

### Authentication & access

* JWT bearer parses cleanly (HS512, payload contains appKey/sellerId/storeId/domain/exp)
* JWT exp claim > 30 days away (warn) / > 7 days (critical) - silent-expiry alarm
* Region credential matches JWT `domain` claim (us / apac / asean host alignment)
* Authorization header attaches as 'Bearer {token}' (NOT raw token - Shopline expects Bearer prefix unlike OnBuy)
* Validate-endpoint /admin/openapi/{api_version}/orders.json?limit=1 returns 200 with orders payload
* shop.json / account.json / merchants.json 404 expected - derive identity from JWT, not from /shop

### Catalogue & SEO completeness

* Products with empty body\_html (missing description) - free conversion lift
* Variants with no SKU populated >5% of catalogue (breaks marketplace + 3PL integrations)
* Products missing primary image (variants without media)
* Products in 'archived' status still showing on storefront
* Tag sprawl - top-10 tags account for \<40% of products (taxonomy decay)

### Order & fulfilment SLA

* Unfulfilled paid orders aged >48h (3PL/warehouse drag)
* Avg time-to-fulfil >36h (slow ops)
* Fulfillment rate \<90% on 30D vsP (broken shipping promises)
* Cancellation rate >3% (refund + rating impact)
* Partially-paid order count >5 outstanding (broken authorise-only flow)

### Refunds & customer trust

* Refund rate >5% on 30D vsP (product quality / expectation mismatch)
* Rolling 24h refund rate >2× 30D baseline (anomaly)
* Top refunding customers - concentrated repeat-refunder fraud signal
* Refund value as % of revenue >8% (margin destroyer)

### Inventory hygiene

* Zero/negative stock variants on active products (OOS but visible)
* Low-stock SKUs \<10 units across >5% of catalogue
* Days-of-cover \<7 on top-50 SKUs by velocity (stockout imminent)
* Inventory-feed staleness - updated\_at >24h on active variants

### Discount & margin discipline

* Discount % of revenue >25% sustained (promo dependency)
* Shipping cost as % of revenue >15% (subsidising delivery)
* AOV with discount vs without - gap >30% indicates margin cannibalisation

### Cross-channel: leak vs Amazon / Ads / Email / Monitoring (the killer area)

* Amazon revenue share >70% on top SKUs (platform-dependency risk)
* Catalogue drift - same SKU, Shopline vs Amazon price delta >20% or title/image mismatch
* Active ads on OOS Shopline SKUs - daily spend on variants with inventory\_quantity \<= 0
* Revenue at risk per minute during a connected Datadog/New Relic incident (>\$0 while incident open)
* Email-attributed revenue share \<15% (email under-utilised) OR drop >20% vsP
* Top-velocity Amazon UK SKUs missing entirely from Shopline catalogue (assortment gap)

## Severity thresholds

| Signal                        | Warn | Critical |
| ----------------------------- | ---- | -------- |
| `jwt_days_to_expiry`          | 30   | 7        |
| `unfulfilled_orders_aged_48h` | 5    | 20       |
| `avg_fulfilment_hours`        | 24   | 36       |
| `fulfillment_rate_pct`        | 92   | 90       |
| `cancellation_rate_pct`       | 2    | 3        |
| `partial_paid_count`          | 5    | 15       |
| `refund_rate_pct`             | 3    | 5        |
| `refund_spike_multiplier`     | 1.5  | 2        |
| `refund_value_pct_of_revenue` | 5    | 8        |
| `oos_active_variant_count`    | 1    | 10       |
| `low_stock_pct_of_catalogue`  | 3    | 5        |
| `days_of_cover_top_skus`      | 14   | 7        |
| `inventory_staleness_hours`   | 12   | 24       |
| `missing_descriptions_count`  | 1    | 10       |
| `sku_coverage_pct`            | 97   | 95       |
| `discount_pct_of_revenue`     | 20   | 25       |
| `shipping_pct_of_revenue`     | 12   | 15       |
| `amazon_revenue_share_pct`    | 10   | -        |
| `catalogue_drift_count`       | 5    | 10       |
| `ads_on_oos_daily_spend`      | 1    | 25       |
| `email_revenue_share_pct`     | 15   | 10       |
| `consecutive_auth_failures`   | 1    | 3        |

## Data sources

* `GET https://sl-open-{region}.myshopline.com/admin/openapi/{api_version}/orders.json` - Auth probe + revenue/refund/fulfilment context (limit=1 = cheapest validate)
* `GET https://sl-open-{region}.myshopline.com/admin/openapi/{api_version}/products.json` - Catalogue completeness + SKU coverage + slow-mover detection
* `GET https://sl-open-{region}.myshopline.com/admin/openapi/{api_version}/customers.json` - Customer count + repeat rate + top-spender concentration
* `GET https://sl-open-{region}.myshopline.com/admin/openapi/{api_version}/inventory_levels.json` - OOS + low-stock + days-of-cover
* `GET https://sl-open-{region}.myshopline.com/admin/openapi/{api_version}/refunds.json` - Refund-rate spike detection + top refunders