> ## 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.

# Big Cartel audit profile, Vortex IQ

> What the Vortex IQ Big Cartel health audit checks: Big Cartel: Catalogue Hygiene, Refund Trust & Cross-Channel Leak

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

Big Cartel is a hosted commerce platform for artists, makers, musicians, and small indie brands - deliberately narrow (small catalogues, low/free fees, fast time-to-live). Merchants run lean with no analyst and no BI seat, so the audit focuses on the executive pulse the built-in reports miss: OAuth token health, catalogue + image/description completeness, sold-out / out-of-stock hygiene against the plan product cap, refund-rate spikes (the product-trust signal), order/fulfilment SLA, and cross-channel comparisons against Ad / Email / Website-performance siblings to surface ad-spend-on-OOS, email-attribution share, and slow-PDP cart loss.

## What this audit checks

### Authentication & access

* OAuth2 bearer token present and attaches as 'Bearer {token}'
* account\_id resolves - /v1/accounts/{account_id} returns 200 with the store profile
* Token scope includes read access to products / orders / customers (no 403 on resource reads)
* Validate probe /v1/accounts/{account_id} is the cheapest auth check (single account object)
* Plan tier readable - plan\_name + product\_limit present for plan-cap signals

### Catalogue & image completeness

* Products with zero images (image\_count = 0) - convert poorly, free lift to fix
* Products with empty description - SEO + conversion drag, AI-fill candidate
* Sold-out products still listed on the storefront (status = sold-out) - quiet revenue leaks
* Active product count vs plan product\_limit > 90% - upgrade-or-delist pressure
* Draft / hidden products lingering >30d (abandoned listings)

### Inventory hygiene

* Tracked products at zero stock (total\_stock \<= 0) on active listings (OOS but visible)
* Low-stock tracked products below reorder threshold across the catalogue
* Recent bestseller now sold-out (top-velocity SKU transitioned to status=sold-out)
* Stale inventory - active product updated\_at > 90d (likely dead listing)

### Refunds & customer trust

* Refund rate > 5% on 30D vsP (product-quality / expectation mismatch)
* Rolling 24h refund rate > 2x 30D baseline (anomaly spike)
* Cancellation rate > 3% (stock or expectation problem)
* Concentrated repeat-refunder - single customer with multiple refunds (fraud / dissatisfaction signal)

### Order & fulfilment SLA

* Pending orders aged > 24h (payment-gateway hiccup or manual-review drag)
* Paid-but-unshipped orders aged > 48h (broken shipping promise)
* Avg time-to-ship > 72h on 30D vsP (slow ops for a hand-packed maker)
* Order volume drop > 20% vsP without a known cause (silent acquisition fall)

### Cross-channel: leak vs Ads / Email / Website-performance (the killer area)

* Active ad spend on sold-out / OOS Big Cartel products - daily spend on products that can't convert
* Email-attributed revenue share \< 15% (email under-utilised) OR drop > 20% vsP when an email tool is connected
* High-value customers (top-spend P90) unengaged on email > 90d - win-back opportunity
* Top-velocity products with LCP > 4s on a connected website-performance source (slow PDP → cart loss)

## Severity thresholds

| Signal                          | Warn | Critical |
| ------------------------------- | ---- | -------- |
| `products_no_image_count`       | 1    | 10       |
| `products_no_description_count` | 1    | 10       |
| `sold_out_listed_count`         | 1    | 5        |
| `plan_product_usage_pct`        | 90   | 100      |
| `oos_tracked_count`             | 1    | 10       |
| `low_stock_count`               | 1    | 10       |
| `inventory_staleness_days`      | 60   | 90       |
| `refund_rate_pct`               | 3    | 5        |
| `refund_spike_multiplier`       | 1.5  | 2        |
| `cancellation_rate_pct`         | 2    | 3        |
| `pending_orders_aged_24h`       | 3    | 15       |
| `unshipped_paid_aged_48h`       | 5    | 20       |
| `avg_time_to_ship_hours`        | 48   | 72       |
| `order_volume_drop_pct`         | 15   | 20       |
| `shipping_pct_of_revenue`       | 12   | 15       |
| `ads_on_oos_daily_spend`        | 1    | 25       |
| `email_revenue_share_pct`       | 15   | 10       |
| `high_value_unengaged_count`    | 3    | 5        |
| `slow_pdp_top_product_count`    | 1    | 3        |

## Data sources

* `GET https://api.bigcartel.com/v1/accounts/{account_id}` - Auth probe + plan tier + product\_limit + currency (cheapest validate)
* `GET https://api.bigcartel.com/v1/accounts/{account_id}/products` - Catalogue completeness + image/description coverage + sold-out + stock hygiene
* `GET https://api.bigcartel.com/v1/accounts/{account_id}/orders` - Revenue + refund-rate spike + fulfilment SLA + country mix
* `GET https://api.bigcartel.com/v1/accounts/{account_id}/customers` - Customer count + repeat rate + top-spender concentration