> ## 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. # Out-of-Stock Products, ShipBob > Out-of-Stock Products for ShipBob 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:** [Fulfilment & Logistics](/nerve-centre/connectors#connectors-by-type) ## At a glance > Live count of SKUs with zero or negative on-hand inventory across all ShipBob DCs, scoped to SKUs with measurable recent demand (no point alerting on dead-SKU stockouts). The "what is missing right now and customers want it" number for ops and merchandising. | | | | ----------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **What it counts** | `COUNT(DISTINCT sku WHERE SUM(on_hand_qty across all DCs) <= 0 AND demand_30d > demand_threshold)`. Each unique SKU counts 1, regardless of how deeply OOS or how many DCs are dry. | | **API endpoint** | `GET /inventory` (Inventory API). Reads `on_hand_quantity` and `available_quantity` per SKU per DC; the card sums across DCs to determine network-wide OOS. | | **DC scope** | **Aggregated across every DC** for OOS determination. A SKU is OOS only when zero across the whole network; if Chicago has stock and Cincinnati does not, the SKU is in-stock for the merchant (multi-DC routing handles it). Per-DC view in [Inventory by Warehouse](/nerve-centre/kpi-cards/shipbob/inventory-by-warehouse). | | **Shipping-method scope** | Not applicable, this is an inventory metric. | | **Inventory-split semantics** | A SKU is "in stock" if any DC has it; the card counts SKUs that are zero everywhere. Single-DC stockouts (one DC dry, another full) appear in [Inventory Heatmap](/nerve-centre/kpi-cards/shipbob/inventory-distribution-heatmap), not here. | | **Perfect-order definition** | Stockouts at order-time block fulfilment, which fails on-time-shipping, which fails perfect-order. The OOS card is one upstream cause of the perfect-order leg. | | **SLA definition** | Not directly applicable, but related: a SKU OOS at order-time creates an "on-hold" order until restocked, which guarantees an SLA miss. The card surfaces the at-risk SKUs before orders queue against them. | | **Peak-period seasonality** | **Q4 typically inflates OOS count by 2 to 5 times steady-state.** Volume spikes outpace supply-chain lead times; viral or sale-driven SKU spikes deplete fastest-moving SKUs in days. December typically sees 5 to 15 OOS at any moment for a 200-SKU brand. | | **API rate limits** | 200 requests / minute / token. Inventory API is webhook-driven via `inventory.updated` events; the card refreshes within seconds of stock movement. | | **Returns / RTO** | Excluded for the OOS calculation (returned items take 2 to 7 days to be re-received and re-stocked, during which they do not contribute to on-hand). | | **Time window** | `RT` (real-time, computed from latest indexed inventory snapshot) | | **Alert trigger** | `any OOS`, the `stockout_with_demand` sentiment trips when ANY SKU with measurable demand goes to zero. The threshold can be adjusted (e.g. ignore SKUs with \<10 sales/30D). | | **Roles** | owner, operations, marketing | ## Calculation Calculated automatically from your ShipBob 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 DTC supplements brand using ShipBob 3PL with 3 DCs and a 180-SKU catalogue. Reading taken at 09:00 ET on 12 Mar 26. | SKU | Top status | 30D demand (units) | Days since OOS network-wide | Note | | ---------------- | ------------------------------- | ------------------ | ----------------------------------- | ----------------------------------- | | MAGNESIUM-500 | OOS in CHI, MOV, CIN | 1,840 | 2 days | Top-3 SKU; replenishment ETA 9 days | | ASHWAGANDHA-30CT | OOS in MOV; in stock at CHI 320 | 920 | 0 (single-DC OOS, not in this card) | Multi-DC routing handles | | OMEGA-3-90CT | OOS in CHI, MOV, CIN | 720 | 4 days | Mid-tier; replenishment ETA 14 days | | VITAMIN-D3-60CT | OOS in CIN; in stock at CHI 80 | 280 | 0 (single-DC OOS, not in this card) | Multi-DC routing handles | | BIOTIN-90CT | OOS in CHI, MOV, CIN | 22 | 18 days | Long-tail SKU, low priority | | PROBIOTIC-30CT | OOS in CHI, MOV, CIN | 480 | 1 day | Mid-tier; replenishment ETA 6 days | The card reads **4** OOS SKUs (MAGNESIUM-500, OMEGA-3-90CT, BIOTIN-90CT, PROBIOTIC-30CT) network-wide. Five things to notice: 1. **Single-DC OOS is hidden by design.** Ashwagandha and Vitamin D3 are out at one DC each but in stock elsewhere; ShipBob's routing engine sends Ashwagandha orders to Chicago and Vitamin D3 orders to Chicago, so customers see "in stock" and orders ship cleanly. The card counts only network-wide OOS to surface customer-facing problems, not warehouse-floor curiosities. Pivot to [Inventory Heatmap](/nerve-centre/kpi-cards/shipbob/inventory-distribution-heatmap) to see single-DC OOS for restocking decisions. 2. **The Magnesium-500 and Probiotic-30CT lines are the bleeding ones.** Top-3 SKUs combined 30D demand is 2,320 units; with 9- and 6-day replenishment lead times, the merchant will lose roughly 110 + 95 = 205 sales over the gap (assuming demand continues at trend). At AOV $58 and 1.4 items / order, that is roughly $5,500 of unrealised revenue. 3. **BIOTIN at 22 units / 30D is tagged but not urgent.** The card surfaces it (network-wide OOS, demand exists) but a 22-unit SKU is not a priority. Configure a higher demand threshold (e.g. 50 units / 30D) to filter this out and reduce alert noise. 4. **Q4 inflates this card structurally.** This same brand's 5 Dec 25 reading was 12 OOS SKUs (vs steady-state 2 to 4); Black Friday and Cyber Monday volume cleared three of their top-10 SKUs in 36 hours. Read peak readings in seasonal context; pre-stock 6 to 8 weeks ahead. 5. **The card is a leading indicator for [Operational Health Score](/nerve-centre/kpi-cards/shipbob/operational-health-score).** OOS feeds the inverse-stockout-severity pulse; a climbing OOS count drops the composite within hours. The card is also a leading indicator for [Pending Backlog](/nerve-centre/kpi-cards/shipbob/pending-fulfilment-backlog), since OOS-held orders accumulate. ## Sibling cards merchants should reference together OOS is the surface; ageing and demand work happens in supporting cards: | Card | Why pair it with Out-of-Stock Products | What the combination tells you | | --------------------------------------------------------------------------------------------------- | -------------------------------------------------- | -------------------------------------------------------------------------------------------------- | | [Inventory by Warehouse](/nerve-centre/kpi-cards/shipbob/inventory-by-warehouse) | Per-DC stock levels. | Shows whether single-DC OOS exists for SKUs in this card; informs routing-vs-restock decisions. | | [Stock vs Demand](/nerve-centre/kpi-cards/shipbob/stock-vs-demand-forecast) | Demand-weighted view. | Surfaces SKUs at risk of going OOS in 7 to 14 days (early warning), not just those already gone. | | [Inventory Heatmap](/nerve-centre/kpi-cards/shipbob/inventory-distribution-heatmap) | DC-by-SKU stock matrix. | Visual identification of single-DC OOS that the headline OOS count hides. | | [Inventory Ageing](/nerve-centre/kpi-cards/shipbob/inventory-ageing) | Time-in-stock per SKU. | Old inventory signals over-buying; OOS signals under-buying. Pair to right-size purchase orders. | | [Operational Health Score](/nerve-centre/kpi-cards/shipbob/operational-health-score) | Composite that includes inverse-stockout-severity. | OOS climb drops the composite within hours; the relationship is direct. | | [Pending Fulfilment Backlog](/nerve-centre/kpi-cards/shipbob/pending-fulfilment-backlog) | OOS-held orders accumulate in backlog. | Climbing OOS predicts climbing on-hold orders within hours. | | Cross-connector: [`shopify.unfulfilled_orders`](/nerve-centre/kpi-cards/shopify/unfulfilled-orders) | Customer-side OOS impact. | OOS at ShipBob causes Shopify orders to either be PARTIALLY\_FULFILLED or held; correlated metric. | | Cross-connector: [`shopify.refund_rate`](/nerve-centre/kpi-cards/shopify/refund-rate) | Downstream impact at 7 to 14 days. | Sustained OOS drives customer-cancel-and-refund. | | Cross-connector: customer NPS surveys | Downstream sentiment, lag 14 to 30 days. | Customers complain loudly about OOS in surveys; correlates with sustained OOS readings. | ## Reconciling against the vendor's own dashboard **Where to look in ShipBob Merchant Portal:** [ShipBob Merchant Portal](https://merchant.shipbob.com/) → **Inventory → Stock Status → Filter "Out of Stock"**. The portal shows per-SKU per-DC inventory levels with on-hand, reserved, available quantities. The closest like-for-like view is "Out of Stock at All DCs". **Why our number may legitimately differ from ShipBob's portal:** | Reason | Direction | Why | | ----------------------------------------------------- | ------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Timezone (UTC default)** | Negligible | Real-time card; timezone affects only the demand-window denominator, not the OOS calculation itself. | | **DC-level vs aggregated reporting** | Aggregated by definition | The card counts network-wide OOS only; portal can show per-DC OOS. Numbers diverge by definition. | | **SLA definition variance (demand-threshold filter)** | Either | The card filters by recent demand (default >5 sales / 30D); portal shows all OOS. Brands with long-tail SKUs see lower numbers in the card. | | **Peak-period batch-processing delays** | Ours lower briefly | Inventory webhook lag of 1 to 5 minutes during normal operation; up to 30 minutes during BFCM. T-1-hour fully reconciles. | | **Reserved stock treatment** | Either | Portal sometimes counts "reserved for in-flight orders" as in-stock; the card uses `available_quantity` (on-hand minus reserved) by default. Configurable. | **Cross-connector reconciliation:** | Card | Expected relationship | What causes legitimate divergence | | ---------------------------------------------------------------------------------- | --------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- | | [`shopify.unfulfilled_orders`](/nerve-centre/kpi-cards/shopify/unfulfilled-orders) | OOS-held orders flow into Shopify unfulfilled. ShipBob lag of 2 to 6 hours. | Shopify orders for OOS SKUs may be allowed at checkout (continue-selling-when-OOS toggle), creating Shopify unfulfilled count without ShipBob being able to ship. | | Shopify product inventory | Storefront catalogue. | Shopify product inventory counts are typically synced from ShipBob; differences indicate sync lag or in-flight reservations. | | Amazon FBA OOS | Peer 3PL with its own inventory. Independent population. | Different SKUs allocated to FBA vs ShipBob; not reconciled. | | Customer NPS / out-of-stock complaints | Downstream sentiment, lag 14 to 30 days. | Survey response bias; complaints peak when sustained OOS exceeds 7 to 14 days on top-tier SKUs. | ***
Documentation cross-reference (for agencies running multiple 3PLs) OOS / stockout count exists on every 3PL platform with conceptually similar definitions. These are independent inventory pools on different SKUs; the cross-link exists so multi-3PL agencies can navigate documentation. * Amazon FBA inventory health * Shopify Fulfillment Network historical OOS report (legacy)
## Known limitations / merchant FAQs **ShipBob vs FBA, can I see OOS across both?** Each 3PL holds its own inventory pool; the SKUs allocated to FBA are not visible to ShipBob and vice-versa. Track each separately. The all-up "what is OOS in my catalogue" view sits in Shopify's product inventory, which usually reconciles from both sources but with sync lag. **How does ShipBob choose which DC to deplete first?** The router picks the closest DC with stock. If Chicago has 100 units and Cincinnati has 200, Chicago depletes first for Chicago-area orders. Different SKUs deplete at different rates per DC; the [Inventory Heatmap](/nerve-centre/kpi-cards/shipbob/inventory-distribution-heatmap) shows the matrix. **SLA-vs-carrier-tracking discrepancy, why does OOS make late deliveries worse?** A SKU OOS at order-time creates an "on-hold" order. The order waits for restock (days to weeks), then ships when stock arrives. Customer expectation set in checkout was 3 to 5 days; actual delivery may be 14+ days. This guarantees an SLA miss and a likely return-and-cancel. **Perfect-order rate vs OOS, what is the relationship?** Stockouts at order-time block fulfilment, which fails on-time-shipping (one perfect-order leg) and often cascades to late delivery (another leg) and customer cancellation (a return-leg miss). OOS is the upstream cause; perfect-order is the downstream consequence. **How do I plan for Q4 / BFCM peak using OOS?** Three actions. (1) Pre-stock 6 to 8 weeks before BFCM with 1.5 to 2 times normal levels for top-20 SKUs. (2) Set the demand-threshold filter to surface only top-tier SKUs (e.g. >50 sales / 30D) during peak to focus attention. (3) Set the alert threshold tighter on top-3 SKUs and looser on long-tail to reduce alert fatigue. **Multi-DC inventory split optimisation, how does OOS guide it?** This card surfaces network-wide OOS; the [Inventory Heatmap](/nerve-centre/kpi-cards/shipbob/inventory-distribution-heatmap) shows single-DC OOS. If one DC consistently runs dry on the same SKU while another holds excess, your inventory split is mis-aligned with customer geography. Re-allocate per the portal's "Inventory Distribution" recommendations. **Returns, do they immediately re-add to OOS?** No, with lag. A return takes 2 to 7 days from received-at-DC to be inspected, re-stocked, and counted as available inventory. During that window, the SKU appears OOS even though physical units exist on the DC floor. Pivot to [Return Processing Time](/nerve-centre/kpi-cards/shipbob/return-processing-time). **Why does ShipBob show OOS but Shopify still allows the order?** Shopify's "continue selling when out of stock" toggle. If enabled, customers can place orders for OOS SKUs; the order arrives at ShipBob and is held until restock. This is intentional for backorder workflows but causes confusion if not communicated to customers in checkout. **Why does the count flicker between values within an hour?** Inventory updates are webhook-driven; each shipment-out and return-in fires an event. A 200-SKU brand can see 5 to 15 inventory events per minute during peak. The count flickers as SKUs cross the OOS boundary back and forth on individual unit movements. The 30-minute rolling average is more useful for monitoring than the live count. *** ### Tracked live in Vortex IQ Nerve Centre *Out-of-Stock Products* is one of hundreds of KPI pulses Vortex IQ tracks across ShipBob 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.