Sell-Through Rate (FBA), Amazon Seller Central

Sell-Through Rate (FBA) for Amazon Seller Central. Tracked live in Vortex IQ Nerve Centre. How to read it, why it matters, and how to act on it.

Metrics type: Supporting Metrics • Category: Inventory Forecasting

At a glance

How fast your FBA inventory turns. Sell-through compares units sold to the average units held over the period, so it tells you whether stock is moving at a healthy clip or sitting in Amazon’s warehouses racking up storage fees. It is the metric behind Amazon’s own Inventory Performance Index (IPI): low sell-through means overstock, capital tied up, and long-term storage exposure; very high sell-through means you are flirting with stockouts. The card flags SKUs turning at less than half the category norm.

What it measures	Units sold over the period divided by the average FBA units on hand over the same period, a turnover ratio. Higher means inventory is moving quickly; lower means it is sitting.
Why it matters	Slow sell-through is the root of overstock costs: storage fees, long-term storage surcharges, stranded capital, and a weak IPI that can trigger storage limits. Fast sell-through risks the opposite, stocking out and losing rank.
Link to IPI	Sell-through and excess inventory are core inputs to Amazon’s Inventory Performance Index. A persistently low sell-through drags IPI down, which can cap how much you are allowed to send into FBA.
FBA-specific	This is an FBA card because FBA is where the storage clock runs. FBM stock sits in your own warehouse on your own cost basis, so the Amazon-fee consequence does not apply the same way.
Benchmark, not absolute	”Good” sell-through is category-dependent. The alert is relative: a SKU below half the category median is turning too slowly regardless of the absolute number.
Action when low	Reduce inbound, run a promotion or coupon, lower price, bundle, or create a removal order before long-term storage fees bite.
Time window	90D (the selected period)
Alert trigger	<0.5x category median, turning at under half the category norm
Roles	owner, operations, finance

Calculation

Calculated automatically from your Amazon Seller Central 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 toys-and-games FBA seller reviewing 90D sell-through on 01 May 26. Assume the category median sell-through for the period is about 1.5x. Figures are illustrative.

SKU	Units sold (90D)	Avg units on hand	Sell-through	vs category median (1.5x)	Read
Hot seller A	5,400	1,800	3.0x	2.0x median	turning fast, watch for stockout
Steady B	2,700	1,800	1.5x	at median	healthy
Slow C	600	1,500	0.4x	0.27x median	alert: overstocked
Dead D	90	1,200	0.075x	0.05x median	alert: severe overstock, plan removal

Category median ≈ 1.5x ; alert threshold = below 0.5 × 1.5 = 0.75x
Slow C  =  0.4x   →  below 0.75x, flagged. ~3 months of stock barely moving.
Dead D  =  0.075x →  far below; this is capital frozen and a storage-fee liability. Plan a removal/markdown.
Hot A   =  3.0x   →  excellent turnover, but watch cover so it does not stock out.

Four things to notice:

1. Low sell-through is money sitting still. Dead D turned only 90 units against 1,200 average on hand over a full quarter. That is frozen capital and a growing storage bill. The fix is markdown, bundle, or removal, not “wait and see”, because long-term storage surcharges escalate the longer it sits. See ASINs Approaching Long-Term Storage.
2. The benchmark is relative, not absolute. A 0.4x sell-through might be fine in a slow-moving category and a disaster in a fast one. The alert fires on under half the category median, which is why Slow C is flagged at 0.4x against a 1.5x norm but would not be in a category that naturally turns at 0.5x.
3. Very high sell-through is a different risk. Hot A’s 3.0x is great for cash and IPI, but it is the SKU most likely to stock out. Pair high sell-through with Days of Cover (avg) and Replenishment Recommendations so a fast turner does not run dry.
4. This feeds your IPI and your storage limits. Persistent low sell-through across the catalogue drags Amazon’s Inventory Performance Index down, which can restrict how much you are allowed to send in. Sell-through is not just a margin metric, it gates your ability to operate FBA at scale.

Sibling cards merchants should reference together

Sell-through is the turnover read. These cover the cost of getting it wrong in either direction:

Card	Why pair it with Sell-Through Rate (FBA)
Days of Cover (avg)	The flip side. High sell-through plus low cover means stockout risk; low sell-through plus high cover means overstock.
Stranded Inventory Value	Where chronically low sell-through ends up, capital stuck in stock that will not move.
ASINs Approaching Long-Term Storage	The escalating fee consequence of slow sell-through; act before stock ages into the surcharge.
FBA Storage Fees	The running cost of holding slow-moving stock. Low sell-through inflates this.
Replenishment Recommendations	Uses velocity to right-size reorders so you do not recreate the overstock.
ASINs Stocking Out <7 Days	The high-sell-through hazard, fast turners running out.

Reconciling against Amazon Seller Central

Where to look in Seller Central:

The closest Amazon-native views are:

Inventory → Inventory Planning → Inventory Performance Dashboard (IPI, sell-through, excess inventory), and Reports → Fulfilment → Inventory reports for units on hand and units sold per SKU.

Amazon’s Inventory Performance Dashboard publishes a sell-through figure and the IPI it feeds. Expect this card’s per-SKU sell-through to track Amazon’s account-level figure in spirit, though the exact ratio depends on the averaging method and window each tool uses.

Timing, settlement, and reporting-lag table:

Topic	Detail
Average-inventory method	Sell-through depends on how average units on hand is computed (start/end average vs daily average over the window). Different methods give slightly different ratios; Amazon’s IPI uses its own method.
Window length	The ratio scales with the window. A 90D sell-through is not directly comparable to a 30D one. Compare like windows.
Available vs total	Whether reserved and unfulfillable units are included in “on hand” affects the denominator. Stranded units in the denominator depress the ratio.
Reporting lag	Inventory snapshots and sales settle on slightly different schedules, so the freshest ratio can move as the latest data finalises.

Why our number may legitimately differ from Seller Central:

Reason	Direction	Why
Averaging method	Either direction	Start/end vs daily-average inventory produces different denominators and therefore different ratios.
Window mismatch	Scales with window	A 90D ratio differs from Amazon’s default IPI window; align periods before comparing.
Stranded units in denominator	Ours may read lower	Including unfulfillable stock in on-hand depresses sell-through; excluding it raises it.
Category-median basis	Judgement	The “category median” benchmark is an estimate of the norm, not an official Amazon figure.

Cross-connector reconciliation against other connectors the same seller may run:

Card	Expected relationship	What causes legitimate divergence
amazon.days_of_cover_avg	Inverse-ish relationship. High sell-through tends to mean low days of cover and vice versa, both built from velocity and on-hand stock.	They diverge when inventory is lumpy (a big inbound shipment) because cover is forward-looking while sell-through is backward-looking.
shopify inventory turnover	Same concept, different cost basis. DTC stock turnover matters for cash but has no Amazon storage-fee or IPI consequence.	If stock is pooled across channels, reconcile total on-hand; if separate, the two are independent.

Known limitations / merchant FAQs

What is a good sell-through rate? There is no universal number, it is category-dependent. A fast-moving consumable turns far quicker than a niche durable. That is why the alert is relative (below half the category median) rather than a fixed threshold. Read your SKUs against their category, not against each other.

Why is this FBA-only? Because FBA is where Amazon’s storage clock and Inventory Performance Index apply. Slow FBA stock costs you storage fees, long-term surcharges, and IPI points that can cap your inbound. FBM stock sits on your own cost basis without those specific Amazon consequences, so the metric means something different there.

How does sell-through affect my IPI and storage limits? Sell-through and excess inventory are core IPI inputs. A persistently low sell-through drags IPI down, and a low IPI can restrict how much inventory Amazon lets you send into FBA. So slow turnover does not just cost storage fees, it can throttle your whole FBA operation.

My sell-through is very high, isn’t that good? Mostly, it means great turnover and healthy cash. But it is also the SKU most likely to stock out. Pair high sell-through with Days of Cover (avg) so a fast turner does not run dry and surrender rank and Buy Box.

Why doesn’t my number match Amazon’s dashboard exactly? Different averaging methods and window lengths. Amazon’s IPI uses its own calculation of average inventory and its own window. Both are valid; align the period and treat the card’s per-SKU view as the actionable, more granular read.

What do I do about a chronically low sell-through SKU? Stop sending more in, then move the existing stock: a coupon or price cut, a bundle, advertising, or, if it truly will not sell, a removal order before long-term storage fees escalate. Check ASINs Approaching Long-Term Storage for the deadline.

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Tracked live in Vortex IQ Nerve Centre

Sell-Through Rate (FBA) is one of hundreds of KPI pulses Vortex IQ tracks across Amazon Seller Central 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.

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