Amazon Inventory Replenishment Service — Forecasting & FBA Restock Automation
A replenishment engine that decides what to ship, when, and how much — before the stockout, not after.
If you're dealing with...
- Stocking out of your best sellers while slow movers sit at 200 days of supply
- Restock decisions made in a spreadsheet that was accurate three weeks ago
- FBA restock recommendations from Amazon that ignore your lead times and margins
- Merchant-fulfilled demand that never makes it into your reorder math
- Two SKUs sharing the same warehouse stock, and one of them always starves
- Purchase orders sized by gut feel instead of velocity and cover targets
- Reorder plans that treat a relabeled SKU as a brand-new product with zero history
The Real Cost of Bad Replenishment
Stockouts don’t just cost you the sales you missed. They reset your organic ranking, hand the Buy Box to a competitor, and force you to spend on PPC to buy back the position you already owned. Overstock is quieter but just as expensive: capital locked in slow movers, long-term storage fees, and aged inventory surcharges eating the margin on everything else.
Most brands manage this with a spreadsheet that somebody updates when they remember to. The velocity numbers are three weeks old. The lead times are guesses. Merchant-fulfilled demand isn’t in the model at all. And when two SKUs share the same warehouse stock, whichever one got reordered first wins and the other starves.
Our amazon inventory replenishment service replaces that with an engine that recalculates the entire catalog on every cycle and outputs one thing: a concrete, executable plan for what to ship and what to order.
How the Replenishment Engine Works
Restock triggers that watch the right number. The metric that matters for FBA is FBA-side cover: units available plus units already inbound, divided by daily velocity. When that drops below the trigger — typically 60 days — the SKU enters the ship plan and gets shipped up to a 90-day target. Warehouse stock and open POs never gate this decision. Plenty of brands have 300 days of “total supply” sitting in a warehouse while their FBA listing goes dark. Total pipeline is a purchasing question; FBA cover is a shipping question. The engine never confuses the two.
Demand capture across the whole catalog. The reorder universe isn’t just the FBA inventory report. Every listing with real order velocity gets a seat at the table, including merchant-fulfilled offers and channel listings your FBA report never mentions. In one catalog audit, about 17% of Amazon revenue was invisible to the brand’s replenishment math because it flowed through non-FBA listings. That demand now reaches reorder quantities, component allocation, and the ship plan.
Forecasting with guardrails. Orders velocity is the primary signal. When a listing has no order history — new products, recovering listings — we fall back to ASIN-level market signals like Keepa sales estimates and traffic data. The guardrail: if a sibling listing on the same ASIN already carries demand in the model, we never estimate on top of it. Double-counted demand is how brands end up shipping 2x what they need.
SKU lifecycle handling. Barcode fixes, relaunches, and catalog restructures mint new SKUs constantly. A naive system sees a new SKU with zero history and forecasts zero. Ours maps every new FBA SKU to its predecessor group and inherits the sales history, so a relabeled bestseller is treated like the bestseller it is. The same logic protects you from the opposite error: a listing that loses its buyable status isn’t necessarily dead — stocked-out FBA listings lose it too. We check the group’s life signs before ever writing a SKU off.
Shared-stock allocation that’s actually fair. Kits, multipacks, and variations frequently draw from one component pool. When the pool can’t cover everyone’s target, allocation happens in tiers: every SKU gets to 30 days of cover, then 60, then full target — with margin-weighted priority inside each tier. Never winner-takes-all. No SKU stocks deep while a sibling sharing the same stock sits at zero.
Margin-aware everything. Every decision in the plan knows its true economics. Fees cascade from actual SP-API fee data to market estimates to category medians when Amazon hasn’t published a number yet. Unit costs come from your most recent purchase orders — with a 24-month lookback — not from a price list that’s been polluted with MSRPs. When the engine ranks what to ship first, it ranks by what actually makes you money.
Who This Is For
You’re a fit if:
- You’re doing $1M+ on Amazon and restock planning still lives in a spreadsheet
- You’ve stocked out of a top-10 SKU in the last quarter
- You sell kits, multipacks, or variations that share physical stock
- You run hybrid FBA/FBM and your FBM demand isn’t in your reorder model
- Your storage fees and aged-inventory surcharges are climbing while bestsellers go dark
- You want profitability analysis built into restock decisions, not bolted on afterward
You’re not a fit if:
- You have fewer than ~25 active SKUs — a simple reorder-point spreadsheet honestly works fine at that scale
- You need someone to also run daily Seller Central operations — that’s account management, which pairs well with this
How We Work
Week 1: Catalog and demand audit. We map your full catalog — FBA, FBM, variations, kits — and reconstruct true velocity per SKU group. This is where invisible demand and double-counted forecasts surface. You get a written report: what your current model sees, what it misses, and what that’s costing you.
Week 2: Policy configuration. Triggers and targets per SKU class, case-pack rounding, supplier lead times, component pool mappings, and cost basis from your PO history. If you run an ERP — NetSuite, Brightpearl, Cin7, whatever — we pull costs and open POs from it directly.
Week 3 onward: The replenishment cycle. Every cycle produces two documents: an FBA ship plan (SKUs, quantities, case packs, ranked by urgency and margin) and a PO plan (what to order from suppliers and when). You approve, we execute or hand off to your team. Every recommendation shows its math — velocity, cover, target, cost — so nothing is a black box.
Reporting. Weekly cover-status dashboards: SKUs below trigger, inbound pipeline, projected stockout dates, aged inventory flags. Monthly reviews tie replenishment performance to revenue and storage-fee trends.
Why Brands Choose Altus Commerce for Replenishment
Most inventory tools are either dumb reorder-point calculators or enterprise systems that take nine months to implement. We built our replenishment engine operating real catalogs with real money on the line, and it encodes the failure modes we’ve been burned by: the phantom “total supply” that masks an FBA stockout, the relabeled SKU that forecasts zero, the MFN listing quietly doing 17% of revenue outside the model, the component pool that starves one sibling to overstock another.
That operational scar tissue is the product. Let’s audit your replenishment math.
What's Included
Days-of-Cover Restock Policy
Every SKU gets a restock trigger and a ship-up-to target based on FBA-side cover — available plus inbound — not vanity stock totals
FBA Ship Plan Generation
A concrete, case-pack-aware shipment plan each cycle: which SKUs, what quantities, ranked by margin contribution and stockout risk
Demand Forecasting with Fallbacks
Orders velocity first, market-data signals (Keepa, traffic) as ASIN-level fallbacks — never double-counting demand across sibling listings
Full-Catalog Demand Capture
Merchant-fulfilled and off-FBA demand seeded into the same reorder math, so no channel is invisible to replenishment
Shared-Stock Fair Allocation
When multiple SKUs draw from one component pool, allocation is tiered and margin-weighted — no winner-takes-all stocking
Purchase Order Planning
Reorder quantities driven by true unit cost from recent POs, supplier lead times, and open-order pipelines
SKU Lifecycle Intelligence
Relabeled and replacement SKUs inherit their predecessor's sales history, so new listings never start from forecast zero
Margin-Aware Prioritization
Fee data cascades from SP-API to market estimates to category medians, so every restock decision knows its true margin
Results We've Delivered
Frequently Asked Questions
Amazon's restock tool doesn't know your supplier lead times, your case packs, your true unit costs, or your merchant-fulfilled demand. It also has no concept of shared stock between SKUs. Our replenishment engine models all of it and produces a shipment plan you can actually execute, not a suggestion you have to second-guess.
Each SKU has a trigger and a target. When FBA-side cover — units available plus units already inbound — drops below the trigger (typically 60 days), the SKU enters the ship plan and gets restocked up to the target (typically 90 days). Warehouse stock and open purchase orders never mask an FBA-side shortage, which is the mistake most spreadsheet models make.
Yes, and most tools can't. Kits, multipacks, and variations often draw from one component pool. We allocate in tiers — everyone gets to 30 days of cover before anyone gets to 60, and margin-weighted priority breaks ties. No SKU stocks deep while a sibling sharing the same stock sits at zero.
That demand is captured too. In one catalog we audited, roughly 17% of Amazon revenue was flowing through listings that the brand's replenishment model couldn't see — merchant-fulfilled offers with real velocity and zero forecast. We seed every listing with sales into the reorder universe, whatever the fulfillment channel.
If a SKU replaced an older listing — a barcode fix, a relaunch, a variation restructure — it inherits the group's sales history instead of starting cold. For genuinely new products, we use market-level demand signals at the ASIN level, carefully, so we never stack an estimate on top of a sibling listing that already carries the demand.
We generate the PO plan — quantities, timing, cost basis — and can work inside your ERP or hand it to your purchasing team. Unit costs come from your most recent purchase orders, not list prices, so reorder math reflects what you actually pay.
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